Zaïd Harchaoui

157 papers A* 32A 10C 1Misc 8Journal 83Unranked 23

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	A Generalization Theory for Zero-Shot Prediction. ICML Ronak Mehta, Zaïd Harchaoui
2025	J	`jnl`	A Generalization Theory for Zero-Shot Prediction. CoRR Ronak Mehta, Zaïd Harchaoui
2025	J	`jnl`	BroRL: Scaling Reinforcement Learning via Broadened Exploration. CoRR Jian Hu, Mingjie Liu, Ximing Lu, Fang Wu, Zaïd Harchaoui, Shizhe Diao, Yejin Choi, Pavlo Molchanov, June Yang, Jan Kautz, Yi Dong
2025	J	`jnl`	On Global and Local Convergence of Iterative Linear Quadratic Optimization Algorithms for Discrete Time Nonlinear Control. J. Mach. Learn. Res. Vincent Roulet, Siddhartha S. Srinivasa, Maryam Fazel, Zaïd Harchaoui
2025	A	`conf`	Spectral Differential Network Analysis for High-Dimensional Time Series. AISTATS Michael Hellstern, Byol Kim, Zaïd Harchaoui, Ali Shojaie
2025	J	`jnl`	Stochastic Gradients under Nuisances. CoRR Facheng Yu, Ronak Mehta, Alex Luedtke, Zaïd Harchaoui
2025	J	`jnl`	Supervised Stochastic Gradient Algorithms for Multi-Trial Source Separation. CoRR Ronak Mehta, Mateus P. Otto, Noah Stanis, Azadeh Yazdan-Shahmorad, Zaïd Harchaoui
2025	J	`jnl`	The Invisible Leash: Why RLVR May Not Escape Its Origin. CoRR Fang Wu, Weihao Xuan, Ximing Lu, Zaïd Harchaoui, Yejin Choi
2024	J	`jnl`	A Primal-Dual Algorithm for Faster Distributionally Robust Optimization. CoRR Ronak Mehta, Jelena Diakonikolas, Zaïd Harchaoui
2024	A*	`conf`	Distributionally Robust Optimization with Bias and Variance Reduction. ICLR Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaïd Harchaoui
2024	A*	`conf`	Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization. NeurIPS Ronak Mehta, Jelena Diakonikolas, Zaïd Harchaoui
2024	J	`jnl`	Federated learning with superquantile aggregation for heterogeneous data. Mach. Learn. Krishna Pillutla, Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
2024	J	`jnl`	From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models. CoRR Sean Welleck, Amanda Bertsch, Matthew Finlayson, Hailey Schoelkopf, Alex Xie, Graham Neubig, Ilia Kulikov, Zaïd Harchaoui
2024	J	`jnl`	From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models. Trans. Mach. Learn. Res. Sean Welleck, Amanda Bertsch, Matthew Finlayson, Hailey Schoelkopf, Alex Xie, Graham Neubig, Ilia Kulikov, Zaïd Harchaoui
2024	J	`jnl`	Iterative Linear Quadratic Optimization for Nonlinear Control: Differentiable Programming Algorithmic Templates. Open J. Math. Optim. Vincent Roulet, Siddhartha S. Srinivasa, Maryam Fazel, Zaïd Harchaoui
2024	—	`conf`	JAMDEC: Unsupervised Authorship Obfuscation using Constrained Decoding over Small Language Models. NAACL-HLT Jillian Fisher, Ximing Lu, Jaehun Jung, Liwei Jiang, Zaïd Harchaoui, Yejin Choi
2024	J	`jnl`	JAMDEC: Unsupervised Authorship Obfuscation using Constrained Decoding over Small Language Models. CoRR Jillian Fisher, Ximing Lu, Jaehun Jung, Liwei Jiang, Zaïd Harchaoui, Yejin Choi
2024	A*	`conf`	StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style Elements. EMNLP Jillian Fisher, Skyler Hallinan, Ximing Lu, Mitchell L. Gordon, Zaïd Harchaoui, Yejin Choi
2024	J	`jnl`	StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style Elements. CoRR Jillian Fisher, Skyler Hallinan, Ximing Lu, Mitchell L. Gordon, Zaïd Harchaoui, Yejin Choi
2024	A*	`conf`	The Benefits of Balance: From Information Projections to Variance Reduction. NeurIPS Lang Liu, Ronak Mehta, Soumik Pal, Zaïd Harchaoui
2024	J	`jnl`	The Benefits of Balance: From Information Projections to Variance Reduction. CoRR Lang Liu, Ronak Mehta, Soumik Pal, Zaïd Harchaoui
2024	Misc	`conf`	The Rao, Wald, And Likelihood-Ratio Tests under Generalized Self-Concordance. ICASSP Lang Liu, Zaïd Harchaoui
2023	J	`jnl`	Distributionally Robust Optimization with Bias and Variance Reduction. CoRR Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaïd Harchaoui
2023	A*	`conf`	Faith and Fate: Limits of Transformers on Compositionality. NeurIPS Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Lorraine Li, Liwei Jiang, Bill Yuchen Lin, Sean Welleck, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena D. Hwang, Soumya Sanyal, Xiang Ren, Allyson Ettinger, Zaïd Harchaoui, Yejin Choi
2023	J	`jnl`	Faith and Fate: Limits of Transformers on Compositionality. CoRR Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Lorraine Li, Liwei Jiang, Bill Yuchen Lin, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena D. Hwang, Soumya Sanyal, Sean Welleck, Xiang Ren, Allyson Ettinger, Zaïd Harchaoui, Yejin Choi
2023	J	`jnl`	FiLM: Fill-in Language Models for Any-Order Generation. CoRR Tianxiao Shen, Hao Peng, Ruoqi Shen, Yao Fu, Zaïd Harchaoui, Yejin Choi
2023	A	`conf`	Influence Diagnostics under Self-concordance. AISTATS Jillian Fisher, Lang Liu, Krishna Pillutla, Yejin Choi, Zaïd Harchaoui
2023	J	`jnl`	MAUVE Scores for Generative Models: Theory and Practice. J. Mach. Learn. Res. Krishna Pillutla, Lang Liu, John Thickstun, Sean Welleck, Swabha Swayamdipta, Rowan Zellers, Sewoong Oh, Yejin Choi, Zaïd Harchaoui
2023	—	`conf`	Modified Gauss-Newton Algorithms under Noise. SSP Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaïd Harchaoui
2023	J	`jnl`	Modified Gauss-Newton Algorithms under Noise. CoRR Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaïd Harchaoui
2023	J	`jnl`	Revisiting Convolutional Neural Networks from the Viewpoint of Kernel-Based Methods. J. Comput. Graph. Stat. Corinne Jones, Vincent Roulet, Zaïd Harchaoui
2023	A	`conf`	Stochastic Optimization for Spectral Risk Measures. AISTATS Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaïd Harchaoui
2023	J	`jnl`	Stochastic Optimization under Distributional Drift. J. Mach. Learn. Res. Joshua Cutler, Dmitriy Drusvyatskiy, Zaïd Harchaoui
2023	J	`jnl`	Target Propagation via Regularized Inversion for Recurrent Neural Networks. Trans. Mach. Learn. Res. Vincent Roulet, Zaïd Harchaoui
2022	J	`jnl`	A Bayesian approach to modeling phytoplankton population dynamics from size distribution time series. PLoS Comput. Biol. Jann Paul Mattern, Kristof Glauninger, Gregory L. Britten, John R. Casey, Sangwon Hyun, Zhen Wu, E. Virginia Armbrust, Zaïd Harchaoui, Francois Ribalet
2022	Misc	`conf`	Differentiable Programming A La Moreau. ICASSP Vincent Roulet, Zaïd Harchaoui
2022	J	`jnl`	Discriminative clustering with representation learning with any ratio of labeled to unlabeled data. Stat. Comput. Corinne Jones, Vincent Roulet, Zaïd Harchaoui
2022	A	`conf`	Entropy Regularized Optimal Transport Independence Criterion. AISTATS Lang Liu, Soumik Pal, Zaïd Harchaoui
2022	J	`jnl`	Iterative Linear Quadratic Optimization for Nonlinear Control: Differentiable Programming Algorithmic Templates. CoRR Vincent Roulet, Siddhartha S. Srinivasa, Maryam Fazel, Zaïd Harchaoui
2022	J	`jnl`	MAUVE Scores for Generative Models: Theory and Practice. CoRR Krishna Pillutla, Lang Liu, John Thickstun, Sean Welleck, Swabha Swayamdipta, Rowan Zellers, Sewoong Oh, Yejin Choi, Zaïd Harchaoui
2022	A*	`conf`	Orthogonal Statistical Learning with Self-Concordant Loss. COLT Lang Liu, Carlos Cinelli, Zaïd Harchaoui
2022	J	`jnl`	Orthogonal Statistical Learning with Self-Concordant Loss. CoRR Lang Liu, Carlos Cinelli, Zaïd Harchaoui
2022	J	`jnl`	Robust Aggregation for Federated Learning. IEEE Trans. Signal Process. Krishna Pillutla, Sham M. Kakade, Zaïd Harchaoui
2022	J	`jnl`	Statistical and Computational Guarantees for Influence Diagnostics. CoRR Jillian Fisher, Lang Liu, Krishna Pillutla, Yejin Choi, Zaïd Harchaoui
2022	J	`jnl`	Stochastic Optimization for Spectral Risk Measures. CoRR Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaïd Harchaoui
2022	J	`jnl`	Stochastic optimization on matrices and a graphon McKean-Vlasov limit. CoRR Zaïd Harchaoui, Sewoong Oh, Soumik Pal, Raghav Somani, Raghavendra Tripathi
2022	J	`jnl`	Superquantile-Based Learning: A Direct Approach Using Gradient-Based Optimization. J. Signal Process. Syst. Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
2022	A	`conf`	Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates. AISTATS Nicholas J. Irons, Meyer Scetbon, Soumik Pal, Zaïd Harchaoui
2021	A	`conf`	A Spectral Analysis of Dot-product Kernels. AISTATS Meyer Scetbon, Zaïd Harchaoui
2021	Misc	`conf`	A Superquantile Approach to Federated Learning with Heterogeneous Devices. CISS Yassine Laguel, Krishna Pillutla, Jérôme Malick, Zaïd Harchaoui
2021	J	`jnl`	Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao
2021	A*	`conf`	Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals. NeurIPS Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaïd Harchaoui
2021	J	`jnl`	Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral. CoRR Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaïd Harchaoui
2021	J	`jnl`	Entropy Regularized Optimal Transport Independence Criterion. CoRR Lang Liu, Soumik Pal, Zaïd Harchaoui
2021	—	`conf`	Faster Policy Learning with Continuous-Time Gradients. L4DC Samuel K. Ainsworth, Kendall Lowrey, John Thickstun, Zaïd Harchaoui, Siddhartha S. Srinivasa
2021	J	`jnl`	Federated Learning with Heterogeneous Data: A Superquantile Optimization Approach. CoRR Krishna Pillutla, Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
2021	J	`jnl`	MAUVE: Human-Machine Divergence Curves for Evaluating Open-Ended Text Generation. CoRR Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Yejin Choi, Zaïd Harchaoui
2021	A*	`conf`	MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers. NeurIPS Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Sean Welleck, Yejin Choi, Zaïd Harchaoui
2021	Misc	`conf`	On the Smoothing of Deep Networks. CISS Vincent Roulet, Zaïd Harchaoui
2021	Misc	`conf`	Score-Based Change Detection For Gradient-Based Learning Machines. ICASSP Lang Liu, Joseph Salmon, Zaïd Harchaoui
2021	J	`jnl`	Score-Based Change Detection for Gradient-Based Learning Machines. CoRR Lang Liu, Joseph Salmon, Zaïd Harchaoui
2021	J	`jnl`	Stochastic optimization under time drift: iterate averaging, step decay, and high probability guarantees. CoRR Joshua Cutler, Dmitriy Drusvyatskiy, Zaïd Harchaoui
2021	A*	`conf`	Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees. NeurIPS Joshua Cutler, Dmitriy Drusvyatskiy, Zaïd Harchaoui
2021	J	`jnl`	Target Propagation via Regularized Inversion. CoRR Vincent Roulet, Zaïd Harchaoui
2021	J	`jnl`	Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates. CoRR Nicholas J. Irons, Meyer Scetbon, Soumik Pal, Zaïd Harchaoui
2020	J	`jnl`	An Elementary Approach to Convergence Guarantees of Optimization Algorithms for Deep Networks. CoRR Vincent Roulet, Zaïd Harchaoui
2020	J	`jnl`	Device Heterogeneity in Federated Learning: A Superquantile Approach. CoRR Yassine Laguel, Krishna Pillutla, Jérôme Malick, Zaïd Harchaoui
2020	J	`jnl`	Differentiable Programming à la Moreau. CoRR Vincent Roulet, Zaïd Harchaoui
2020	—	`conf`	End-to-End Learning for Retrospective Change-Point Estimation. MLSP Corinne Jones, Zaïd Harchaoui
2020	J	`jnl`	Faster Policy Learning with Continuous-Time Gradients. CoRR Samuel K. Ainsworth, Kendall Lowrey, John Thickstun, Zaïd Harchaoui, Siddhartha S. Srinivasa
2020	—	`conf`	First-Order Optimization for Superquantile-Based Supervised Learning. MLSP Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
2020	J	`jnl`	First-order Optimization for Superquantile-based Supervised Learning. CoRR Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
2020	A*	`conf`	Harmonic Decompositions of Convolutional Networks. ICML Meyer Scetbon, Zaïd Harchaoui
2020	J	`jnl`	Harmonic Decompositions of Convolutional Networks. CoRR Meyer Scetbon, Zaïd Harchaoui
2020	C	`conf`	On the Convergence of the Iterative Linear Exponential Quadratic Gaussian Algorithm to Stationary Points. ACC Vincent Roulet, Maryam Fazel, Siddhartha S. Srinivasa, Zaïd Harchaoui
2020	J	`jnl`	Risk Bounds for Multi-layer Perceptrons through Spectra of Integral Operators. CoRR Meyer Scetbon, Zaïd Harchaoui
2019	J	`jnl`	A Kernel Multiple Change-point Algorithm via Model Selection. J. Mach. Learn. Res. Sylvain Arlot, Alain Celisse, Zaïd Harchaoui
2019	A*	`conf`	A Simple Adaptive Tracker with Reminiscences. ICRA Christopher Xie, Emily B. Fox, Zaïd Harchaoui
2019	J	`jnl`	A Smoother Way to Train Structured Prediction Models. CoRR Venkata Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaïd Harchaoui
2019	A*	`conf`	A Statistical Investigation of Long Memory in Language and Music. ICML Alexander Greaves-Tunnell, Zaïd Harchaoui
2019	J	`jnl`	A Statistical Investigation of Long Memory in Language and Music. CoRR Alexander Greaves-Tunnell, Zaïd Harchaoui
2019	J	`jnl`	Advances and Open Problems in Federated Learning. CoRR Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao
2019	—	`conf`	An Elementary Approach to Convergence Guarantees of Optimization Algorithms for Deep Networks. Allerton Vincent Roulet, Zaïd Harchaoui
2019	J	`jnl`	An Inexact Variable Metric Proximal Point Algorithm for Generic Quasi-Newton Acceleration. SIAM J. Optim. Hongzhou Lin, Julien Mairal, Zaïd Harchaoui
2019	—	`conf`	Coupled Recurrent Models for Polyphonic Music Composition. ISMIR John Thickstun, Zaïd Harchaoui, Dean P. Foster, Sham M. Kakade
2019	J	`jnl`	End-to-end Learning, with or without Labels. CoRR Corinne Jones, Vincent Roulet, Zaïd Harchaoui
2019	A*	`conf`	Iterative Linearized Control: Stable Algorithms and Complexity Guarantees. ICML Vincent Roulet, Dmitriy Drusvyatskiy, Siddhartha S. Srinivasa, Zaïd Harchaoui
2019	J	`jnl`	Kernel-based Translations of Convolutional Networks. CoRR Corinne Jones, Vincent Roulet, Zaïd Harchaoui
2019	A*	`conf`	Object Discovery in Videos as Foreground Motion Clustering. CVPR Christopher Xie, Yu Xiang, Zaïd Harchaoui, Dieter Fox
2019	J	`jnl`	Robust Aggregation for Federated Learning. CoRR Venkata Krishna Pillutla, Sham M. Kakade, Zaïd Harchaoui
2018	A*	`conf`	A Smoother Way to Train Structured Prediction Models. NeurIPS Venkata Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaïd Harchaoui
2018	A	`conf`	Catalyst for Gradient-based Nonconvex Optimization. AISTATS Courtney Paquette, Hongzhou Lin, Dmitriy Drusvyatskiy, Julien Mairal, Zaïd Harchaoui
2018	J	`jnl`	Coupled Recurrent Models for Polyphonic Music Composition. CoRR John Thickstun, Zaïd Harchaoui, Dean P. Foster, Sham M. Kakade
2018	A*	`conf`	Efficient First-Order Algorithms for Adaptive Signal Denoising. ICML Dmitrii Ostrovskii, Zaïd Harchaoui
2018	Misc	`conf`	Invariances and Data Augmentation for Supervised Music Transcription. ICASSP John Thickstun, Zaïd Harchaoui, Dean P. Foster, Sham M. Kakade
2018	J	`jnl`	Object Discovery in Videos as Foreground Motion Clustering. CoRR Christopher Xie, Yu Xiang, Dieter Fox, Zaïd Harchaoui
2018	A*	`conf`	Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm (Extended Abstract). IJCAI Yury Maximov, Massih-Reza Amini, Zaïd Harchaoui
2018	J	`jnl`	Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm. J. Artif. Intell. Res. Yury Maximov, Massih-Reza Amini, Zaïd Harchaoui
2017	J	`jnl`	Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice. J. Mach. Learn. Res. Hongzhou Lin, Julien Mairal, Zaïd Harchaoui
2017	J	`jnl`	Convolutional Patch Representations for Image Retrieval: An Unsupervised Approach. Int. J. Comput. Vis. Mattis Paulin, Julien Mairal, Matthijs Douze, Zaïd Harchaoui, Florent Perronnin, Cordelia Schmid
2017	—	`conf`	Inferring the Structure of Action Movies. WICED@Eurographics Danila Potapov, Matthijs Douze, Jérôme Revaud, Zaïd Harchaoui, Cordelia Schmid
2017	J	`jnl`	Invariances and Data Augmentation for Supervised Music Transcription. CoRR John Thickstun, Zaïd Harchaoui, Dean P. Foster, Sham M. Kakade
2017	—	`conf`	Learning Features of Music From Scratch. ICLR (Poster) John Thickstun, Zaïd Harchaoui, Sham M. Kakade
2017	Misc	`conf`	The group k-support norm for learning with structured sparsity. ICASSP Nikhil Rao, Miroslav Dudík, Zaïd Harchaoui
2016	J	`jnl`	Convolutional Patch Representations for Image Retrieval: an Unsupervised Approach. CoRR Mattis Paulin, Julien Mairal, Matthijs Douze, Zaïd Harchaoui, Florent Perronnin, Cordelia Schmid
2016	J	`jnl`	DeepMatching: Hierarchical Deformable Dense Matching. Int. J. Comput. Vis. Jérôme Revaud, Philippe Weinzaepfel, Zaïd Harchaoui, Cordelia Schmid
2016	J	`jnl`	Fast and Simple Optimization for Poisson Likelihood Models. CoRR Niao He, Zaïd Harchaoui, Yichen Wang, Le Song
2016	J	`jnl`	Label-Embedding for Image Classification. IEEE Trans. Pattern Anal. Mach. Intell. Zeynep Akata, Florent Perronnin, Zaïd Harchaoui, Cordelia Schmid
2016	J	`jnl`	Learning Features of Music from Scratch. CoRR John Thickstun, Zaïd Harchaoui, Sham M. Kakade
2016	J	`jnl`	Rademacher Complexity Bounds for a Penalized Multiclass Semi-Supervised Algorithm. CoRR Yury Maximov, Massih-Reza Amini, Zaïd Harchaoui
2016	—	`conf`	Structure-Blind Signal Recovery. NIPS Dmitry Ostrovsky, Zaïd Harchaoui, Anatoli B. Juditsky, Arkadi Nemirovski
2015	—	`conf`	A Universal Catalyst for First-Order Optimization. NIPS Hongzhou Lin, Julien Mairal, Zaïd Harchaoui
2015	A*	`conf`	Adaptive Recovery of Signals by Convex Optimization. COLT Zaïd Harchaoui, Anatoli B. Juditsky, Arkadi Nemirovski, Dmitry Ostrovsky
2015	J	`jnl`	Beat-Event Detection in Action Movie Franchises. CoRR Danila Potapov, Matthijs Douze, Jérôme Revaud, Zaïd Harchaoui, Cordelia Schmid
2015	J	`jnl`	Conditional gradient algorithms for norm-regularized smooth convex optimization. Math. Program. Zaïd Harchaoui, Anatoli B. Juditsky, Arkadi Nemirovski
2015	J	`jnl`	Deep Convolutional Matching. CoRR Jérôme Revaud, Philippe Weinzaepfel, Zaïd Harchaoui, Cordelia Schmid
2015	J	`jnl`	EpicFlow: Edge-Preserving Interpolation of Correspondences for Optical Flow. CoRR Jérôme Revaud, Philippe Weinzaepfel, Zaïd Harchaoui, Cordelia Schmid
2015	A*	`conf`	EpicFlow: Edge-preserving interpolation of correspondences for optical flow. CVPR Jérôme Revaud, Philippe Weinzaepfel, Zaïd Harchaoui, Cordelia Schmid
2015	J	`jnl`	Label-Embedding for Image Classification. CoRR Zeynep Akata, Florent Perronnin, Zaïd Harchaoui, Cordelia Schmid
2015	A*	`conf`	Learning to Track for Spatio-Temporal Action Localization. ICCV Philippe Weinzaepfel, Zaïd Harchaoui, Cordelia Schmid
2015	A*	`conf`	Learning to detect Motion Boundaries. CVPR Philippe Weinzaepfel, Jérôme Revaud, Zaïd Harchaoui, Cordelia Schmid
2015	J	`jnl`	Learning to track for spatio-temporal action localization. CoRR Philippe Weinzaepfel, Zaïd Harchaoui, Cordelia Schmid
2015	A*	`conf`	Local Convolutional Features with Unsupervised Training for Image Retrieval. ICCV Mattis Paulin, Matthijs Douze, Zaïd Harchaoui, Julien Mairal, Florent Perronnin, Cordelia Schmid
2015	—	`conf`	Semi-Proximal Mirror-Prox for Nonsmooth Composite Minimization. NIPS Niao He, Zaïd Harchaoui
2015	J	`jnl`	Semi-proximal Mirror-Prox for Nonsmooth Composite Minimization. CoRR Niao He, Zaïd Harchaoui
2014	J	`jnl`	Activity representation with motion hierarchies. Int. J. Comput. Vis. Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid
2014	—	`conf`	Category-Specific Video Summarization. ECCV (6) Danila Potapov, Matthijs Douze, Zaïd Harchaoui, Cordelia Schmid
2014	—	`conf`	Convolutional Kernel Networks. NIPS Julien Mairal, Piotr Koniusz, Zaïd Harchaoui, Cordelia Schmid
2014	J	`jnl`	Convolutional Kernel Networks. CoRR Julien Mairal, Piotr Koniusz, Zaïd Harchaoui, Cordelia Schmid
2014	A*	`conf`	Fast and Robust Archetypal Analysis for Representation Learning. CVPR Yuansi Chen, Julien Mairal, Zaïd Harchaoui
2014	J	`jnl`	Fast and Robust Archetypal Analysis for Representation Learning. CoRR Yuansi Chen, Julien Mairal, Zaïd Harchaoui
2014	J	`jnl`	Good Practice in Large-Scale Learning for Image Classification. IEEE Trans. Pattern Anal. Mach. Intell. Zeynep Akata, Florent Perronnin, Zaïd Harchaoui, Cordelia Schmid
2014	A*	`conf`	On learning to localize objects with minimal supervision. ICML Hyun Oh Song, Ross B. Girshick, Stefanie Jegelka, Julien Mairal, Zaïd Harchaoui, Trevor Darrell
2014	J	`jnl`	One-Bit Object Detection: On learning to localize objects with minimal supervision. CoRR Hyun Oh Song, Ross B. Girshick, Stefanie Jegelka, Julien Mairal, Zaïd Harchaoui, Trevor Darrell
2014	—	`conf`	The INRIA-LIM-VocR and AXES submissions to TrecVid 2014 Multimedia Event Detection. TRECVID Matthijs Douze, Dan Oneata, Mattis Paulin, Clément Leray, Nicolas Chesneau, Danila Potapov, Jakob Verbeek, Karteek Alahari, Zaïd Harchaoui, Lori Lamel, Jean-Luc Gauvain, Christoph Schmidt, Cordelia Schmid
2014	A*	`conf`	Transformation Pursuit for Image Classification. CVPR Mattis Paulin, Jérôme Revaud, Zaïd Harchaoui, Florent Perronnin, Cordelia Schmid
2013	J	`jnl`	Automatic Recognition of Human Activities in Realistic Videos. ERCIM News Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid
2013	A*	`conf`	DeepFlow: Large Displacement Optical Flow with Deep Matching. ICCV Philippe Weinzaepfel, Jérôme Revaud, Zaïd Harchaoui, Cordelia Schmid
2013	J	`jnl`	Kernel-Based Methods for Hypothesis Testing: A Unified View. IEEE Signal Process. Mag. Zaïd Harchaoui, Francis R. Bach, Olivier Cappé, Eric Moulines
2013	A*	`conf`	Label-Embedding for Attribute-Based Classification. CVPR Zeynep Akata, Florent Perronnin, Zaïd Harchaoui, Cordelia Schmid
2013	J	`jnl`	Temporal Localization of Actions with Actoms. IEEE Trans. Pattern Anal. Mach. Intell. Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid
2013	—	`conf`	The AXES submissions at TRECVID 2013. TRECVID Robin Aly, Relja Arandjelovic, Ken Chatfield, Matthijs Douze, Basura Fernando, Zaïd Harchaoui, Kevin McGuinness, Noel E. O'Connor, Dan Oneata, Omkar M. Parkhi, Danila Potapov, Jérôme Revaud, Cordelia Schmid, Jochen Schwenninger, David Scott, Tinne Tuytelaars, Jakob Verbeek, Heng Wang, Andrew Zisserman
2012	—	`conf`	AXES at TRECVID 2012: KIS, INS, and MED. TRECVID Robin Aly, Kevin McGuinness, Shu Chen, Noel E. O'Connor, Ken Chatfield, Omkar M. Parkhi, Relja Arandjelovic, Andrew Zisserman, Basura Fernando, Tinne Tuytelaars, Dan Oneata, Matthijs Douze, Jérôme Revaud, Jochen Schwenninger, Danila Potapov, Heng Wang, Zaïd Harchaoui, Jakob Verbeek, Cordelia Schmid
2012	A*	`conf`	Large-scale image classification with trace-norm regularization. CVPR Zaïd Harchaoui, Matthijs Douze, Mattis Paulin, Miroslav Dudík, Jérôme Malick
2012	A	`conf`	Lifted coordinate descent for learning with trace-norm regularization. AISTATS Miroslav Dudík, Zaïd Harchaoui, Jérôme Malick
2012	A	`conf`	Recognizing activities with cluster-trees of tracklets. BMVC Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid
2012	A*	`conf`	Towards good practice in large-scale learning for image classification. CVPR Florent Perronnin, Zeynep Akata, Zaïd Harchaoui, Cordelia Schmid
2011	A	`conf`	A time series kernel for action recognition. BMVC Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid
2011	A*	`conf`	Actom sequence models for efficient action detection. CVPR Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid
2009	—	`conf`	A Fast, Consistent Kernel Two-Sample Test. NIPS Arthur Gretton, Kenji Fukumizu, Zaïd Harchaoui, Bharath K. Sriperumbudur
2009	Misc	`conf`	A regularized kernel-based approach to unsupervised audio segmentation. ICASSP Zaïd Harchaoui, Félicien Vallet, Alexandre Lung-Yut-Fong, Olivier Cappé
2008	—	`conf`	Kernel Change-point Analysis. NIPS Zaïd Harchaoui, Francis R. Bach, Eric Moulines
2007	—	`conf`	Catching Change-points with Lasso. NIPS Zaïd Harchaoui, Céline Lévy-Leduc
2007	—	`conf`	DIFFRAC: a discriminative and flexible framework for clustering. NIPS Francis R. Bach, Zaïd Harchaoui
2007	A*	`conf`	Image Classification with Segmentation Graph Kernels. CVPR Zaïd Harchaoui, Francis R. Bach
2007	—	`conf`	Testing for Homogeneity with Kernel Fisher Discriminant Analysis. NIPS Zaïd Harchaoui, Francis R. Bach, Eric Moulines
2004	—	`conf`	A Machine Learning Approach to Conjoint Analysis. NIPS Olivier Chapelle, Zaïd Harchaoui