A Machine Learning Approach to Conjoint Analysis. - Olivier Chapelle; Zaïd Harchaoui (NIPS, 2004)

Image Classification with Segmentation Graph Kernels. - Zaïd Harchaoui; Francis R. Bach (CVPR, 2007)

DIFFRAC: a discriminative and flexible framework for clustering. - Francis R. Bach; Zaïd Harchaoui (NIPS, 2007)

Testing for Homogeneity with Kernel Fisher Discriminant Analysis. - Zaïd Harchaoui; Francis R. Bach; Eric Moulines (NIPS, 2007)

Catching Change-points with Lasso. - Zaïd Harchaoui; Céline Lévy-Leduc (NIPS, 2007)

Kernel Change-point Analysis. - Zaïd Harchaoui; Francis R. Bach; Eric Moulines (NIPS, 2008)

A regularized kernel-based approach to unsupervised audio segmentation. - Zaïd Harchaoui; Félicien Vallet; Alexandre Lung-Yut-Fong; Olivier Cappé (ICASSP, 2009)

A Fast, Consistent Kernel Two-Sample Test. - Arthur Gretton; Kenji Fukumizu; Zaïd Harchaoui; Bharath K. Sriperumbudur (NIPS, 2009)

A time series kernel for action recognition. - Adrien Gaidon; Zaïd Harchaoui; Cordelia Schmid (BMVC, 2011)

Actom sequence models for efficient action detection. - Adrien Gaidon; Zaïd Harchaoui; Cordelia Schmid (CVPR, 2011)

Recognizing activities with cluster-trees of tracklets. - Adrien Gaidon; Zaïd Harchaoui; Cordelia Schmid (BMVC, 2012)

Large-scale image classification with trace-norm regularization. - Zaïd Harchaoui; Matthijs Douze; Mattis Paulin; Miroslav Dudík; Jérôme Malick (CVPR, 2012)

Towards good practice in large-scale learning for image classification. - Florent Perronnin; Zeynep Akata; Zaïd Harchaoui; Cordelia Schmid (CVPR, 2012)

AXES at TRECVID 2012: KIS, INS, and MED. - 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; et al. (TRECVID, 2012)

Lifted coordinate descent for learning with trace-norm regularization. - Miroslav Dudík; Zaïd Harchaoui; Jérôme Malick (AISTATS, 2012)

Label-Embedding for Attribute-Based Classification. - Zeynep Akata; Florent Perronnin; Zaïd Harchaoui; Cordelia Schmid (CVPR, 2013)

DeepFlow: Large Displacement Optical Flow with Deep Matching. - Philippe Weinzaepfel; Jérôme Revaud; Zaïd Harchaoui; Cordelia Schmid (ICCV, 2013)

The AXES submissions at TRECVID 2013. - 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; et al. (TRECVID, 2013)

Automatic Recognition of Human Activities in Realistic Videos. - Adrien Gaidon; Zaïd Harchaoui; Cordelia Schmid (ERCIM News, 2013)

Temporal Localization of Actions with Actoms. - Adrien Gaidon; Zaïd Harchaoui; Cordelia Schmid (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

Kernel-Based Methods for Hypothesis Testing: A Unified View. - Zaïd Harchaoui; Francis R. Bach; Olivier Cappé; Eric Moulines (IEEE Signal Process. Mag., 2013)

Fast and Robust Archetypal Analysis for Representation Learning. - Yuansi Chen; Julien Mairal; Zaïd Harchaoui (CVPR, 2014)

Transformation Pursuit for Image Classification. - Mattis Paulin; Jérôme Revaud; Zaïd Harchaoui; Florent Perronnin; Cordelia Schmid (CVPR, 2014)

Category-Specific Video Summarization. - Danila Potapov; Matthijs Douze; Zaïd Harchaoui; Cordelia Schmid (ECCV (6), 2014)

On learning to localize objects with minimal supervision. - Hyun Oh Song; Ross B. Girshick; Stefanie Jegelka; Julien Mairal; Zaïd Harchaoui; Trevor Darrell (ICML, 2014)

Convolutional Kernel Networks. - Julien Mairal; Piotr Koniusz; Zaïd Harchaoui; Cordelia Schmid (NIPS, 2014)

The INRIA-LIM-VocR and AXES submissions to TrecVid 2014 Multimedia Event Detection. - 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; et al. (TRECVID, 2014)

One-Bit Object Detection: On learning to localize objects with minimal supervision. - Hyun Oh Song; Ross B. Girshick; Stefanie Jegelka; Julien Mairal; Zaïd Harchaoui; Trevor Darrell (CoRR, 2014)

Activity representation with motion hierarchies. - Adrien Gaidon; Zaïd Harchaoui; Cordelia Schmid (Int. J. Comput. Vis., 2014)

Good Practice in Large-Scale Learning for Image Classification. - Zeynep Akata; Florent Perronnin; Zaïd Harchaoui; Cordelia Schmid (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Adaptive Recovery of Signals by Convex Optimization. - Zaïd Harchaoui; Anatoli B. Juditsky; Arkadi Nemirovski; Dmitry Ostrovsky (COLT, 2015)

EpicFlow: Edge-preserving interpolation of correspondences for optical flow. - Jérôme Revaud; Philippe Weinzaepfel; Zaïd Harchaoui; Cordelia Schmid (CVPR, 2015)

Learning to detect Motion Boundaries. - Philippe Weinzaepfel; Jérôme Revaud; Zaïd Harchaoui; Cordelia Schmid (CVPR, 2015)

Local Convolutional Features with Unsupervised Training for Image Retrieval. - Mattis Paulin; Matthijs Douze; Zaïd Harchaoui; Julien Mairal; Florent Perronnin; Cordelia Schmid (ICCV, 2015)

Learning to Track for Spatio-Temporal Action Localization. - Philippe Weinzaepfel; Zaïd Harchaoui; Cordelia Schmid (ICCV, 2015)

Semi-Proximal Mirror-Prox for Nonsmooth Composite Minimization. - Niao He; Zaïd Harchaoui (NIPS, 2015)

A Universal Catalyst for First-Order Optimization. - Hongzhou Lin; Julien Mairal; Zaïd Harchaoui (NIPS, 2015)

Beat-Event Detection in Action Movie Franchises. - Danila Potapov; Matthijs Douze; Jérôme Revaud; Zaïd Harchaoui; Cordelia Schmid (CoRR, 2015)

Deep Convolutional Matching. - Jérôme Revaud; Philippe Weinzaepfel; Zaïd Harchaoui; Cordelia Schmid (CoRR, 2015)

Conditional gradient algorithms for norm-regularized smooth convex optimization. - Zaïd Harchaoui; Anatoli B. Juditsky; Arkadi Nemirovski (Math. Program., 2015)

Structure-Blind Signal Recovery. - Dmitry Ostrovsky; Zaïd Harchaoui; Anatoli B. Juditsky; Arkadi Nemirovski (NIPS, 2016)

Fast and Simple Optimization for Poisson Likelihood Models. - Niao He; Zaïd Harchaoui; Yichen Wang 001; Le Song (CoRR, 2016)

Rademacher Complexity Bounds for a Penalized Multiclass Semi-Supervised Algorithm. - Yury Maximov; Massih-Reza Amini; Zaïd Harchaoui (CoRR, 2016)

DeepMatching: Hierarchical Deformable Dense Matching. - Jérôme Revaud; Philippe Weinzaepfel; Zaïd Harchaoui; Cordelia Schmid (Int. J. Comput. Vis., 2016)

Label-Embedding for Image Classification. - Zeynep Akata; Florent Perronnin; Zaïd Harchaoui; Cordelia Schmid (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

The group k-support norm for learning with structured sparsity. - Nikhil Rao 001; Miroslav Dudík; Zaïd Harchaoui (ICASSP, 2017)

Learning Features of Music From Scratch. - John Thickstun; Zaïd Harchaoui; Sham M. Kakade (ICLR (Poster), 2017)

Inferring the Structure of Action Movies. - Danila Potapov; Matthijs Douze; Jérôme Revaud; Zaïd Harchaoui; Cordelia Schmid (WICED@Eurographics, 2017)

Convolutional Patch Representations for Image Retrieval: An Unsupervised Approach. - Mattis Paulin; Julien Mairal; Matthijs Douze; Zaïd Harchaoui; Florent Perronnin; Cordelia Schmid (Int. J. Comput. Vis., 2017)

Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice. - Hongzhou Lin; Julien Mairal; Zaïd Harchaoui (J. Mach. Learn. Res., 2017)

Catalyst for Gradient-based Nonconvex Optimization. - Courtney Paquette; Hongzhou Lin; Dmitriy Drusvyatskiy; Julien Mairal; Zaïd Harchaoui (AISTATS, 2018)

Invariances and Data Augmentation for Supervised Music Transcription. - John Thickstun; Zaïd Harchaoui; Dean P. Foster; Sham M. Kakade (ICASSP, 2018)

Efficient First-Order Algorithms for Adaptive Signal Denoising. - Dmitrii Ostrovskii; Zaïd Harchaoui (ICML, 2018)

Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm (Extended Abstract). - Yury Maximov; Massih-Reza Amini; Zaïd Harchaoui (IJCAI, 2018)

A Smoother Way to Train Structured Prediction Models. - Venkata Krishna Pillutla; Vincent Roulet; Sham M. Kakade; Zaïd Harchaoui (NeurIPS, 2018)

Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm. - Yury Maximov; Massih-Reza Amini; Zaïd Harchaoui (J. Artif. Intell. Res., 2018)

An Elementary Approach to Convergence Guarantees of Optimization Algorithms for Deep Networks. - Vincent Roulet; Zaïd Harchaoui (Allerton, 2019)

Object Discovery in Videos as Foreground Motion Clustering. - Christopher Xie; Yu Xiang 001; Zaïd Harchaoui; Dieter Fox (CVPR, 2019)

A Statistical Investigation of Long Memory in Language and Music. - Alexander Greaves-Tunnell; Zaïd Harchaoui (ICML, 2019)

Iterative Linearized Control: Stable Algorithms and Complexity Guarantees. - Vincent Roulet; Dmitriy Drusvyatskiy; Siddhartha S. Srinivasa; Zaïd Harchaoui (ICML, 2019)

A Simple Adaptive Tracker with Reminiscences. - Christopher Xie; Emily B. Fox; Zaïd Harchaoui (ICRA, 2019)

Coupled Recurrent Models for Polyphonic Music Composition. - John Thickstun; Zaïd Harchaoui; Dean P. Foster; Sham M. Kakade (ISMIR, 2019)

Kernel-based Translations of Convolutional Networks. - Corinne Jones; Vincent Roulet; Zaïd Harchaoui (CoRR, 2019)

Advances and Open Problems in Federated Learning. - 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; et al. (CoRR, 2019)

End-to-end Learning, with or without Labels. - Corinne Jones; Vincent Roulet; Zaïd Harchaoui (CoRR, 2019)

Robust Aggregation for Federated Learning. - Venkata Krishna Pillutla; Sham M. Kakade; Zaïd Harchaoui (CoRR, 2019)

A Kernel Multiple Change-point Algorithm via Model Selection. - Sylvain Arlot; Alain Celisse; Zaïd Harchaoui (J. Mach. Learn. Res., 2019)

An Inexact Variable Metric Proximal Point Algorithm for Generic Quasi-Newton Acceleration. - Hongzhou Lin; Julien Mairal; Zaïd Harchaoui (SIAM J. Optim., 2019)

On the Convergence of the Iterative Linear Exponential Quadratic Gaussian Algorithm to Stationary Points. - Vincent Roulet; Maryam Fazel; Siddhartha S. Srinivasa; Zaïd Harchaoui (ACC, 2020)

Harmonic Decompositions of Convolutional Networks. - Meyer Scetbon; Zaïd Harchaoui (ICML, 2020)

End-to-End Learning for Retrospective Change-Point Estimation. - Corinne Jones; Zaïd Harchaoui (MLSP, 2020)

First-Order Optimization for Superquantile-Based Supervised Learning. - Yassine Laguel; Jérôme Malick; Zaïd Harchaoui (MLSP, 2020)

Device Heterogeneity in Federated Learning: A Superquantile Approach. - Yassine Laguel; Krishna Pillutla; Jérôme Malick; Zaïd Harchaoui (CoRR, 2020)

Risk Bounds for Multi-layer Perceptrons through Spectra of Integral Operators. - Meyer Scetbon; Zaïd Harchaoui (CoRR, 2020)

A Spectral Analysis of Dot-product Kernels. - Meyer Scetbon; Zaïd Harchaoui (AISTATS, 2021)

A Superquantile Approach to Federated Learning with Heterogeneous Devices. - Yassine Laguel; Krishna Pillutla; Jérôme Malick; Zaïd Harchaoui (CISS, 2021)

On the Smoothing of Deep Networks. - Vincent Roulet; Zaïd Harchaoui (CISS, 2021)

Score-Based Change Detection For Gradient-Based Learning Machines. - Lang Liu; Joseph Salmon; Zaïd Harchaoui (ICASSP, 2021)

Faster Policy Learning with Continuous-Time Gradients. - Samuel K. Ainsworth; Kendall Lowrey; John Thickstun; Zaïd Harchaoui; Siddhartha S. Srinivasa (L4DC, 2021)

Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees. - Joshua Cutler; Dmitriy Drusvyatskiy; Zaïd Harchaoui (NeurIPS, 2021)

Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals. - Lang Liu; Krishna Pillutla; Sean Welleck; Sewoong Oh; Yejin Choi 001; Zaïd Harchaoui (NeurIPS, 2021)

MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers. - Krishna Pillutla; Swabha Swayamdipta; Rowan Zellers; John Thickstun; Sean Welleck; Yejin Choi 001; Zaïd Harchaoui (NeurIPS, 2021)

MAUVE: Human-Machine Divergence Curves for Evaluating Open-Ended Text Generation. - Krishna Pillutla; Swabha Swayamdipta; Rowan Zellers; John Thickstun; Yejin Choi 001; Zaïd Harchaoui (CoRR, 2021)

Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral. - Lang Liu; Krishna Pillutla; Sean Welleck; Sewoong Oh; Yejin Choi 001; Zaïd Harchaoui (CoRR, 2021)

Stochastic optimization under time drift: iterate averaging, step decay, and high probability guarantees. - Joshua Cutler; Dmitriy Drusvyatskiy; Zaïd Harchaoui (CoRR, 2021)

Target Propagation via Regularized Inversion. - Vincent Roulet; Zaïd Harchaoui (CoRR, 2021)

Federated Learning with Heterogeneous Data: A Superquantile Optimization Approach. - Krishna Pillutla; Yassine Laguel; Jérôme Malick; Zaïd Harchaoui (CoRR, 2021)

Advances and Open Problems in Federated Learning. - 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; et al. (Found. Trends Mach. Learn., 2021)

Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates. - Nicholas J. Irons; Meyer Scetbon; Soumik Pal; Zaïd Harchaoui (AISTATS, 2022)

Entropy Regularized Optimal Transport Independence Criterion. - Lang Liu; Soumik Pal; Zaïd Harchaoui (AISTATS, 2022)

Orthogonal Statistical Learning with Self-Concordant Loss. - Lang Liu; Carlos Cinelli; Zaïd Harchaoui (COLT, 2022)

Differentiable Programming A La Moreau. - Vincent Roulet; Zaïd Harchaoui (ICASSP, 2022)

Iterative Linear Quadratic Optimization for Nonlinear Control: Differentiable Programming Algorithmic Templates. - Vincent Roulet; Siddhartha S. Srinivasa; Maryam Fazel; Zaïd Harchaoui (CoRR, 2022)

Stochastic optimization on matrices and a graphon McKean-Vlasov limit. - Zaïd Harchaoui; Sewoong Oh; Soumik Pal; Raghav Somani; Raghavendra Tripathi (CoRR, 2022)

Statistical and Computational Guarantees for Influence Diagnostics. - Jillian Fisher; Lang Liu; Krishna Pillutla; Yejin Choi 001; Zaïd Harchaoui (CoRR, 2022)

A Bayesian approach to modeling phytoplankton population dynamics from size distribution time series. - Jann Paul Mattern; Kristof Glauninger; Gregory L. Britten; John R. Casey; Sangwon Hyun; Zhen Wu; E. Virginia Armbrust; Zaïd Harchaoui; Francois Ribalet (PLoS Comput. Biol., 2022)

Discriminative clustering with representation learning with any ratio of labeled to unlabeled data. - Corinne Jones; Vincent Roulet; Zaïd Harchaoui (Stat. Comput., 2022)

Robust Aggregation for Federated Learning. - Krishna Pillutla; Sham M. Kakade; Zaïd Harchaoui (IEEE Trans. Signal Process., 2022)

Superquantile-Based Learning: A Direct Approach Using Gradient-Based Optimization. - Yassine Laguel; Jérôme Malick; Zaïd Harchaoui (J. Signal Process. Syst., 2022)

Influence Diagnostics under Self-concordance. - Jillian Fisher; Lang Liu; Krishna Pillutla; Yejin Choi 001; Zaïd Harchaoui (AISTATS, 2023)

Stochastic Optimization for Spectral Risk Measures. - Ronak Mehta; Vincent Roulet; Krishna Pillutla; Lang Liu; Zaïd Harchaoui (AISTATS, 2023)

Faith and Fate: Limits of Transformers on Compositionality. - Nouha Dziri; Ximing Lu; Melanie Sclar; Xiang Lorraine Li; Liwei Jiang; Bill Yuchen Lin; Sean Welleck; Peter West; Chandra Bhagavatula; Ronan Le Bras 001; Jena D. Hwang; Soumya Sanyal 001; et al. (NeurIPS, 2023)

Modified Gauss-Newton Algorithms under Noise. - Krishna Pillutla; Vincent Roulet; Sham M. Kakade; Zaïd Harchaoui (SSP, 2023)

FiLM: Fill-in Language Models for Any-Order Generation. - Tianxiao Shen; Hao Peng 009; Ruoqi Shen; Yao Fu; Zaïd Harchaoui; Yejin Choi 001 (CoRR, 2023)

Revisiting Convolutional Neural Networks from the Viewpoint of Kernel-Based Methods. - Corinne Jones; Vincent Roulet; Zaïd Harchaoui (J. Comput. Graph. Stat., 2023)

Stochastic Optimization under Distributional Drift. - Joshua Cutler; Dmitriy Drusvyatskiy; Zaïd Harchaoui (J. Mach. Learn. Res., 2023)

MAUVE Scores for Generative Models: Theory and Practice. - Krishna Pillutla; Lang Liu; John Thickstun; Sean Welleck; Swabha Swayamdipta; Rowan Zellers; Sewoong Oh; Yejin Choi 001; Zaïd Harchaoui (J. Mach. Learn. Res., 2023)

Target Propagation via Regularized Inversion for Recurrent Neural Networks. - Vincent Roulet; Zaïd Harchaoui (Trans. Mach. Learn. Res., 2023)

The Rao, Wald, And Likelihood-Ratio Tests under Generalized Self-Concordance. - Lang Liu; Zaïd Harchaoui (ICASSP, 2024)

Distributionally Robust Optimization with Bias and Variance Reduction. - Ronak Mehta; Vincent Roulet; Krishna Pillutla; Zaïd Harchaoui (ICLR, 2024)

JAMDEC: Unsupervised Authorship Obfuscation using Constrained Decoding over Small Language Models. - Jillian Fisher; Ximing Lu; Jaehun Jung; Liwei Jiang; Zaïd Harchaoui; Yejin Choi 001 (NAACL-HLT, 2024)

A Primal-Dual Algorithm for Faster Distributionally Robust Optimization. - Ronak Mehta; Jelena Diakonikolas; Zaïd Harchaoui (CoRR, 2024)

From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models. - Sean Welleck; Amanda Bertsch; Matthew Finlayson; Hailey Schoelkopf; Alex Xie; Graham Neubig; Ilia Kulikov; Zaïd Harchaoui (CoRR, 2024)

The Benefits of Balance: From Information Projections to Variance Reduction. - Lang Liu; Ronak Mehta; Soumik Pal; Zaïd Harchaoui (CoRR, 2024)

StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style Elements. - Jillian Fisher; Skyler Hallinan; Ximing Lu; Mitchell L. Gordon; Zaïd Harchaoui; Yejin Choi 001 (CoRR, 2024)

Federated learning with superquantile aggregation for heterogeneous data. - Krishna Pillutla; Yassine Laguel; Jérôme Malick; Zaïd Harchaoui (Mach. Learn., 2024)