You can download the complete bibtex file fleuret.bib.
@inproceedings{pagliardini-et-al-2024,
title = {DenseFormer: Enhancing Information Flow in Transformers via Depth Weighted Averaging},
author = {Pagliardini, M. and Mohtashami, A. and Fleuret, F. and Jaggi, M.},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NeurIPS)},
year = {2024},
type = {Poster},
tmp = {https://openreview.net/pdf?id=kMnoh7CXrq},
notes = {To appear}
}
@inproceedings{alonso-et-al-2024,
title = {Diffusion for World Modeling: Visual Details Matter in Atari},
author = {Alonso, E. and Jelley, A. and Micheli, V. and Kanervisto, A. and Storkey, A. and Pearce, T. and Fleuret, F.},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NeurIPS)},
year = {2024},
type = {Spotlight},
tmp = {https://openreview.net/pdf?id=NadTwTODgC},
notes = {To appear}
}
@inproceedings{sinha-fleuret-2024,
author = {Sinha, A. and Fleuret, F.},
title = {DeepEMD: A Transformer-based Fast Estimation of the Earth Mover’s Distance},
booktitle = {Proceedings of the IEEE International Conference on Pattern Recognition (ICPR)},
year = {2024},
url = {https://fleuret.org/papers/sinha-fleuret-icpr2024.pdf},
notes = {To appear}
}
@inproceedings{pannatier-et-al-2024b,
author = {Pannatier, A. and Courdier, E. and Fleuret, F.},
title = {$\sigma$-GPTs: A New Approach to Autoregressive Models},
booktitle = {Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD)},
year = {2024},
tmp = {https://arxiv.org/abs/2404.09562},
note = {to appear}
}
@inproceedings{micheli-et-al-2024,
author = {Micheli, V. and Alonso, E. and Fleuret, F.},
title = {Efficient World Models with Time-Aware and Context-Augmented Tokenization},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2024},
tmp = {https://openreview.net/pdf?id=BiWIERWBFX},
note = {to appear}
}
@inproceedings{wang-et-al-2024,
author = {Wang, K. and Dimitriadis, N. and Ortiz-Jimenez, G. and Fleuret, F. and Frossard, P.},
title = {Localizing Task Information for Improved Model Merging and Compression},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2024},
tmp = {https://openreview.net/pdf?id=DWT9uiGjxT},
note = {to appear}
}
@article{pannatier-et-al-2024,
title = {Inference from Real-World Sparse Measurements},
author = {Pannatier, A. and Matoba, K. and Fleuret, F.},
journal = {Transactions on Machine Learning Research (TMLR)},
year = {2024},
tmp = {https://openreview.net/pdf?id=y9IDfODRns}
}
@article{matoba-et-al-2023,
title = {Benefits of Max Pooling in Neural Networks: Theoretical and Experimental Evidence},
author = {Matoba, K. and Dimitriadis, N. and Fleuret, F.},
journal = {Transactions on Machine Learning Research (TMLR)},
year = {2023},
url = {https://fleuret.org/papers/matoba-et-al-tmlr2023.pdf}
}
@inproceedings{pagliardini-et-al-2023b,
title = {Faster Causal Attention Over Large Sequences Through Sparse Flash Attention},
author = {Pagliardini, M. and Paliotta, D. and Jaggi, M. and Fleuret, F.},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NeurIPS)},
year = {2023},
pages = {59808--59831},
type = {Poster},
url = {https://fleuret.org/papers/pagliardini-et-al-neurips2023.pdf}
}
@inproceedings{sinha-et-al-2023,
author = {Sinha, A. and Paliotta, D. and Máté, B. and Raine, J. and Golling, T. and Fleuret, F.},
title = {SUPA: A Lightweight Diagnostic Simulator for Machine Learning in Particle Physics},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems Datasets and Benchmarks Track (NeurIPS)},
year = {2023},
pages = {64829--64856},
type = {Poster},
url = {https://fleuret.org/papers/sinha-et-al-neurips2023.pdf}
}
@article{kandul-et-al-2023,
author = {Kandul, S. and Micheli, V. and Beck, J. and Burri, T. and Fleuret, F. and Kneer, M. and Christen, M.},
year = {2023},
pages = {100290},
title = {Human control redressed: Comparing AI and human predictability in a real-effort task},
volume = {10},
journal = {Computers in Human Behavior Reports},
url = {https://fleuret.org/papers/kandul-et-al-chbr2023.pdf}
}
@article{mate-fleuret-2023,
author = {M\'at\'e, B. and Fleuret, F.},
title = {Learning Interpolations between Boltzmann Densities},
journal = {Transactions on Machine Learning Research (TMLR)},
year = {2023},
url = {https://fleuret.org/papers/mate-fleuret-tmlr2023.pdf}
}
@inproceedings{mai-et-al-2023,
author = {Mai, F. and Pannatier, A. and Fehr, F. and Chen, H. and Marelli, F. and Fleuret, F. and Henderson, J.},
title = {HyperMixer: An MLP-based Low Cost Alternative to Transformers},
booktitle = {Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL)},
year = {2023},
url = {https://fleuret.org/papers/mai-et-al-acl2023.pdf}
}
@inproceedings{dimitriadis-et-al-2023,
author = {Dimitriadis, N. and Frossard, P. and Fleuret, F.},
title = {Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2023},
url = {https://fleuret.org/papers/dimitriadis-et-al-icml2023.pdf}
}
@book{fleuret-2023,
author = {Fleuret, F.},
title = {The Little Book of Deep Learning},
year = {2023},
publisher = {lulu.com},
isbn = {9781447678618},
url = {https://fleuret.org/public/lbdl.pdf}
}
@inproceedings{johari-et-al-2023,
author = {Johari, M. and Carta, C. and Fleuret, F.},
title = {{ESLAM}: Efficient Dense SLAM System Based on Hybrid Representation of Signed Distance Fields},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2023},
url = {https://fleuret.org/papers/johari-et-al-cvpr2023.pdf}
}
@inproceedings{micheli-et-al-2023,
author = {Micheli, V. and Alonso, E. and Fleuret, F.},
title = {Transformers are Sample Efficient World Models},
booktitle = {Proceedings of the International Conference on Learning Representations (ICLR)},
year = {2023},
type = {Oral},
url = {https://fleuret.org/papers/micheli-et-al-iclr2023.pdf}
}
@inproceedings{pagliardini-et-al-2023,
author = {Pagliardini, M. and Jaggi, M. and Fleuret, F. and Karimireddy, S. P.},
title = {Agree to Disagree: Diversity through Disagreement for Better Transferability},
booktitle = {Proceedings of the International Conference on Learning Representations (ICLR)},
year = {2023},
type = {Oral},
url = {https://fleuret.org/papers/pagliardini-et-al-iclr2023.pdf}
}
@inproceedings{courdier-et-al-2022,
author = {Courdier, E. and Prabhu, T. and Fleuret, F.},
title = {PAUMER: Patch Pausing Transformer for Semantic Segmentation},
booktitle = {Proceedings of the British Machine Vision Conference (BMVC)},
year = {2022},
url = {https://fleuret.org/papers/courdier-et-al-bmvc2022.pdf}
}
@inproceedings{srinivas-et-al-2022,
author = {Srinivas, S. and Matoba, K. and Lakkaraju, H. and Fleuret, F.},
title = {Flatten the Curve: Efficiently Training Low-Curvature Neural Networks},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NeurIPS)},
year = {2022},
pages = {25951--25964},
url = {https://fleuret.org/papers/srinivas-et-al-neurips2022.pdf}
}
@inproceedings{mate-et-al-2022,
author = {M\'at\'e, B. and Klein, S. and Golling, T. and Fleuret, F.},
title = {Flowification: Everything is a normalizing flow},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NeurIPS)},
year = {2022},
url = {https://fleuret.org/papers/mate-et-al-neurips2022.pdf}
}
@inproceedings{courdier-fleuret-2022,
author = {Courdier, E. and Fleuret, F.},
title = {Borrowing from yourself: Faster future video segmentation with partial channel update},
booktitle = {Proceedings of the IEEE International Conference on Pattern Recognition (ICPR)},
year = {2022},
url = {https://fleuret.org/papers/courdier-fleuret-icpr2022.pdf},
pages = {1--8}
}
@inproceedings{johari-et-al-2022,
author = {Johari, M. and Lepoittevin, Y. and Fleuret, F.},
title = {{GeoNeRF}: Generalizing NeRF with Geometry Priors},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2022},
url = {https://fleuret.org/papers/johari-et-al-cvpr2022.pdf}
}
@inproceedings{pannatier-et-al-2022,
author = {Pannatier, A. and Picatoste, R. and Fleuret, F.},
title = {Efficient Wind Speed Nowcasting with {GPU}-Accelerated Nearest Neighbors Algorithm},
booktitle = {Proceedings of the SIAM International Conference on Data Mining (SDM)},
year = {2022},
url = {https://fleuret.org/papers/pannatier-et-al-sdm2022.pdf}
}
@inproceedings{kanervisto-et-al-2022,
title = {MineRL Diamond 2021 Competition: Overview, Results, and Lessons Learned},
author = {Kanervisto, A. and Milani, S. and Ramanauskas, K. and Topin, N. and Lin, Z. and Li, J. and Shi, J. and Ye, D. and Fu, Q. and Yang, W. and Hong, W. and Huang, Z. and Chen, H. and Zeng, G. and Lin, Y. and Micheli, V. and Alonso, E. and Fleuret, F. and Nikulin, A. and Belousov, Y. and Svidchenko, O. and Shpilman, A.},
booktitle = {Proceedings of the NeurIPS Competitions and Demonstrations Track},
pages = {13--28},
year = {2022},
url = {https://fleuret.org/papers/kanervisto-et-al-neurips-compet2022.pdf}
}
@inproceedings{micheli-fleuret-2021,
author = {Micheli, V. and Fleuret, F.},
title = {Language Models are Few-Shot Butlers},
booktitle = {Proceedings of the international conference on Empirical Methods in Natural Language Processing (EMLNP)},
year = {2021},
pages = {9312--9318},
url = {https://fleuret.org/papers/micheli-fleuret-emnlp2021.pdf}
}
@inproceedings{johari-et-al-2021,
author = {Johari, M. and Carta, C. and Fleuret, F.},
title = {DepthInSpace: Exploitation and Fusion of Multiple Video Frames for Structured-Light Depth Estimation},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
pages = {6039--6048},
year = {2021},
type = {Poster},
url = {https://fleuret.org/papers/johari-et-al-iccv2021.pdf}
}
@inproceedings{prabhu-fleuret-2021,
author = {Prabhu, T. and Fleuret, F.},
title = {Uncertainty Reduction for Model Adaptation in Semantic Segmentation},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
pages = {9613--9623},
type = {Poster},
year = {2021},
url = {https://fleuret.org/papers/prabhu-fleuret-cvpr2021.pdf}
}
@inproceedings{prabhu-fleuret-2021b,
author = {Prabhu, T. and Fleuret, F.},
title = {Test time Adaptation through Perturbation Robustness},
booktitle = {Proceedings of the NeurIPS DistShift Workshop (NeurIPS DistShift)},
type = {Poster},
year = {2021},
url = {https://fleuret.org/papers/prabhu-fleuret-distshift2021.pdf}
}
@inproceedings{srinivas-fleuret-2021,
author = {Srinivas, S. and Fleuret, F.},
title = {Rethinking the Role of Gradient-based Attribution Methods for Model Interpretability},
booktitle = {Proceedings of the International Conference on Learning Representations (ICLR)},
year = {2021},
type = {Oral},
url = {https://fleuret.org/papers/srinivas-fleuret-iclr2021.pdf}
}
@inproceedings{chavdarova-et-al-2021,
author = {Chavdarova, T. and Pagliardini, M. and Stich, S. and Fleuret, F. and Jaggi, M.},
title = {Taming {GAN}s with Lookahead-Minmax},
booktitle = {Proceedings of the International Conference on Learning Representations (ICLR)},
year = {2021},
type = {Poster},
url = {https://fleuret.org/papers/chavdarova-et-al-iclr2021.pdf}
}
@inproceedings{vyas-et-al-2020,
author = {Vyas, A. and Katharopoulos, A. and Fleuret, F.},
title = {Fast Transformers with Clustered Attention},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NeurIPS)},
year = {2020},
pages = {21665--21674},
url = {https://fleuret.org/papers/vyas-et-al-neurips2020.pdf}
}
@inproceedings{micheli-et-al-2020,
author = {Micheli, V. and d'Hoffschmidt, M. and Fleuret, F.},
title = {On the importance of pre-training data volume for compact language models},
booktitle = {Proceedings of the international Conference on Empirical Methods in Natural Language Processing (EMNLP)},
year = {2020},
pages = {7853--7858},
url = {https://fleuret.org/papers/micheli-et-al-emnlp2020.pdf}
}
@inproceedings{Matoba2020,
author = {Matoba, K. and Fleuret, F.},
title = {Exact Preimages of Neural Network Aircraft Collision Avoidance Systems},
booktitle = {Machine Learning for Engineering Modeling, Simulation, and Design Workshop at NeurIPS},
year = {2020},
url = {https://fleuret.org/papers/matoba-fleuret-ml4eng2020.pdf}
}
@inproceedings{courdier-fleuret-2020,
author = {Courdier, E. and Fleuret, F.},
title = {Real-Time Segmentation Networks should be Latency Aware},
booktitle = {Proceedings of the Asian Conference on Computer Vision (ACCV)},
year = {2020},
url = {https://fleuret.org/papers/courdier-fleuret-accv2020.pdf},
pages = {603--619}
}
@inproceedings{prabhu-et-al-2020,
author = {Prabhu, T. and Mai, F. and Vogels, T. and Jaggi, M. and Fleuret, F.},
title = {Optimizer Benchmarking Needs to Account for Hyperparameter Tuning},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2020},
url = {https://fleuret.org/papers/prabhu-et-al-icml2020.pdf},
pages = {8837--8846}
}
@inproceedings{katharopoulos-et-al-2020,
author = {Katharopoulos, A. and Vyas, A. and Pappas, N. and Fleuret, F.},
title = {Transformers are {RNN}s: Fast Autoregressive Transformers with Linear Attention},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2020},
url = {https://fleuret.org/papers/katharopoulos-et-al-icml2020.pdf},
pages = {5294--5303}
}
@inproceedings{chavdarova-et-al-2019,
author = {Chavdarova, T. and Gidel, G. and Fleuret, F. and Lacoste-Julien, S.},
title = {Reducing Noise in {GAN} Training with Variance Reduced Extragradient},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NeurIPS)},
year = {2019},
type = {Poster},
pages = {391--401},
url = {https://fleuret.org/papers/chavdarova-et-al-neurips2019.pdf}
}
@inproceedings{srinivas-fleuret-2019,
author = {Srinivas, S. and Fleuret, F.},
title = {Full-Gradient Representation for Neural Network Visualization},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NeurIPS)},
year = {2019},
type = {Poster},
pages = {4126--4135},
url = {https://fleuret.org/papers/srinivas-fleuret-neurips2019.pdf}
}
@inproceedings{tulyakov-et-al-2019,
author = {Tulyakov, S. and Fleuret, F. and Kiefel, M. and Gehler, P. and Hirsch, M.},
title = {Learning an event sequence embedding for event-based deep stereo},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
year = {2019},
type = {Oral},
pages = {1527-1537},
url = {https://fleuret.org/papers/tulyakov-et-al-iccv2019.pdf}
}
@inproceedings{katharopoulos-fleuret-2019,
author = {Katharopoulos, A. and Fleuret, F.},
title = {Processing Megapixel Images with Deep Attention-Sampling Models},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2019},
pages = {3282-3291},
type = {Short oral},
url = {https://fleuret.org/papers/katharopoulos-fleuret-icml2019.pdf}
}
@inproceedings{tulyakov-et-al-2018b,
author = {Tulyakov, S. and Ivanov, A. and Fleuret, F.},
title = {{P}ractical {D}eep {S}tereo ({PDS}): {T}oward applications-friendly deep stereo matching},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NeurIPS)},
year = {2018},
pages = {5874-5884},
type = {Poster},
url = {https://fleuret.org/papers/tulyakov-et-al-neurips2018.pdf}
}
@inproceedings{jose-et-al-2018,
author = {Jose, C. and Ciss\'e, M. and Fleuret, F.},
title = {Kronecker Recurrent Units},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2018},
pages = {2380-2389},
type = {Short oral},
url = {https://fleuret.org/papers/jose-et-al-icml2018.pdf}
}
@inproceedings{srinivas-fleuret-2018,
author = {Srinivas, S. and Fleuret, F.},
title = {Knowledge Transfer with Jacobian Matching},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2018},
pages = {4723-4731},
type = {Short oral},
url = {https://fleuret.org/papers/srinivas-fleuret-icml2018.pdf}
}
@inproceedings{katharopoulos-fleuret-2018,
author = {Katharopoulos, A. and Fleuret, F.},
title = {Not All Samples Are Created Equal: Deep Learning with Importance Sampling},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2018},
pages = {2525-2534},
type = {Short oral},
url = {https://fleuret.org/papers/katharopoulos-fleuret-icml2018.pdf}
}
@inproceedings{baque-et-al-2018,
author = {Baqu\'e, P. and Remelli, E. and Fleuret, F. and Fua, P.},
title = {Geodesic Convolutional Shape Optimization},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2018},
pages = {472-481},
type = {Long oral},
url = {https://fleuret.org/papers/baque-et-al-icml2018.pdf}
}
@inproceedings{chavdarova-fleuret-2018,
author = {Chavdarova, T. and Fleuret, F.},
title = {{SGAN}: An Alternative Training of Generative Adversarial Networks},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2018},
pages = {9407-9415},
url = {https://fleuret.org/papers/chavdarova-fleuret-cvpr2018.pdf}
}
@inproceedings{chavdarova-et-al-2018,
author = {Chavdarova, T. and Baqué, P. and Bouquet, S. and Maksai, A. and Jose, C. and Bagautdinov, T. and Lettry, L. and Fua, P. and Van Gool, L. and Fleuret, F.
},
title = {{WILDTRACK}: A Multi-camera {HD} Dataset for Dense Unscripted Pedestrian Detection},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2018},
pages = {5030-5039},
type = {poster},
url = {https://fleuret.org/papers/chavdarova-et-al-cvpr2018.pdf}
}
@article{tulyakov-et-al-2018,
title = {Geometric calibration of Colour and Stereo Surface Imaging System of {ESA}'s {T}race {G}as {O}rbiter},
author = {Tulyakov, S. and Ivanov, A. and Thomas, N. and Roloff, V. and Pommerol, A. and Cremonese, G. and Weigel, T. and Fleuret, F.},
journal = {Advances in Space Research},
volume = {61},
number = {1},
pages = {487-496},
year = {2018},
url = {https://fleuret.org/papers/tulyakov-et-al-jasr2018.pdf}
}
@inproceedings{newling-fleuret-2017b,
author = {Newling, J. and Fleuret, F.},
title = {K-Medoids For K-Means Seeding},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NIPS)},
pages = {5195-5203},
year = {2017},
type = {Spotlight},
url = {https://fleuret.org/papers/newling-fleuret-nips2017.pdf}
}
@inproceedings{tulyakov-et-al-2017,
author = {Tulyakov, S. and Ivanov, A. and Fleuret, F.},
title = {Weakly Supervised Learning of Deep Metrics for Stereo Reconstruction},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
year = {2017},
type = {Poster},
pages = {1348-1357},
url = {https://fleuret.org/papers/tulyakov-et-al-iccv2017.pdf}
}
@inproceedings{baque-et-al-2017b,
author = {Baqu\'e, P. and Fleuret, F. and Fua, P.},
title = {Deep Occlusion Reasoning for Multi-Camera Multi-Target Detection},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
year = {2017},
type = {Poster},
pages = {271-279},
url = {https://fleuret.org/papers/baque-et-al-iccv2017.pdf}
}
@inproceedings{maksai-et-al-2017,
author = {Maksai, A. and Wang, X. and Fleuret, F. and Fua, P.},
title = {Non-Markovian Globally Consistent Multi-Object Tracking},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
year = {2017},
type = {Poster},
pages = {2563-2573},
url = {https://fleuret.org/papers/maksai-et-al-iccv2017.pdf}
}
@inproceedings{chavdarova-fleuret-2017,
author = {Chavdarova, T. and Fleuret, F.},
title = {Deep Multi-Camera People Detection},
booktitle = {Proceedings of the IEEE International Conference on Machine Learning and Applications (ICMLA)},
year = {2017},
type = {Poster},
pages = {848-853},
url = {https://fleuret.org/papers/chavdarova-fleuret-icmla2017.pdf}
}
@inproceedings{abbasi-et-al-2017b,
author = {Abbasi-Sureshjani, S. and Dasht Bozorg, B. and ter Haar Romeny, B. M. and Fleuret, F.},
title = {Boosted Exudate Segmentation in Retinal Images using Residual Nets},
booktitle = {Proceedings of the MICCAI Workshop on Ophthalmic Medical Image Analysis (OMIA)},
year = {2017},
pages = {210-218},
url = {https://fleuret.org/papers/abbasi-et-al-omia2017.pdf}
}
@inproceedings{baque-et-al-2017,
author = {Baqu\'e, P. and Fleuret, F. and Fua, P.},
title = {Multi-Modal Mean-Fields via Cardinality-Based Clamping},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2017},
type = {Spotlight},
pages = {271-279},
url = {https://fleuret.org/papers/baque-et-al-cvpr2017.pdf}
}
@inproceedings{bagautdinov-et-al-2017,
author = {Bagautdinov, T. and Alahi, A. and Fleuret, F. and Fua, P. and Savarese, S.},
title = {Social Scene Understanding: End-to-End Multi-Person Action Localization and Collective Activity Recognition},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2017},
type = {Oral},
pages = {3425-3434},
url = {https://fleuret.org/papers/bagautdinov-et-al-cvpr2017.pdf}
}
@inproceedings{newling-fleuret-2017,
author = {Newling, J. and Fleuret, F.},
title = {A Sub-Quadratic Exact Medoid Algorithm},
booktitle = {Proceedings of the international conference on Artificial Intelligence and Statistics (AISTATS)},
year = {2017},
type = {Oral},
pages = {185-193},
url = {https://fleuret.org/papers/newling-fleuret-aistats2017.pdf},
note = {(Best paper award)}
}
@inproceedings{abbasi-et-al-2017,
author = {Abbasi-Sureshjani, S. and Dasht Bozorg, B. and ter Haar Romeny, B. M. and Fleuret, F.},
title = {Exploratory Study on Direct Prediction of Diabetes using Deep Residual Networks},
booktitle = {Proceedings of the thematic conference on computational vision and medical image processing (VipIMAGE)},
year = {2017},
url = {https://fleuret.org/papers/abbasi-et-al-vipimage2017.pdf},
pages = {797-802}
}
@article{lefort-et-al-2017,
author = {Lefort, R. and Fusco, L. and Pertz, O. and Fleuret, F.},
title = {Machine learning-based tools to model and to remove the off-target effect},
journal = {Pattern Analysis and Applications (PAA)},
year = {2017},
volume = {20},
number = {1},
pages = {87-100},
url = {https://fleuret.org/papers/lefort-et-al-paa2017.pdf}
}
@article{fleuret-2016,
author = {Fleuret, F.},
title = {Predicting the dynamics of 2d objects with a deep residual network},
journal = {CoRR},
volume = {abs/1610.04032},
year = {2016},
url = {https://arxiv.org/pdf/1610.04032}
}
@inproceedings{newling-fleuret-2016b,
author = {Newling, J. and Fleuret, F.},
title = {Fast mini-batch k-means by nesting},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NIPS)},
year = {2016},
type = {Poster},
pages = {1352-1360},
url = {https://fleuret.org/papers/newling-fleuret-nips2016.pdf}
}
@inproceedings{jose-fleuret-2016,
author = {Jose, C. and Fleuret, F.},
title = {Scalable Metric Learning via Weighted Approximate Rank Component Analysis},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2016},
type = {Poster},
pages = {875-890},
url = {https://fleuret.org/papers/jose-fleuret-eccv2016.pdf}
}
@inproceedings{newling-fleuret-2016,
author = {Newling, J. and Fleuret, F.},
title = {Fast k-means with accurate bounds},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
pages = {936-944},
year = {2016},
type = {Oral},
url = {https://fleuret.org/papers/newling-fleuret-icml2016.pdf}
}
@inproceedings{canevet-et-al-2016,
author = {Can{\'e}vet, O. and Jose, C. and Fleuret, F.},
title = {Importance Sampling Tree for Large-scale Empirical Expectation},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
pages = {1454-1462},
year = {2016},
type = {Oral},
url = {https://fleuret.org/papers/canevet-et-al-icml2016.pdf}
}
@inproceedings{canevet-fleuret-2016,
author = {Can\'evet, O. and Fleuret, F.},
title = {Large Scale Hard Sample Mining with Monte Carlo Tree Search},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2016},
type = {Poster},
pages = {5128-5137},
url = {https://fleuret.org/papers/canevet-fleuret-cvpr2016.pdf}
}
@inproceedings{baque-et-al-2016,
author = {Baqu\'e, P. and Bagautdinov, T. and Fleuret, F. and Fua, P.},
title = {Principled Parallel Mean-Field Inference for Discrete Random Fields},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2016},
type = {Poster},
pages = {5848-5857},
url = {https://fleuret.org/papers/baque-et-al-cvpr2016.pdf}
}
@article{lefakis-fleuret-2016,
author = {Lefakis, L. and Fleuret, F.},
title = {Jointly Informative Feature Selection Made Tractable by Gaussian Modeling},
journal = {Journal of Machine Learning Research (JMLR)},
year = {2016},
pages = {1-39},
volume = {17},
number = {182},
url = {https://fleuret.org/papers/lefakis-fleuret-jmlr2016.pdf}
}
@article{wang-et-al-2016,
author = {Wang, X. and Turetken, E. and Fleuret, F. and Fua, P.},
title = {Tracking Interacting Objects Using Intertwined Flows},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
volume = {38},
number = {11},
pages = {2312-2326},
year = {2016},
url = {https://fleuret.org/papers/wang-et-al-tpami2016.pdf}
}
@article{fusco-et-al-2016,
author = {Fusco, L. and Lefort, R. and Smith, K. and Benmansour, F. and Gonzalez, G. and Barilari, C. and Rinn, B. and Fleuret, F. and Fua, P. and Pertz, O.},
title = {Computer vision profiling of neurite outgrowth dynamics reveals spatio-temporal modularity of Rho GTPase signaling},
journal = {Journal of Cell Biology},
volume = {212},
number = {1},
pages = {91-111},
year = {2016},
url = {https://fleuret.org/papers/fusco-et-al-jcb2016.pdf}
}
@article{suditu-fleuret-2016,
author = {Suditu, N. and Fleuret, F.},
title = {Adaptive relevance feedback for large-scale image retrieval},
journal = {Multimedia Tools and Applications (MTA)},
volume = {75},
number = {12},
pages = {6777--6807},
year = {2016},
url = {https://fleuret.org/papers/suditu-fleuret-mta2016.pdf}
}
@inproceedings{khan-et-al-2015,
author = {Khan, E. and Baqu\'e, P. and Fleuret, F. and Fua, P.},
title = {Kullback-Leibler Proximal Variational Inference},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NIPS)},
year = {2015},
type = {Poster},
url = {https://fleuret.org/papers/khan-et-al-nips2015.pdf},
pages = {3402-3410}
}
@inproceedings{bagautdinov-et-al-2015,
author = {Bagautdinov, T. and Fleuret, F. and Fua, P.},
title = {Probability Occupancy Maps for Occluded Depth Images},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2015},
pages = {2829-2837},
type = {Poster},
url = {https://fleuret.org/papers/bagautdinov-et-al-cvpr2015.pdf}
}
@inproceedings{canevet-fleuret-2014,
author = {Can\'evet, O. and Fleuret, F.},
title = {Efficient Sample Mining for Object Detection},
booktitle = {Proceedings of the Asian Conference on Machine Learning (ACML)},
year = {2014},
pages = {48-63},
type = {Oral},
url = {https://fleuret.org/papers/canevet-fleuret-acml2014.pdf}
}
@inproceedings{canevet-et-al-2014,
author = {Can\'evet, O. and Lefakis, L. and Fleuret, F.},
title = {Sample Distillation for Object Detection and Image Classification},
booktitle = {Proceedings of the Asian Conference on Machine Learning (ACML)},
year = {2014},
pages = {64-79},
type = {Oral},
url = {https://fleuret.org/papers/canevet-et-al-acml2014.pdf}
}
@inproceedings{penate-et-al-2014,
author = {Penate Sanchez, A. and Moreno-Noguer, F. and Andrade Cetto, J. and Fleuret, F.},
title = {{L}{E}{T}{H}{A}: Learning from High Quality Inputs for 3D Pose Estimation in Low Quality Images},
booktitle = {Proceedings of the International Conference on 3D vision (3DV)},
year = {2014},
pages = {517-524},
volume = {1},
type = {Oral},
url = {https://fleuret.org/papers/penate-et-al-3dv2014.pdf}
}
@inproceedings{wang-et-al-2014,
author = {Wang, X. and Turetken, E. and Fleuret, F. and Fua, P.},
title = {Tracking Interacting Objects Optimally Using Integer Programming},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2014},
type = {Oral},
pages = {17-32},
url = {https://fleuret.org/papers/wang-et-al-eccv2014.pdf}
}
@inproceedings{lefakis-fleuret-2014b,
author = {Lefakis, L. and Fleuret, F.},
title = {Dynamic Programming Boosting for Discriminative Macro-Action Discovery},
booktitle = {Proceedings of the International Conference on Machine Learning (ICML)},
year = {2014},
type = {Oral},
pages = {1548-1556},
url = {https://fleuret.org/papers/lefakis-fleuret-icml2014.pdf}
}
@article{dubout-fleuret-2014,
author = {Dubout, C. and Fleuret, F.},
title = {Adaptive Sampling for Large Scale {B}oosting},
journal = {Journal of Machine Learning Research (JMLR)},
year = {2014},
volume = {15},
pages = {1431-1453},
url = {https://fleuret.org/papers/dubout-fleuret-jmlr2014.pdf}
}
@inproceedings{lefakis-fleuret-2014,
author = {Lefakis, L. and Fleuret, F.},
title = {Jointly Informative Feature Selection},
booktitle = {Proceedings of the international conference on Artificial Intelligence and Statistics (AISTATS)},
pages = {567-575},
year = {2014},
type = {Poster},
url = {https://fleuret.org/papers/lefakis-fleuret-aistats2014.pdf}
}
@incollection{fleuret-et-al-2014,
author = {Fleuret, F. and Ben Shitrit, H. and Fua, P.},
editor = {Gong, S. and Cristani, M. and Shuicheng, Y. and Loy, C. C.},
title = {Re-Identification for Improved People Tracking},
booktitle = {Person Re-Identification},
pages = {311-336},
publisher = {Springer},
year = {2014},
url = {https://fleuret.org/papers/fleuret-et-al-chapter2014.pdf}
}
@article{benshitrit-et-al-2013,
author = {Ben Shitrit, H. and Berclaz, J. and Fleuret, F. and Fua, P.},
title = {Multi-Commodity Network Flow for Tracking Multiple People},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
year = {2013},
volume = {36},
number = {8},
pages = {1614-1627},
url = {https://fleuret.org/papers/benshitrit-et-al-tpami2013.pdf}
}
@inproceedings{lefakis-fleuret-2013,
author = {Lefakis, L. and Fleuret, F.},
title = {Reservoir {B}oosting : Between Online and Offline Ensemble Learning},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NIPS)},
pages = {1412-1420},
year = {2013},
type = {Poster},
url = {https://fleuret.org/papers/lefakis-fleuret-nips2013.pdf}
}
@inproceedings{dubout-fleuret-2013b,
author = {Dubout, C. and Fleuret, F.},
title = {Deformable Part Models with Individual Part Scaling},
booktitle = {Proceedings of the British Machine Vision Conference (BMVC)},
year = {2013},
pages = {28.1-28.10},
type = {Poster},
url = {https://fleuret.org/papers/dubout-fleuret-bmvc2013.pdf}
}
@inproceedings{dubout-fleuret-2013,
author = {Dubout, C. and Fleuret, F.},
title = {Accelerated Training of Linear Object Detectors},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
year = {2013},
type = {Oral},
pages = {572-577},
url = {https://fleuret.org/papers/dubout-fleuret-spws2013.pdf}
}
@inproceedings{sznitman-et-al-2013,
author = {Sznitman, R. and Becker, C. and Fleuret, F. and Fua, P.},
title = {Fast Object Detection with Entropy-Driven Evaluation},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2013},
pages = {3270-3277},
type = {Poster},
url = {https://fleuret.org/papers/sznitman-et-al-cvpr2013.pdf}
}
@article{lefort-fleuret-2013,
author = {Lefort, R. and Fleuret, F.},
title = {Tree{K}{L}: A distance between high dimension empirical distributions},
journal = {Pattern Recognition Letters (PRL)},
year = {2013},
volume = {34},
number = {2},
pages = {140-145},
url = {https://fleuret.org/papers/lefort-fleuret-prl2013.pdf}
}
@inproceedings{lefakis-fleuret-2012,
author = {Lefakis, L. and Fleuret, F.},
title = {Macro-Action Discovery Based on Change Point Detection and {B}oosting},
booktitle = {Proceedings of the IEEE International Conference on Machine Learning and Applications (ICMLA)},
year = {2012},
volume = {1},
pages = {574-577},
type = {Poster},
url = {https://fleuret.org/papers/lefakis-fleuret-icmla2012.pdf}
}
@inproceedings{suditu-fleuret-2012,
author = {Suditu, N. and Fleuret, F.},
title = {Iterative Relevance Feedback with Adaptive Exploration / Exploitation Trade-off},
booktitle = {Proceedings of the ACM Conference on Information and Knowledge Management (CIKM)},
year = {2012},
pages = {1323-1331},
type = {Oral},
url = {https://fleuret.org/papers/suditu-fleuret-cimk2012.pdf}
}
@inproceedings{dubout-fleuret-2012,
author = {Dubout, C. and Fleuret, F.},
title = {Exact Acceleration of Linear Object Detectors},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2012},
pages = {301-311},
type = {Oral},
url = {https://fleuret.org/papers/dubout-fleuret-eccv2012.pdf}
}
@inproceedings{lefort-fleuret-2012,
author = {Lefort, R. and Fleuret, F.},
title = {A tree-based distance between distributions: application to classification of neurons},
booktitle = {Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
year = {2012},
pages = {2237-2240},
type = {Poster},
url = {https://fleuret.org/papers/lefort-fleuret-icassp2012.pdf}
}
@article{ali-et-al-2012,
author = {Ali, K. and Fleuret, F. and Hasler, D. and Fua, P.},
title = {A Real-Time Deformable Detector},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
year = {2012},
volume = {34},
number = {2},
pages = {225-239},
url = {https://fleuret.org/papers/ali-et-al-tpami2012.pdf}
}
@article{fleuret-et-al-2011b,
author = {Fleuret, F. and Li, T. and Dubout, C. and Wampler, E. K. and Yantis, S. and Geman, D.},
title = {Comparing machines and humans on a visual categorization test},
journal = {Proceedings of the National Academy of Sciences (PNAS)},
year = {2011},
volume = {108},
number = {43},
pages = {17621-17625},
url = {https://fleuret.org/papers/fleuret-et-al-pnas2011.pdf}
}
@inproceedings{dubout-fleuret-2011b,
author = {Dubout, C. and Fleuret, F.},
title = {{B}oosting with Maximum Adaptive Sampling},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NIPS)},
pages = {1332-1340},
year = {2011},
type = {Poster},
url = {https://fleuret.org/papers/dubout-fleuret-nips2011.pdf}
}
@inproceedings{dubout-fleuret-2011,
author = {Dubout, C. and Fleuret, F.},
title = {Tasting Families of Features for Image Classification},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
pages = {929-936},
year = {2011},
type = {Poster},
url = {https://fleuret.org/papers/dubout-fleuret-iccv2011.pdf}
}
@inproceedings{suditu-fleuret-2011,
author = {Suditu, N. and Fleuret, F.},
title = {{H}{E}{A}{T}: Iterative Relevance Feedback with One Million Images},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
pages = {2118-2125},
year = {2011},
type = {Poster},
url = {https://fleuret.org/papers/suditu-fleuret-iccv2011.pdf}
}
@inproceedings{benshitrit-et-al-2011,
author = {Ben Shitrit, H. and Berclaz, J. and Fleuret, F. and Fua, P.},
title = {Tracking Multiple Objects under Global Appearance Constraints},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
pages = {137-144},
year = {2011},
type = {Poster},
url = {https://fleuret.org/papers/benshitrit-et-al-iccv2011.pdf}
}
@inproceedings{fleuret-et-al-2011,
author = {Fleuret, F. and Abbet, P. and Dubout, C. and Lefakis, L.},
title = {The {M}{A}{S}{H} project},
booktitle = {Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD)},
year = {2011},
pages = {626-629},
type = {Demo},
url = {https://fleuret.org/papers/fleuret-et-al-ecml2011.pdf}
}
@techreport{penedones-et-al-tr2011,
author = {Penedones, H. and Collobert, R. and Fleuret, F. and Grangier, D.},
title = {Improving Object Classification using Pose Information },
institution = {Idiap Research Institute},
year = {2011},
key = {30-2012},
url = {https://fleuret.org/papers/penedones-et-al-tr2011.pdf}
}
@inproceedings{ali-et-al-2011,
author = {Ali, K. and Hasler, D. and Fleuret, F.},
title = {FlowBoost -- {A}ppearance Learning from Sparsely Annotated Video},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
pages = {1433-1440},
year = {2011},
type = {Oral},
url = {https://fleuret.org/papers/ali-hasler-fleuret-cvpr2011.pdf}
}
@article{berclaz-et-al-2011,
title = {Multiple Object Tracking using K-Shortest Paths Optimization},
author = {Berclaz, J. and Fleuret, F. and Turetken, E. and Fua, P.},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
year = {2011},
volume = {33},
number = {9},
pages = {1806-1819},
url = {https://fleuret.org/papers/berclaz-et-al-tpami2011.pdf}
}
@inproceedings{lefakis-fleuret-2010,
author = {Lefakis, L. and Fleuret, F.},
title = {Joint Cascade Optimization Using a Product of Boosted Classifiers},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NIPS)},
year = {2010},
pages = {1315-1323},
type = {Poster},
url = {https://fleuret.org/papers/lefakis-fleuret-nips2010.pdf}
}
@inproceedings{gonzalez-et-al-2010,
author = {Gonzalez, G. and Turetken, E. and Fleuret, F. and Fua, P.},
title = {Delineating Trees in Noisy 2D Images and 3D Image Stacks},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2010},
pages = {2799-2806},
type = {Poster},
url = {https://fleuret.org/papers/gonzalez-et-al-cvpr2010.pdf}
}
@inproceedings{berclaz-et-al-2009,
author = {Berclaz, J. and Fleuret, F. and Fua, P.},
title = {Multiple Object Tracking using Flow Linear Programming},
booktitle = {Proceedings of the 12th IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (Winter-PETS)},
year = {2009},
pages = {1-8},
url = {https://fleuret.org/papers/berclaz-et-al-pets2009.pdf}
}
@inproceedings{berclaz-et-al-2009b,
author = {Berclaz, J. and Shahrokni, A. and Fleuret, F. and Ferryman, J. and Fua, P.},
title = {Evaluation of Probabilistic Occupancy Map People Detection for Surveillance Systems},
booktitle = {Proceedings of the IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (PETS)},
year = {2009},
pages = {55-62},
url = {https://fleuret.org/papers/berclaz-et-al-pets2009b.pdf}
}
@techreport{berclaz-et-al-2009c,
author = {Berclaz, J. and Fleuret, F. and Fua, P.},
title = {Multiple Object Tracking using Flow Linear Programming},
institution = {IDIAP Research Institute},
year = {2009},
number = {10-2009},
url = {https://fleuret.org/papers/berclaz-et-al-rr-10-2009.pdf}
}
@inproceedings{ali-et-al-2009,
author = {Ali, K. and Fleuret, F. and Hasler, D. and Fua, P.},
title = {Joint Pose Estimator and Feature Learning for Object Detection},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
year = {2009},
pages = {1373-1380},
type = {Poster},
url = {https://fleuret.org/papers/ali-et-al-iccv2009.pdf}
}
@inproceedings{gonzalez-et-al-2009,
author = {Gonzalez, G. and Fleuret, F. and Fua, P.},
title = {Learning Rotational Features for Filament Detection},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2009},
pages = {1582-1589},
url = {https://fleuret.org/papers/gonzalez-et-al-cvpr2009.pdf}
}
@inproceedings{gonzalez-et-al-2009b,
author = {Gonzalez, G. and Aguet, F. and Fleuret, F. and Unser, M. and Fua, P.},
title = {Steerable Features for Statistical 3D Dendrite Detection},
booktitle = {Proceedings of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)},
year = {2009},
pages = {625-632},
url = {https://fleuret.org/papers/gonzalez-et-al-miccai2009.pdf}
}
@article{fleuret-2009,
author = {Fleuret, F.},
title = {Multi-Layer {B}oosting for Pattern Recognition},
journal = {Pattern Recognition Letters (PRL)},
year = {2009},
volume = {30},
pages = {237-241},
url = {https://fleuret.org/papers/fleuret-prl2009.pdf}
}
@article{shahrokni-et-al-2009,
author = {Shahrokni, A. and Fleuret, F. and Drummond, T. and Fua, P.},
title = {Classification-based Probabilistic Modeling of Texture Transition for Fast Line Search Tracking and Delineation},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
year = {2009},
volume = {31},
number = {3},
pages = {570-576},
url = {https://fleuret.org/papers/shahrokni-et-al-tpami2009.pdf}
}
@article{fleuret-geman-2008,
author = {Fleuret, F. and Geman, D.},
title = {Stationary Features and Cat Detection},
journal = {Journal of Machine Learning Research (JMLR)},
year = {2008},
volume = {9},
pages = {2549-2578},
url = {https://fleuret.org/papers/fleuret-geman-jmlr2008.pdf}
}
@inproceedings{berclaz-et-al-2008,
author = {Berclaz, J. and Fleuret, F. and Fua, P.},
title = {Multi-Camera Tracking and Atypical Motion Detection with Behavioral Maps},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2008},
pages = {112-125},
url = {https://fleuret.org/papers/berclaz-et-al-eccv2008.pdf}
}
@inproceedings{gonzalez-et-al-2008,
author = {Gonzalez, G. and Fleuret, F. and Fua, P.},
title = {Automated Delineation of Dendritic Networks in Noisy Image Stacks},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2008},
pages = {214-227},
url = {https://fleuret.org/papers/gonzalez-et-al-eccv2008.pdf}
}
@article{fleuret-et-al-2008,
author = {Fleuret, F. and Berclaz, J. and Lengagne, R. and Fua, P.},
title = {Multi-Camera People Tracking with a Probabilistic Occupancy Map},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
year = {2008},
volume = {30},
number = {2},
pages = {267-282},
url = {https://fleuret.org/papers/fleuret-et-al-tpami2008.pdf}
}
@inproceedings{berclaz-fleuret-fua-2008,
author = {Berclaz, J. and Fleuret, F. and Fua, P.},
title = {Principled Detection-by-classification from Multiple Views},
booktitle = {Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP)},
year = {2008},
volume = {2},
pages = {375-382},
url = {https://fleuret.org/papers/berclaz-et-al-visapp2008.pdf}
}
@inproceedings{lanza-et-al-2007,
author = {Lanza, A. and Di Stefano, L. and Berclaz, J. and Fleuret, F. and Fua, P.},
title = {Robust Multi-View Change Detection},
booktitle = {Proceedings of the British Machine Vision Conference (BMVC)},
year = {2007},
url = {https://fleuret.org/papers/lanza-et-al-bmvc2007.pdf}
}
@inproceedings{blanchard-fleuret-2007,
author = {Blanchard, G. and Fleuret, F.},
title = {Occam's Hammer},
booktitle = {Proceedings of the Annual Conference on Learning Theory (COLT)},
year = {2007},
pages = {112-126},
url = {https://fleuret.org/papers/blanchard-fleuret-colt2007.pdf}
}
@techreport{fleuret-et-al-2006,
author = {Fleuret, F. and Berclaz, J. and Lengagne, R. and Fua, P.},
title = {Multi-Camera People Tracking with a Probabilistic Occupancy Map},
institution = {EPFL},
year = {2006},
number = {EPFL/CVLAB2006.06},
url = {https://fleuret.org/papers/fleuret-berclaz-lengagne-fua-TR-EPFL_CVLAB2006.06.pdf}
}
@techreport{fleuret-fua-2006,
author = {Fleuret, F. and Fua, P.},
title = {Dendrite Tracking in Microscopic Images using Minimum Spanning Trees and Localized {E}-{M}},
institution = {EPFL},
year = {2006},
number = {EPFL/CVLAB2006.02},
url = {https://fleuret.org/papers/fleuret-fua-TR-EPFL_CVLAB2006.02.pdf}
}
@inproceedings{berclaz-fleuret-fua-2006,
author = {Berclaz, J. and Fleuret, F. and Fua, P.},
title = {Robust People Tracking with Global Trajectory Optimization},
booktitle = {Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2006},
volume = {1},
pages = {744-750},
url = {https://fleuret.org/papers/berclaz-fleuret-fua-cvpr2006.pdf}
}
@inproceedings{oezuysal-et-al-2006,
author = {Oezuysal, M. and Lepetit, V. and Fleuret, F. and Fua, P.},
title = {Feature Harvesting for Tracking-by-Detection},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2006},
volume = {3953},
pages = {592-605},
url = {https://fleuret.org/papers/oezuysal-et-al-eccv2006.pdf}
}
@misc{fleuret-2006,
author = {Fleuret, F.},
title = {{M}od\`eles G\'en\'eratifs et Efficacit\'e Algorithmique pour la Pr\'ediction},
howpublished = {Habilitation dissertation, University of Paris XIII},
year = {2006},
url = {https://fleuret.org/papers/fleuret-synthese-hdr.pdf}
}
@inproceedings{fleuret-gerstner-2005,
author = {Fleuret, F. and Gerstner, W.},
title = {A {B}ayesian Kernel for the Prediction of Neuron Properties from Binary Gene Profiles},
booktitle = {Proceedings of the IEEE International Conference on Machine Learning and Applications (ICMLA)},
year = {2005},
pages = {129-134},
url = {https://fleuret.org/papers/fleuret-gerstner-icmla2005.pdf}
}
@inproceedings{fleuret-blanchard-2005,
author = {Fleuret, F. and Blanchard, G.},
title = {Pattern Recognition from One Example by {C}hopping},
booktitle = {Proceedings of the international conference on Neural Information Processing Systems (NIPS)},
year = {2005},
pages = {371-378},
url = {https://fleuret.org/papers/fleuret-blanchard-nips2005.pdf}
}
@inproceedings{fleuret-lengagne-fua-2005,
author = {Fleuret, F. and Lengagne, R. and Fua, P.},
title = {Fixed Point Probability Field for Complex Occlusion Handling},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
year = {2005},
volume = {1},
pages = {694-700},
url = {https://fleuret.org/papers/fleuret-lengagne-fua-iccv2005.pdf}
}
@inproceedings{shahrokni-fleuret-fua-2005,
author = {Shahrokni, A. and Fleuret, F. and Fua, P.},
title = {Classifier-based Contour Tracking for Rigid and Deformable Objects},
booktitle = {Proceedings of the British Machine Vision Conference (BMVC)},
year = {2005},
volume = {2},
pages = {699-708},
url = {https://fleuret.org/papers/shahrokni-fleuret-fua-bmvc2005.pdf}
}
@inproceedings{boughorbel-et-al-2005,
author = {Boughorbel, S. and Tarel, J-P. and Fleuret, F. and Boujemaa, N.},
title = {The {G}{C}{S} Kernel For {S}{V}{M} Based Image Recognition},
booktitle = {Proceedings of the International Conference on Artificial Neural Networks (ICANN)},
year = {2005},
volume = {2},
pages = {595-600},
url = {https://fleuret.org/papers/boughorbel-et-al-ICCAN2005.pdf}
}
@article{fleuret-2004,
author = {Fleuret, F.},
title = {Fast Binary Feature Selection with Conditional Mutual Information},
journal = {Journal of Machine Learning Research (JMLR)},
year = {2004},
volume = {5},
pages = {1531-1555},
url = {https://fleuret.org/papers/fleuret-jmlr2004.pdf}
}
@techreport{fleuret-lengagne-fua-2004,
author = {Fleuret, F. and Lengagne, R. and Fua, P.},
title = {Fixed Point Probability Field for Occlusion Handling},
institution = {EPFL},
year = {2004},
number = {IC/2004/87},
url = {https://fleuret.org/papers/IC_TECH_REPORT_200487.pdf}
}
@inproceedings{boughorbel-et-al-2004,
author = {Boughorbel, S. and Tarel, J-P. and Fleuret, F.},
title = {Non-{M}ercer Kernel for {S}{V}{M} Object Recognition},
booktitle = {Proceedings of the British Machine Vision Conference (BMVC)},
year = {2004},
pages = {137-146},
url = {https://fleuret.org/papers/boughorbel-et-al-bmvc2004.pdf}
}
@inproceedings{boujemaa-et-al-2004,
author = {Boujemaa, N. and Fleuret, F. and Gouet, V. and Sahbi, H.},
title = {Automatic Textual Annotation of Video News Based on Semantic Visual Object Extraction},
booktitle = {Proceedings of the conference of the International Society for Optical Engineering (SPIE)},
volume = {5307},
year = {2004},
pages = {329-339},
url = {https://fleuret.org/papers/boujemaa-et-al-spie2004.pdf}
}
@inproceedings{fleuret-sahbi-2003,
author = {Fleuret, F. and Sahbi, H.},
title = {Scale Invariance of Support Vector Machines based on the Triangular Kernel},
booktitle = {Proceedings of the workshop on Statistical and Computational Theories of Vision of the IEEE International Conference on Computer Vision (ICCV/SCTV)},
year = {2003},
url = {https://fleuret.org/papers/sctv2003-fleuret-sahbi.pdf}
}
@article{fleuret-sahbi-ercim2003,
author = {Fleuret, F. and Sahbi, H.},
title = {Coarse-to-fine object detection},
journal = {ERCIM News},
year = {2003},
volume = {55},
url = {https://fleuret.org/papers/fleuret-sahbi-ercim2003.pdf}
}
@inproceedings{rossi-et-al-2002,
author = {Rossi, F. and Conan-Guez, B. and Fleuret, F.},
title = {Functional Data Analysis With Multi Layer Perceptrons},
booktitle = {Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN)},
year = {2002},
pages = {2843-2848},
url = {https://fleuret.org/papers/rossi-conan-fleuret-ijcn2002.pdf}
}
@inproceedings{rossi-et-al-2002b,
author = {Rossi, F. and Conan-Guez, B. and Fleuret, F.},
title = {Theoretical Properties of Functional Multi Layer Perceptrons},
booktitle = {Proceedings of the European Symposium on Artificial Neural Networks (ESANN)},
pages = {7-12},
year = {2002},
url = {https://fleuret.org/papers/rossi-conan-fleuret-esann2002.pdf}
}
@inproceedings{fleuret-geman-2002,
author = {Fleuret, F. and Geman, D.},
title = {Fast Face Detection with Precise Pose Estimation},
booktitle = {Proceedings of the IEEE International Conference on Pattern Recognition (ICPR)},
pages = {235-238},
volume = {1},
year = {2002},
url = {https://fleuret.org/papers/fleuret-geman-icpr2002.pdf}
}
@article{fleuret-geman-2001,
author = {Fleuret, F. and Geman, D.},
title = {Coarse-to-fine Face Detection},
journal = {International Journal of Computer Vision (IJCV)},
year = {2001},
volume = {41},
number = {1/2},
pages = {85-107},
url = {https://fleuret.org/papers/fleuret-geman-preprint-ijcv2001.pdf},
urlps = {https://fleuret.org/papers/fleuret-geman-preprint-ijcv2001.ps.gz}
}
@inproceedings{boujemaa-et-al-2001,
author = {Boujemaa, N. and Fauqueur, F. and Ferecatu, M. and Fleuret, F. and Gouet, V. and Le Saux, B. and Sahbi, H.},
title = {Interactive Specific and Generic Image Retrieval},
booktitle = {Proceedings of the international workshop on Multi-Media Content Based Indexing and Retrieval (MMCBIR)},
year = {2001},
url = {https://fleuret.org/papers/boujemaa-et-al-mmcbir2001.pdf}
}
@phdthesis{fleuret-2000,
author = {Fleuret, F.},
title = {D{\'e}tection hi{\'e}rarchique de visages par apprentissage statistique},
school = {University of Paris VI},
year = {2000},
urlps = {https://fleuret.org/papers/fleuret-these.ps.gz},
url = {https://fleuret.org/papers/fleuret-these.pdf}
}
@inproceedings{fleuret-vezien-2000,
author = {Fleuret, F. and V{\'e}zien, J-M.},
title = {D{\'e}tection de visages dans des s{\'e}quences vid{\'e}o {\`a} l'aide d'arbres de d{\'e}cision},
booktitle = {Actes de la conf\'erence Reconnaissance des Formes et Intelligence Artificielle (RFIA)},
pages = {17-25},
volume = {1},
year = {2000},
url = {https://fleuret.org/papers/fleuret-vezien-rfia2000.pdf}
}
@inproceedings{fleuret-geman-2000,
author = {Fleuret, F. and Geman, D.},
title = {Apprentissage hi{\'e}rarchique pour la d{\'e}tection de visages},
booktitle = {Actes de la conf\'erence Reconnaissance des Formes et Intelligence Artificielle (RFIA)},
pages = {349-357},
volume = {2},
year = {2000},
url = {https://fleuret.org/papers/fleuret-geman-rfia2000.pdf}
}
@article{fleuret-brunet-2000,
author = {Fleuret, F. and Brunet, E.},
title = {{D}{E}{A}~: An Architecture for Goal Planning and Classification},
journal = {Neural Computation},
year = {2000},
volume = {12},
pages = {1987-2008},
url = {https://fleuret.org/papers/fleuret-brunet-preprint-nc2000.pdf}
}
@inproceedings{fleuret-geman-1999,
author = {Fleuret, F. and Geman, D.},
title = {Graded learning for object detection},
booktitle = {Proceedings of the workshop on Statistical and Computational Theories of Vision of the IEEE international conference on Computer Vision and Pattern Recognition (CVPR/SCTV)},
year = {1999},
url = {https://fleuret.org/papers/fleuret-geman-cvpr1999.pdf},
urlps = {https://fleuret.org/papers/fleuret-geman-cvpr1999.ps.gz}
}
@inproceedings{oisel-et-al-1998,
author = {Oisel, L. and Fleuret, F. and Horain, P. and Morin, L. and V{\'e}zien, J. M. and Pr{\^e}teux, F. and Gagalowicz, A. and Labit, C. and Leray, P.},
title = {Analyse de s{\'e}quences non calibr{\'e}es pour la reconstruction 3D de sc{\`e}nes},
booktitle = {Actes de la conf\'erence Reconnaissance des Formes et Intelligence Artificielle (RFIA)},
pages = {189-198},
volume = {1},
year = {1998},
url = {https://fleuret.org/papers/oisel-et-al-rfia1998.pdf}
}
@inproceedings{jedynak-fleuret-1996,
author = {Jedynak, B. and Fleuret, F.},
title = {Reconnaissance d'objets 3D {\`a} l'aide d'arbres de classification},
booktitle = {Actes de la conf\'erence Images et Communication (IMAGECOM)},
year = {1996},
url = {https://fleuret.org/papers/jedynak-fleuret-imagecom1996.pdf},
urlps = {https://fleuret.org/papers/jedynak-fleuret-imagecom1996.ps.gz}
}