You can download the complete bibtex file fleuret.bib.

@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)},
  note = {(to appear)},
  year = {2021},
  url = {https://fleuret.org/papers/prabhu-fleuret-cvpr2021.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{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}
}