Zaïd Harchaoui

ORCID

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 95

Top Venues

Publications

Lang Liu, Zaïd Harchaoui
The Rao, Wald, And Likelihood-Ratio Tests under Generalized Self-Concordance. ICASSP (2024)
Jillian Fisher, Ximing Lu, Jaehun Jung, Liwei Jiang, Zaïd Harchaoui, Yejin Choi
JAMDEC: Unsupervised Authorship Obfuscation using Constrained Decoding over Small Language Models. NAACL-HLT (2024)
Jillian Fisher, Ximing Lu, Jaehun Jung, Liwei Jiang, Zaïd Harchaoui, Yejin Choi
JAMDEC: Unsupervised Authorship Obfuscation using Constrained Decoding over Small Language Models. CoRR (2024)
Ronak Mehta, Jelena Diakonikolas, Zaïd Harchaoui
A Primal-Dual Algorithm for Faster Distributionally Robust Optimization. CoRR (2024)
Sean Welleck, Amanda Bertsch, Matthew Finlayson, Hailey Schoelkopf, Alex Xie, Graham Neubig, Ilia Kulikov, Zaïd Harchaoui
From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models. CoRR (2024)
Krishna Pillutla, Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
Federated learning with superquantile aggregation for heterogeneous data. Mach. Learn. 113 (5) (2024)
Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaïd Harchaoui
Distributionally Robust Optimization with Bias and Variance Reduction. ICLR (2024)
Tianxiao Shen, Hao Peng, Ruoqi Shen, Yao Fu, Zaïd Harchaoui, Yejin Choi
FiLM: Fill-in Language Models for Any-Order Generation. CoRR (2023)
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
Faith and Fate: Limits of Transformers on Compositionality. NeurIPS (2023)
Joshua Cutler, Dmitriy Drusvyatskiy, Zaïd Harchaoui
Stochastic Optimization under Distributional Drift. J. Mach. Learn. Res. 24 (2023)
Vincent Roulet, Zaïd Harchaoui
Target Propagation via Regularized Inversion for Recurrent Neural Networks. Trans. Mach. Learn. Res. 2023 (2023)
Corinne Jones, Vincent Roulet, Zaïd Harchaoui
Revisiting Convolutional Neural Networks from the Viewpoint of Kernel-Based Methods. J. Comput. Graph. Stat. 32 (4) (2023)
Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaïd Harchaoui
Distributionally Robust Optimization with Bias and Variance Reduction. CoRR (2023)
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
Faith and Fate: Limits of Transformers on Compositionality. CoRR (2023)
Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaïd Harchaoui
Modified Gauss-Newton Algorithms under Noise. CoRR (2023)
Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaïd Harchaoui
Modified Gauss-Newton Algorithms under Noise. SSP (2023)
Jillian Fisher, Lang Liu, Krishna Pillutla, Yejin Choi, Zaïd Harchaoui
Influence Diagnostics under Self-concordance. AISTATS (2023)
Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaïd Harchaoui
Stochastic Optimization for Spectral Risk Measures. AISTATS (2023)
Zaïd Harchaoui, Sewoong Oh, Soumik Pal, Raghav Somani, Raghavendra Tripathi
Stochastic optimization on matrices and a graphon McKean-Vlasov limit. CoRR (2022)
Krishna Pillutla, Lang Liu, John Thickstun, Sean Welleck, Swabha Swayamdipta, Rowan Zellers, Sewoong Oh, Yejin Choi, Zaïd Harchaoui
MAUVE Scores for Generative Models: Theory and Practice. CoRR (2022)
Corinne Jones, Vincent Roulet, Zaïd Harchaoui
Discriminative clustering with representation learning with any ratio of labeled to unlabeled data. Stat. Comput. 32 (1) (2022)
Lang Liu, Carlos Cinelli, Zaïd Harchaoui
Orthogonal Statistical Learning with Self-Concordant Loss. CoRR (2022)
Jann Paul Mattern, Kristof Glauninger, Gregory L. Britten, John R. Casey, Sangwon Hyun, Zhen Wu, E. Virginia Armbrust, Zaïd Harchaoui, Francois Ribalet
A Bayesian approach to modeling phytoplankton population dynamics from size distribution time series. PLoS Comput. Biol. 18 (1) (2022)
Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
Superquantile-Based Learning: A Direct Approach Using Gradient-Based Optimization. J. Signal Process. Syst. 94 (2) (2022)
Lang Liu, Soumik Pal, Zaïd Harchaoui
Entropy Regularized Optimal Transport Independence Criterion. AISTATS (2022)
Lang Liu, Carlos Cinelli, Zaïd Harchaoui
Orthogonal Statistical Learning with Self-Concordant Loss. COLT (2022)
Jillian Fisher, Lang Liu, Krishna Pillutla, Yejin Choi, Zaïd Harchaoui
Statistical and Computational Guarantees for Influence Diagnostics. CoRR (2022)
Vincent Roulet, Siddhartha S. Srinivasa, Maryam Fazel, Zaïd Harchaoui
Iterative Linear Quadratic Optimization for Nonlinear Control: Differentiable Programming Algorithmic Templates. CoRR (2022)
Vincent Roulet, Zaïd Harchaoui
Differentiable Programming A La Moreau. ICASSP (2022)
Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaïd Harchaoui
Stochastic Optimization for Spectral Risk Measures. CoRR (2022)
Krishna Pillutla, Sham M. Kakade, Zaïd Harchaoui
Robust Aggregation for Federated Learning. IEEE Trans. Signal Process. 70 (2022)
Nicholas J. Irons, Meyer Scetbon, Soumik Pal, Zaïd Harchaoui
Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates. AISTATS (2022)
Lang Liu, Joseph Salmon, Zaïd Harchaoui
Score-Based Change Detection For Gradient-Based Learning Machines. ICASSP (2021)
Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Sean Welleck, Yejin Choi, Zaïd Harchaoui
MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers. NeurIPS (2021)
Meyer Scetbon, Zaïd Harchaoui
A Spectral Analysis of Dot-product Kernels. AISTATS (2021)
Vincent Roulet, Zaïd Harchaoui
On the Smoothing of Deep Networks. CISS (2021)
Yassine Laguel, Krishna Pillutla, Jérôme Malick, Zaïd Harchaoui
A Superquantile Approach to Federated Learning with Heterogeneous Devices. CISS (2021)
Lang Liu, Joseph Salmon, Zaïd Harchaoui
Score-Based Change Detection for Gradient-Based Learning Machines. CoRR (2021)
Joshua Cutler, Dmitriy Drusvyatskiy, Zaïd Harchaoui
Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees. NeurIPS (2021)
Samuel K. Ainsworth, Kendall Lowrey, John Thickstun, Zaïd Harchaoui, Siddhartha S. Srinivasa
Faster Policy Learning with Continuous-Time Gradients. L4DC (2021)
Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaïd Harchaoui
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals. NeurIPS (2021)
Nicholas J. Irons, Meyer Scetbon, Soumik Pal, Zaïd Harchaoui
Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates. CoRR (2021)
Krishna Pillutla, Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
Federated Learning with Heterogeneous Data: A Superquantile Optimization Approach. CoRR (2021)
Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Yejin Choi, Zaïd Harchaoui
MAUVE: Human-Machine Divergence Curves for Evaluating Open-Ended Text Generation. CoRR (2021)
Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaïd Harchaoui
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral. CoRR (2021)
Joshua Cutler, Dmitriy Drusvyatskiy, Zaïd Harchaoui
Stochastic optimization under time drift: iterate averaging, step decay, and high probability guarantees. CoRR (2021)
Vincent Roulet, Zaïd Harchaoui
Target Propagation via Regularized Inversion. CoRR (2021)
Lang Liu, Soumik Pal, Zaïd Harchaoui
Entropy Regularized Optimal Transport Independence Criterion. CoRR (2021)
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
Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 14 (1-2) (2021)
Vincent Roulet, Zaïd Harchaoui
An Elementary Approach to Convergence Guarantees of Optimization Algorithms for Deep Networks. CoRR (2020)
Vincent Roulet, Zaïd Harchaoui
Differentiable Programming à la Moreau. CoRR (2020)
Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
First-Order Optimization for Superquantile-Based Supervised Learning. MLSP (2020)
Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
First-order Optimization for Superquantile-based Supervised Learning. CoRR (2020)
Samuel K. Ainsworth, Kendall Lowrey, John Thickstun, Zaïd Harchaoui, Siddhartha S. Srinivasa
Faster Policy Learning with Continuous-Time Gradients. CoRR (2020)
Corinne Jones, Zaïd Harchaoui
End-to-End Learning for Retrospective Change-Point Estimation. MLSP (2020)
Meyer Scetbon, Zaïd Harchaoui
Harmonic Decompositions of Convolutional Networks. ICML (2020)
Meyer Scetbon, Zaïd Harchaoui
Harmonic Decompositions of Convolutional Networks. CoRR (2020)
Vincent Roulet, Maryam Fazel, Siddhartha S. Srinivasa, Zaïd Harchaoui
On the Convergence of the Iterative Linear Exponential Quadratic Gaussian Algorithm to Stationary Points. ACC (2020)
Yassine Laguel, Krishna Pillutla, Jérôme Malick, Zaïd Harchaoui
Device Heterogeneity in Federated Learning: A Superquantile Approach. CoRR (2020)
Meyer Scetbon, Zaïd Harchaoui
Risk Bounds for Multi-layer Perceptrons through Spectra of Integral Operators. CoRR (2020)
Alexander Greaves-Tunnell, Zaïd Harchaoui
A Statistical Investigation of Long Memory in Language and Music. CoRR (2019)
Corinne Jones, Vincent Roulet, Zaïd Harchaoui
Kernel-based Translations of Convolutional Networks. CoRR (2019)
Venkata Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaïd Harchaoui
A Smoother Way to Train Structured Prediction Models. CoRR (2019)
John Thickstun, Zaïd Harchaoui, Dean P. Foster, Sham M. Kakade
Coupled Recurrent Models for Polyphonic Music Composition. ISMIR (2019)
Vincent Roulet, Zaïd Harchaoui
An Elementary Approach to Convergence Guarantees of Optimization Algorithms for Deep Networks. Allerton (2019)
Alexander Greaves-Tunnell, Zaïd Harchaoui
A Statistical Investigation of Long Memory in Language and Music. ICML (2019)
Venkata Krishna Pillutla, Sham M. Kakade, Zaïd Harchaoui
Robust Aggregation for Federated Learning. CoRR (2019)
Vincent Roulet, Dmitriy Drusvyatskiy, Siddhartha S. Srinivasa, Zaïd Harchaoui
Iterative Linearized Control: Stable Algorithms and Complexity Guarantees. ICML (2019)
Hongzhou Lin, Julien Mairal, Zaïd Harchaoui
An Inexact Variable Metric Proximal Point Algorithm for Generic Quasi-Newton Acceleration. SIAM J. Optim. 29 (2) (2019)
Sylvain Arlot, Alain Celisse, Zaïd Harchaoui
A Kernel Multiple Change-point Algorithm via Model Selection. J. Mach. Learn. Res. 20 (2019)
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
Advances and Open Problems in Federated Learning. CoRR (2019)
Corinne Jones, Vincent Roulet, Zaïd Harchaoui
End-to-end Learning, with or without Labels. CoRR (2019)
Christopher Xie, Yu Xiang, Zaïd Harchaoui, Dieter Fox
Object Discovery in Videos as Foreground Motion Clustering. CVPR (2019)
Christopher Xie, Emily B. Fox, Zaïd Harchaoui
A Simple Adaptive Tracker with Reminiscences. ICRA (2019)
Dmitrii Ostrovskii, Zaïd Harchaoui
Efficient First-Order Algorithms for Adaptive Signal Denoising. ICML (2018)
John Thickstun, Zaïd Harchaoui, Dean P. Foster, Sham M. Kakade
Coupled Recurrent Models for Polyphonic Music Composition. CoRR (2018)
John Thickstun, Zaïd Harchaoui, Dean P. Foster, Sham M. Kakade
Invariances and Data Augmentation for Supervised Music Transcription. ICASSP (2018)
Venkata Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaïd Harchaoui
A Smoother Way to Train Structured Prediction Models. NeurIPS (2018)
Yury Maximov, Massih-Reza Amini, Zaïd Harchaoui
Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm (Extended Abstract). IJCAI (2018)
Yury Maximov, Massih-Reza Amini, Zaïd Harchaoui
Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm. J. Artif. Intell. Res. 61 (2018)
Courtney Paquette, Hongzhou Lin, Dmitriy Drusvyatskiy, Julien Mairal, Zaïd Harchaoui
Catalyst for Gradient-based Nonconvex Optimization. AISTATS (2018)
Christopher Xie, Yu Xiang, Dieter Fox, Zaïd Harchaoui
Object Discovery in Videos as Foreground Motion Clustering. CoRR (2018)
John Thickstun, Zaïd Harchaoui, Sham M. Kakade
Learning Features of Music From Scratch. ICLR (Poster) (2017)
John Thickstun, Zaïd Harchaoui, Dean P. Foster, Sham M. Kakade
Invariances and Data Augmentation for Supervised Music Transcription. CoRR (2017)
Hongzhou Lin, Julien Mairal, Zaïd Harchaoui
Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice. J. Mach. Learn. Res. 18 (2017)
Mattis Paulin, Julien Mairal, Matthijs Douze, Zaïd Harchaoui, Florent Perronnin, Cordelia Schmid
Convolutional Patch Representations for Image Retrieval: An Unsupervised Approach. Int. J. Comput. Vis. 121 (1) (2017)
Nikhil Rao, Miroslav Dudík, Zaïd Harchaoui
The group k-support norm for learning with structured sparsity. ICASSP (2017)
Danila Potapov, Matthijs Douze, Jérôme Revaud, Zaïd Harchaoui, Cordelia Schmid
Inferring the Structure of Action Movies. WICED@Eurographics (2017)
Niao He, Zaïd Harchaoui, Yichen Wang, Le Song
Fast and Simple Optimization for Poisson Likelihood Models. CoRR (2016)
Mattis Paulin, Julien Mairal, Matthijs Douze, Zaïd Harchaoui, Florent Perronnin, Cordelia Schmid
Convolutional Patch Representations for Image Retrieval: an Unsupervised Approach. CoRR (2016)
Zeynep Akata, Florent Perronnin, Zaïd Harchaoui, Cordelia Schmid
Label-Embedding for Image Classification. IEEE Trans. Pattern Anal. Mach. Intell. 38 (7) (2016)
Yury Maximov, Massih-Reza Amini, Zaïd Harchaoui
Rademacher Complexity Bounds for a Penalized Multiclass Semi-Supervised Algorithm. CoRR (2016)
John Thickstun, Zaïd Harchaoui, Sham M. Kakade
Learning Features of Music from Scratch. CoRR (2016)
Jérôme Revaud, Philippe Weinzaepfel, Zaïd Harchaoui, Cordelia Schmid
DeepMatching: Hierarchical Deformable Dense Matching. Int. J. Comput. Vis. 120 (3) (2016)
Dmitry Ostrovsky, Zaïd Harchaoui, Anatoli B. Juditsky, Arkadi Nemirovski
Structure-Blind Signal Recovery. NIPS (2016)
Danila Potapov, Matthijs Douze, Jérôme Revaud, Zaïd Harchaoui, Cordelia Schmid
Beat-Event Detection in Action Movie Franchises. CoRR (2015)
Mattis Paulin, Matthijs Douze, Zaïd Harchaoui, Julien Mairal, Florent Perronnin, Cordelia Schmid
Local Convolutional Features with Unsupervised Training for Image Retrieval. ICCV (2015)
Philippe Weinzaepfel, Zaïd Harchaoui, Cordelia Schmid
Learning to Track for Spatio-Temporal Action Localization. ICCV (2015)
Hongzhou Lin, Julien Mairal, Zaïd Harchaoui
A Universal Catalyst for First-Order Optimization. NIPS (2015)
Zaïd Harchaoui, Anatoli B. Juditsky, Arkadi Nemirovski
Conditional gradient algorithms for norm-regularized smooth convex optimization. Math. Program. 152 (1-2) (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Zaïd Harchaoui