You can download the complete bibtex file fleuret.bib.
@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}, note = {(to appear)} }
@inproceedings{chavdarova-et-al-2021, author = {Chavdarova, T. and Pagliardini, M. and Stich, S. and Fleuret, F. and Jaggi, M.}, title = {Taming GANs with Lookahead-Minmax}, booktitle = {Proceedings of the International Conference on Learning Representations (ICLR)}, year = {2021}, type = {Poster}, note = {(to appear)} }
@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}, url = {https://fleuret.org/papers/vyas-et-al-neurips2020.pdf}, note = {(to appear)} }
@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}, note = {(to appear)} }
@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} }