Harchaoui, Zaid

63 publications

ICML 2025 A Generalization Theory for Zero-Shot Prediction Ronak Mehta, Zaid Harchaoui

JMLR 2025 On Global and Local Convergence of Iterative Linear Quadratic Optimization Algorithms for Discrete Time Nonlinear Control Vincent Roulet, Siddhartha Srinivasa, Maryam Fazel, Zaid Harchaoui

AISTATS 2025 Spectral Differential Network Analysis for High-Dimensional Time Series Michael Hellstern, Byol Kim, Zaid Harchaoui, Ali Shojaie

NeurIPS 2025 Stochastic Gradients Under Nuisances Facheng Yu, Ronak Mehta, Alex Luedtke, Zaid Harchaoui

ICLR 2024 Distributionally Robust Optimization with Bias and Variance Reduction Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaid Harchaoui

NeurIPS 2024 Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization Ronak Mehta, Jelena Diakonikolas, Zaid Harchaoui

MLJ 2024 Federated Learning with Superquantile Aggregation for Heterogeneous Data Krishna Pillutla, Yassine Laguel, Jérôme Malick, Zaïd Harchaoui

TMLR 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, Zaid Harchaoui

NeurIPS 2024 The Benefits of Balance: From Information Projections to Variance Reduction Lang Liu, Ronak Mehta, Soumik Pal, Zaid Harchaoui

NeurIPS 2023 Faith and Fate: Limits of Transformers on Compositionality Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Li, Liwei Jiang, Bill Yuchen Lin, Sean Welleck, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena Hwang, Soumya Sanyal, Xiang Ren, Allyson Ettinger, Zaid Harchaoui, Yejin Choi

AISTATS 2023 Influence Diagnostics Under Self-Concordance Jillian Fisher, Lang Liu, Krishna Pillutla, Yejin Choi, Zaid Harchaoui

JMLR 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, Zaid Harchaoui

JMLR 2023 Stochastic Optimization Under Distributional Drift Joshua Cutler, Dmitriy Drusvyatskiy, Zaid Harchaoui

AISTATS 2023 Stochastic Optimization for Spectral Risk Measures Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaid Harchaoui

TMLR 2023 Target Propagation via Regularized Inversion for Recurrent Neural Networks Vincent Roulet, Zaid Harchaoui

AISTATS 2022 Entropy Regularized Optimal Transport Independence Criterion Lang Liu, Soumik Pal, Zaid Harchaoui

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

NeurIPSW 2022 Differentially Private Federated Quantiles with the Distributed Discrete Gaussian Mechanism Krishna Pillutla, Yassine Laguel, Jérôme Malick, Zaid Harchaoui

NeurIPSW 2022 Likelihood Score Under Generalized Self-Concordance Lang Liu, Zaid Harchaoui

COLT 2022 Orthogonal Statistical Learning with Self-Concordant Loss Lang Liu, Carlos Cinelli, Zaid Harchaoui

NeurIPSW 2022 Tackling Distribution Shifts in Federated Learning with Superquantile Aggregation Krishna Pillutla, Yassine Laguel, Jerome Malick, Zaid Harchaoui

AISTATS 2021 A Spectral Analysis of Dot-Product Kernels Meyer Scetbon, Zaid Harchaoui

FnTML 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, 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

NeurIPS 2021 Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaid Harchaoui

L4DC 2021 Faster Policy Learning with Continuous-Time Gradients Samuel Ainsworth, Kendall Lowrey, John Thickstun, Zaid Harchaoui, Siddhartha Srinivasa

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, Zaid Harchaoui

NeurIPS 2021 Stochastic Optimization Under Time Drift: Iterate Averaging, Step-Decay Schedules, and High Probability Guarantees Joshua Cutler, Dmitriy Drusvyatskiy, Zaid Harchaoui

ICML 2020 Harmonic Decompositions of Convolutional Networks Meyer Scetbon, Zaid Harchaoui

JMLR 2019 A Kernel Multiple Change-Point Algorithm via Model Selection Sylvain Arlot, Alain Celisse, Zaid Harchaoui

ICML 2019 A Statistical Investigation of Long Memory in Language and Music Alexander Greaves-Tunnell, Zaid Harchaoui

ICML 2019 Iterative Linearized Control: Stable Algorithms and Complexity Guarantees Vincent Roulet, Siddhartha Srinivasa, Dmitriy Drusvyatskiy, Zaid Harchaoui

NeurIPS 2018 A Smoother Way to Train Structured Prediction Models Venkata Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaid Harchaoui

AISTATS 2018 Catalyst for Gradient-Based Nonconvex Optimization Courtney Paquette, Hongzhou Lin, Dmitriy Drusvyatskiy, Julien Mairal, Zaïd Harchaoui

ICML 2018 Efficient First-Order Algorithms for Adaptive Signal Denoising Dmitrii Ostrovskii, Zaid Harchaoui

JAIR 2018 Rademacher Complexity Bounds for a Penalized Multi-Class Semi-Supervised Algorithm Yury Maximov, Massih-Reza Amini, Zaïd Harchaoui

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

ICLR 2017 Learning Features of Music from Scratch John Thickstun, Zaïd Harchaoui, Sham M. Kakade

NeurIPS 2016 Structure-Blind Signal Recovery Dmitry Ostrovsky, Zaid Harchaoui, Anatoli Juditsky, Arkadi S. Nemirovski

NeurIPS 2015 A Universal Catalyst for First-Order Optimization Hongzhou Lin, Julien Mairal, Zaid Harchaoui

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

CVPR 2015 EpicFlow: Edge-Preserving Interpolation of Correspondences for Optical Flow Jerome Revaud, Philippe Weinzaepfel, Zaid Harchaoui, Cordelia Schmid

CVPR 2015 Learning to Detect Motion Boundaries Philippe Weinzaepfel, Jerome Revaud, Zaid Harchaoui, Cordelia Schmid

ICCV 2015 Learning to Track for Spatio-Temporal Action Localization Philippe Weinzaepfel, Zaid Harchaoui, Cordelia Schmid

ICCV 2015 Local Convolutional Features with Unsupervised Training for Image Retrieval Mattis Paulin, Matthijs Douze, Zaid Harchaoui, Julien Mairal, Florent Perronin, Cordelia Schmid

NeurIPS 2015 Semi-Proximal Mirror-Prox for Nonsmooth Composite Minimization Niao He, Zaid Harchaoui

ECCV 2014 Category-Specific Video Summarization Danila Potapov, Matthijs Douze, Zaïd Harchaoui, Cordelia Schmid

NeurIPS 2014 Convolutional Kernel Networks Julien Mairal, Piotr Koniusz, Zaid Harchaoui, Cordelia Schmid

CVPR 2014 Fast and Robust Archetypal Analysis for Representation Learning Yuansi Chen, Julien Mairal, Zaid Harchaoui

ICML 2014 On Learning to Localize Objects with Minimal Supervision Hyun Oh Song, Ross Girshick, Stefanie Jegelka, Julien Mairal, Zaid Harchaoui, Trevor Darrell

CVPR 2014 Transformation Pursuit for Image Classification Mattis Paulin, Jerome Revaud, Zaid Harchaoui, Florent Perronnin, Cordelia Schmid

ICCV 2013 DeepFlow: Large Displacement Optical Flow with Deep Matching Philippe Weinzaepfel, Jerome Revaud, Zaid Harchaoui, Cordelia Schmid

CVPR 2013 Label-Embedding for Attribute-Based Classification Zeynep Akata, Florent Perronnin, Zaid Harchaoui, Cordelia Schmid

CVPR 2012 Large-Scale Image Classification with Trace-Norm Regularization Zaïd Harchaoui, Matthijs Douze, Mattis Paulin, Miroslav Dudík, Jérôme Malick

AISTATS 2012 Lifted Coordinate Descent for Learning with Trace-Norm Regularization Miroslav Dudik, Zaid Harchaoui, Jerome Malick

CVPR 2012 Towards Good Practice in Large-Scale Learning for Image Classification Florent Perronnin, Zeynep Akata, Zaïd Harchaoui, Cordelia Schmid

CVPR 2011 Actom Sequence Models for Efficient Action Detection Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid

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

NeurIPS 2008 Kernel Change-Point Analysis Zaïd Harchaoui, Eric Moulines, Francis R. Bach

NeurIPS 2007 Catching Change-Points with Lasso Céline Levy-leduc, Zaïd Harchaoui

NeurIPS 2007 DIFFRAC: A Discriminative and Flexible Framework for Clustering Francis R. Bach, Zaïd Harchaoui

CVPR 2007 Image Classification with Segmentation Graph Kernels Zaïd Harchaoui, Francis R. Bach

NeurIPS 2007 Testing for Homogeneity with Kernel Fisher Discriminant Analysis Moulines Eric, Francis R. Bach, Zaïd Harchaoui

NeurIPS 2004 A Machine Learning Approach to Conjoint Analysis Olivier Chapelle, Zaïd Harchaoui