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2020 – today
- 2024
[j23]Krishna Pillutla
, Yassine Laguel, Jérôme Malick, Zaïd Harchaoui:
Federated learning with superquantile aggregation for heterogeneous data. Mach. Learn. 113(5): 2955-3022 (2024)- [j22]Vincent Roulet, Siddhartha S. Srinivasa, Maryam Fazel, Zaïd Harchaoui:
Iterative Linear Quadratic Optimization for Nonlinear Control: Differentiable Programming Algorithmic Templates. Open J. Math. Optim. 5: 1-63 (2024) - [c72]Jillian Fisher, Skyler Hallinan, Ximing Lu, Mitchell L. Gordon, Zaïd Harchaoui, Yejin Choi:
StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style Elements. EMNLP 2024: 4172-4206 - [c71]Lang Liu, Zaïd Harchaoui:
The Rao, Wald, And Likelihood-Ratio Tests under Generalized Self-Concordance. ICASSP 2024: 9776-9780 - [c70]Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaïd Harchaoui:
Distributionally Robust Optimization with Bias and Variance Reduction. ICLR 2024 - [c69]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: 1552-1581 - [c68]Lang Liu, Ronak Mehta, Soumik Pal, Zaïd Harchaoui:
The Benefits of Balance: From Information Projections to Variance Reduction. NeurIPS 2024 - [c67]Ronak Mehta, Jelena Diakonikolas, Zaïd Harchaoui:
Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization. NeurIPS 2024 - [i53]Jillian Fisher, Ximing Lu, Jaehun Jung, Liwei Jiang, Zaïd Harchaoui, Yejin Choi:
JAMDEC: Unsupervised Authorship Obfuscation using Constrained Decoding over Small Language Models. CoRR abs/2402.08761 (2024) - [i52]Ronak Mehta, Jelena Diakonikolas, Zaïd Harchaoui:
A Primal-Dual Algorithm for Faster Distributionally Robust Optimization. CoRR abs/2403.10763 (2024) - [i51]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 abs/2406.16838 (2024) - [i50]Lang Liu, Ronak Mehta, Soumik Pal, Zaïd Harchaoui:
The Benefits of Balance: From Information Projections to Variance Reduction. CoRR abs/2408.15065 (2024) - [i49]Jillian Fisher, Skyler Hallinan, Ximing Lu, Mitchell L. Gordon, Zaïd Harchaoui, Yejin Choi:
StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style Elements. CoRR abs/2408.15666 (2024) - 2023
- [j21]Corinne Jones, Vincent Roulet, Zaïd Harchaoui:
Revisiting Convolutional Neural Networks from the Viewpoint of Kernel-Based Methods. J. Comput. Graph. Stat. 32(4): 1237-1247 (2023) - [j20]Joshua Cutler, Dmitriy Drusvyatskiy, Zaïd Harchaoui:
Stochastic Optimization under Distributional Drift. J. Mach. Learn. Res. 24: 147:1-147:56 (2023) - [j19]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. J. Mach. Learn. Res. 24: 356:1-356:92 (2023) - [j18]Vincent Roulet, Zaïd Harchaoui:
Target Propagation via Regularized Inversion for Recurrent Neural Networks. Trans. Mach. Learn. Res. 2023 (2023) - [c66]Jillian Fisher, Lang Liu, Krishna Pillutla, Yejin Choi, Zaïd Harchaoui:
Influence Diagnostics under Self-concordance. AISTATS 2023: 10028-10076 - [c65]Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaïd Harchaoui:
Stochastic Optimization for Spectral Risk Measures. AISTATS 2023: 10112-10159 - [c64]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 - [c63]Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaïd Harchaoui:
Modified Gauss-Newton Algorithms under Noise. SSP 2023: 51-55 - [i48]Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaïd Harchaoui:
Modified Gauss-Newton Algorithms under Noise. CoRR abs/2305.10634 (2023) - [i47]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 abs/2305.18654 (2023) - [i46]Tianxiao Shen, Hao Peng, Ruoqi Shen, Yao Fu, Zaïd Harchaoui, Yejin Choi:
FiLM: Fill-in Language Models for Any-Order Generation. CoRR abs/2310.09930 (2023) - [i45]Ronak Mehta, Vincent Roulet, Krishna Pillutla, Zaïd Harchaoui:
Distributionally Robust Optimization with Bias and Variance Reduction. CoRR abs/2310.13863 (2023) - 2022
- [j17]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) - [j16]Corinne Jones, Vincent Roulet, Zaïd Harchaoui:
Discriminative clustering with representation learning with any ratio of labeled to unlabeled data. Stat. Comput. 32(1): 17 (2022) - [j15]Krishna Pillutla, Sham M. Kakade, Zaïd Harchaoui:
Robust Aggregation for Federated Learning. IEEE Trans. Signal Process. 70: 1142-1154 (2022) - [j14]Yassine Laguel, Jérôme Malick, Zaïd Harchaoui:
Superquantile-Based Learning: A Direct Approach Using Gradient-Based Optimization. J. Signal Process. Syst. 94(2): 161-177 (2022) - [c62]Nicholas J. Irons, Meyer Scetbon, Soumik Pal, Zaïd Harchaoui:
Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates. AISTATS 2022: 10161-10195 - [c61]Lang Liu, Soumik Pal, Zaïd Harchaoui:
Entropy Regularized Optimal Transport Independence Criterion. AISTATS 2022: 11247-11279 - [c60]Lang Liu, Carlos Cinelli, Zaïd Harchaoui:
Orthogonal Statistical Learning with Self-Concordant Loss. COLT 2022: 5253-5277 - [c59]Vincent Roulet, Zaïd Harchaoui:
Differentiable Programming A La Moreau. ICASSP 2022: 3498-3502 - [i44]Lang Liu, Carlos Cinelli, Zaïd Harchaoui:
Orthogonal Statistical Learning with Self-Concordant Loss. CoRR abs/2205.00350 (2022) - [i43]Vincent Roulet, Siddhartha S. Srinivasa, Maryam Fazel, Zaïd Harchaoui:
Iterative Linear Quadratic Optimization for Nonlinear Control: Differentiable Programming Algorithmic Templates. CoRR abs/2207.06362 (2022) - [i42]Zaïd Harchaoui, Sewoong Oh, Soumik Pal, Raghav Somani, Raghavendra Tripathi:
Stochastic optimization on matrices and a graphon McKean-Vlasov limit. CoRR abs/2210.00422 (2022) - [i41]Jillian Fisher, Lang Liu, Krishna Pillutla, Yejin Choi, Zaïd Harchaoui:
Statistical and Computational Guarantees for Influence Diagnostics. CoRR abs/2212.04014 (2022) - [i40]Ronak Mehta, Vincent Roulet, Krishna Pillutla, Lang Liu, Zaïd Harchaoui:
Stochastic Optimization for Spectral Risk Measures. CoRR abs/2212.05149 (2022) - [i39]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 abs/2212.14578 (2022) - 2021
- [j13]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): 1-210 (2021) - [c58]Meyer Scetbon, Zaïd Harchaoui:
A Spectral Analysis of Dot-product Kernels. AISTATS 2021: 3394-3402 - [c57]Yassine Laguel, Krishna Pillutla, Jérôme Malick, Zaïd Harchaoui:
A Superquantile Approach to Federated Learning with Heterogeneous Devices. CISS 2021: 1-6 - [c56]Vincent Roulet, Zaïd Harchaoui:
On the Smoothing of Deep Networks. CISS 2021: 1-6 - [c55]Lang Liu, Joseph Salmon, Zaïd Harchaoui:
Score-Based Change Detection For Gradient-Based Learning Machines. ICASSP 2021: 4990-4994 - [c54]Samuel K. Ainsworth, Kendall Lowrey, John Thickstun, Zaïd Harchaoui, Siddhartha S. Srinivasa:
Faster Policy Learning with Continuous-Time Gradients. L4DC 2021: 1054-1067 - [c53]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: 4816-4828 - [c52]Joshua Cutler, Dmitriy Drusvyatskiy, Zaïd Harchaoui:
Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees. NeurIPS 2021: 11859-11869 - [c51]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: 12930-12942 - [i38]Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Yejin Choi, Zaïd Harchaoui:
MAUVE: Human-Machine Divergence Curves for Evaluating Open-Ended Text Generation. CoRR abs/2102.01454 (2021) - [i37]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 abs/2106.07898 (2021) - [i36]Lang Liu, Joseph Salmon, Zaïd Harchaoui:
Score-Based Change Detection for Gradient-Based Learning Machines. CoRR abs/2106.14122 (2021) - [i35]Joshua Cutler, Dmitriy Drusvyatskiy, Zaïd Harchaoui:
Stochastic optimization under time drift: iterate averaging, step decay, and high probability guarantees. CoRR abs/2108.07356 (2021) - [i34]Vincent Roulet, Zaïd Harchaoui:
Target Propagation via Regularized Inversion. CoRR abs/2112.01453 (2021) - [i33]Krishna Pillutla, Yassine Laguel, Jérôme Malick, Zaïd Harchaoui:
Federated Learning with Heterogeneous Data: A Superquantile Optimization Approach. CoRR abs/2112.09429 (2021) - [i32]Lang Liu, Soumik Pal, Zaïd Harchaoui:
Entropy Regularized Optimal Transport Independence Criterion. CoRR abs/2112.15265 (2021) - [i31]Nicholas J. Irons, Meyer Scetbon, Soumik Pal, Zaïd Harchaoui:
Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates. CoRR abs/2112.15595 (2021) - 2020
- [c50]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: 132-137 - [c49]Meyer Scetbon, Zaïd Harchaoui:
Harmonic Decompositions of Convolutional Networks. ICML 2020: 8522-8532 - [c48]Corinne Jones, Zaïd Harchaoui:
End-to-End Learning for Retrospective Change-Point Estimation. MLSP 2020: 1-6 - [c47]Yassine Laguel, Jérôme Malick, Zaïd Harchaoui:
First-Order Optimization for Superquantile-Based Supervised Learning. MLSP 2020: 1-6 - [i30]Vincent Roulet, Zaïd Harchaoui:
An Elementary Approach to Convergence Guarantees of Optimization Algorithms for Deep Networks. CoRR abs/2002.09051 (2020) - [i29]Yassine Laguel, Krishna Pillutla, Jérôme Malick, Zaïd Harchaoui:
Device Heterogeneity in Federated Learning: A Superquantile Approach. CoRR abs/2002.11223 (2020) - [i28]Meyer Scetbon, Zaïd Harchaoui:
Risk Bounds for Multi-layer Perceptrons through Spectra of Integral Operators. CoRR abs/2002.12640 (2020) - [i27]Meyer Scetbon, Zaïd Harchaoui:
Harmonic Decompositions of Convolutional Networks. CoRR abs/2003.12756 (2020) - [i26]Yassine Laguel, Jérôme Malick, Zaïd Harchaoui:
First-order Optimization for Superquantile-based Supervised Learning. CoRR abs/2009.14575 (2020) - [i25]Samuel K. Ainsworth, Kendall Lowrey, John Thickstun, Zaïd Harchaoui, Siddhartha S. Srinivasa:
Faster Policy Learning with Continuous-Time Gradients. CoRR abs/2012.06684 (2020) - [i24]Vincent Roulet, Zaïd Harchaoui:
Differentiable Programming à la Moreau. CoRR abs/2012.15458 (2020)
2010 – 2019
- 2019
- [j12]Sylvain Arlot, Alain Celisse, Zaïd Harchaoui:
A Kernel Multiple Change-point Algorithm via Model Selection. J. Mach. Learn. Res. 20: 162:1-162:56 (2019) - [j11]Hongzhou Lin, Julien Mairal, Zaïd Harchaoui:
An Inexact Variable Metric Proximal Point Algorithm for Generic Quasi-Newton Acceleration. SIAM J. Optim. 29(2): 1408-1443 (2019) - [c46]Vincent Roulet, Zaïd Harchaoui:
An Elementary Approach to Convergence Guarantees of Optimization Algorithms for Deep Networks. Allerton 2019: 84-91 - [c45]Christopher Xie, Yu Xiang, Zaïd Harchaoui, Dieter Fox:
Object Discovery in Videos as Foreground Motion Clustering. CVPR 2019: 9994-10003 - [c44]Alexander Greaves-Tunnell, Zaïd Harchaoui:
A Statistical Investigation of Long Memory in Language and Music. ICML 2019: 2394-2403 - [c43]Vincent Roulet, Dmitriy Drusvyatskiy, Siddhartha S. Srinivasa, Zaïd Harchaoui:
Iterative Linearized Control: Stable Algorithms and Complexity Guarantees. ICML 2019: 5518-5527 - [c42]Christopher Xie, Emily B. Fox, Zaïd Harchaoui:
A Simple Adaptive Tracker with Reminiscences. ICRA 2019: 6596-6603 - [c41]John Thickstun, Zaïd Harchaoui, Dean P. Foster, Sham M. Kakade:
Coupled Recurrent Models for Polyphonic Music Composition. ISMIR 2019: 311-318 - [i23]Venkata Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaïd Harchaoui:
A Smoother Way to Train Structured Prediction Models. CoRR abs/1902.03228 (2019) - [i22]Corinne Jones, Vincent Roulet, Zaïd Harchaoui:
Kernel-based Translations of Convolutional Networks. CoRR abs/1903.08131 (2019) - [i21]Alexander Greaves-Tunnell, Zaïd Harchaoui:
A Statistical Investigation of Long Memory in Language and Music. CoRR abs/1904.03834 (2019) - [i20]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 abs/1912.04977 (2019) - [i19]Corinne Jones, Vincent Roulet, Zaïd Harchaoui:
End-to-end Learning, with or without Labels. CoRR abs/1912.12979 (2019) - [i18]Venkata Krishna Pillutla, Sham M. Kakade, Zaïd Harchaoui:
Robust Aggregation for Federated Learning. CoRR abs/1912.13445 (2019) - 2018
- [j10]Yury Maximov, Massih-Reza Amini, Zaïd Harchaoui:
Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm. J. Artif. Intell. Res. 61: 761-786 (2018) - [c40]Courtney Paquette, Hongzhou Lin, Dmitriy Drusvyatskiy, Julien Mairal, Zaïd Harchaoui:
Catalyst for Gradient-based Nonconvex Optimization. AISTATS 2018: 613-622 - [c39]John Thickstun, Zaïd Harchaoui, Dean P. Foster, Sham M. Kakade:
Invariances and Data Augmentation for Supervised Music Transcription. ICASSP 2018: 2241-2245 - [c38]Dmitrii Ostrovskii, Zaïd Harchaoui:
Efficient First-Order Algorithms for Adaptive Signal Denoising. ICML 2018: 3943-3952 - [c37]Yury Maximov, Massih-Reza Amini, Zaïd Harchaoui:
Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm (Extended Abstract). IJCAI 2018: 5637-5641 - [c36]Venkata Krishna Pillutla, Vincent Roulet, Sham M. Kakade, Zaïd Harchaoui:
A Smoother Way to Train Structured Prediction Models. NeurIPS 2018: 4771-4783 - [i17]John Thickstun, Zaïd Harchaoui, Dean P. Foster, Sham M. Kakade:
Coupled Recurrent Models for Polyphonic Music Composition. CoRR abs/1811.08045 (2018) - [i16]Christopher Xie, Yu Xiang, Dieter Fox, Zaïd Harchaoui:
Object Discovery in Videos as Foreground Motion Clustering. CoRR abs/1812.02772 (2018) - 2017
- [j9]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): 149-168 (2017) - [j8]Hongzhou Lin, Julien Mairal, Zaïd Harchaoui:
Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice. J. Mach. Learn. Res. 18: 212:1-212:54 (2017) - [c35]Nikhil Rao, Miroslav Dudík, Zaïd Harchaoui:
The group k-support norm for learning with structured sparsity. ICASSP 2017: 2402-2406 - [c34]John Thickstun, Zaïd Harchaoui, Sham M. Kakade:
Learning Features of Music From Scratch. ICLR (Poster) 2017 - [c33]Danila Potapov, Matthijs Douze, Jérôme Revaud, Zaïd Harchaoui, Cordelia Schmid:
Inferring the Structure of Action Movies. WICED@Eurographics 2017: 19-27 - [i15]John Thickstun, Zaïd Harchaoui, Dean P. Foster, Sham M. Kakade:
Invariances and Data Augmentation for Supervised Music Transcription. CoRR abs/1711.04845 (2017) - 2016
- [j7]Jérôme Revaud, Philippe Weinzaepfel, Zaïd Harchaoui, Cordelia Schmid:
DeepMatching: Hierarchical Deformable Dense Matching. Int. J. Comput. Vis. 120(3): 300-323 (2016) - [j6]Zeynep Akata, Florent Perronnin, Zaïd Harchaoui, Cordelia Schmid:
Label-Embedding for Image Classification. IEEE Trans. Pattern Anal. Mach. Intell. 38(7): 1425-1438 (2016) - [c32]Dmitry Ostrovsky, Zaïd Harchaoui, Anatoli B. Juditsky, Arkadi Nemirovski:
Structure-Blind Signal Recovery. NIPS 2016: 4817-4825 - [i14]Mattis Paulin, Julien Mairal, Matthijs Douze, Zaïd Harchaoui, Florent Perronnin, Cordelia Schmid:
Convolutional Patch Representations for Image Retrieval: an Unsupervised Approach. CoRR abs/1603.00438 (2016) - [i13]Yury Maximov, Massih-Reza Amini, Zaïd Harchaoui:
Rademacher Complexity Bounds for a Penalized Multiclass Semi-Supervised Algorithm. CoRR abs/1607.00567 (2016) - [i12]Niao He, Zaïd Harchaoui, Yichen Wang, Le Song:
Fast and Simple Optimization for Poisson Likelihood Models. CoRR abs/1608.01264 (2016) - [i11]John Thickstun, Zaïd Harchaoui, Sham M. Kakade:
Learning Features of Music from Scratch. CoRR abs/1611.09827 (2016) - 2015
- [j5]Zaïd Harchaoui, Anatoli B. Juditsky, Arkadi Nemirovski:
Conditional gradient algorithms for norm-regularized smooth convex optimization. Math. Program. 152(1-2): 75-112 (2015) - [c31]Zaïd Harchaoui, Anatoli B. Juditsky, Arkadi Nemirovski, Dmitry Ostrovsky:
Adaptive Recovery of Signals by Convex Optimization. COLT 2015: 929-955 - [c30]Jérôme Revaud, Philippe Weinzaepfel, Zaïd Harchaoui, Cordelia Schmid:
EpicFlow: Edge-preserving interpolation of correspondences for optical flow. CVPR 2015: 1164-1172 - [c29]Philippe Weinzaepfel, Jérôme Revaud, Zaïd Harchaoui, Cordelia Schmid:
Learning to detect Motion Boundaries. CVPR 2015: 2578-2586 - [c28]Mattis Paulin, Matthijs Douze, Zaïd Harchaoui, Julien Mairal, Florent Perronnin, Cordelia Schmid:
Local Convolutional Features with Unsupervised Training for Image Retrieval. ICCV 2015: 91-99 - [c27]Philippe Weinzaepfel, Zaïd Harchaoui, Cordelia Schmid:
Learning to Track for Spatio-Temporal Action Localization. ICCV 2015: 3164-3172 - [c26]Hongzhou Lin, Julien Mairal, Zaïd Harchaoui:
A Universal Catalyst for First-Order Optimization. NIPS 2015: 3384-3392 - [c25]Niao He, Zaïd Harchaoui:
Semi-Proximal Mirror-Prox for Nonsmooth Composite Minimization. NIPS 2015: 3411-3419 - [i10]Jérôme Revaud, Philippe Weinzaepfel, Zaïd Harchaoui, Cordelia Schmid:
EpicFlow: Edge-Preserving Interpolation of Correspondences for Optical Flow. CoRR abs/1501.02565 (2015) - [i9]Zeynep Akata, Florent Perronnin, Zaïd Harchaoui, Cordelia Schmid:
Label-Embedding for Image Classification. CoRR abs/1503.08677 (2015) - [i8]Philippe Weinzaepfel, Zaïd Harchaoui, Cordelia Schmid:
Learning to track for spatio-temporal action localization. CoRR abs/1506.01929 (2015) - [i7]Jérôme Revaud, Philippe Weinzaepfel, Zaïd Harchaoui, Cordelia Schmid:
Deep Convolutional Matching. CoRR abs/1506.07656 (2015) - [i6]Niao He, Zaïd Harchaoui:
Semi-proximal Mirror-Prox for Nonsmooth Composite Minimization. CoRR abs/1507.01476 (2015) - [i5]Danila Potapov, Matthijs Douze, Jérôme Revaud, Zaïd Harchaoui, Cordelia Schmid:
Beat-Event Detection in Action Movie Franchises. CoRR abs/1508.03755 (2015) - 2014
- [j4]Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid:
Activity representation with motion hierarchies. Int. J. Comput. Vis. 107(3): 219-238 (2014) - [j3]Zeynep Akata, Florent Perronnin, Zaïd Harchaoui, Cordelia Schmid:
Good Practice in Large-Scale Learning for Image Classification. IEEE Trans. Pattern Anal. Mach. Intell. 36(3): 507-520 (2014) - [c24]Yuansi Chen, Julien Mairal, Zaïd Harchaoui:
Fast and Robust Archetypal Analysis for Representation Learning. CVPR 2014: 1478-1485 - [c23]Mattis Paulin, Jérôme Revaud, Zaïd Harchaoui, Florent Perronnin, Cordelia Schmid:
Transformation Pursuit for Image Classification. CVPR 2014: 3646-3653 - [c22]Danila Potapov, Matthijs Douze, Zaïd Harchaoui, Cordelia Schmid:
Category-Specific Video Summarization. ECCV (6) 2014: 540-555 - [c21]Hyun Oh Song, Ross B. Girshick, Stefanie Jegelka, Julien Mairal, Zaïd Harchaoui, Trevor Darrell:
On learning to localize objects with minimal supervision. ICML 2014: 1611-1619 - [c20]Julien Mairal, Piotr Koniusz, Zaïd Harchaoui, Cordelia Schmid:
Convolutional Kernel Networks. NIPS 2014: 2627-2635 - [c19]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:
The INRIA-LIM-VocR and AXES submissions to TrecVid 2014 Multimedia Event Detection. TRECVID 2014 - [i4]Hyun Oh Song, Ross B. Girshick, Stefanie Jegelka, Julien Mairal, Zaïd Harchaoui, Trevor Darrell:
One-Bit Object Detection: On learning to localize objects with minimal supervision. CoRR abs/1403.1024 (2014) - [i3]Yuansi Chen, Julien Mairal, Zaïd Harchaoui:
Fast and Robust Archetypal Analysis for Representation Learning. CoRR abs/1405.6472 (2014) - [i2]Julien Mairal, Piotr Koniusz, Zaïd Harchaoui, Cordelia Schmid:
Convolutional Kernel Networks. CoRR abs/1406.3332 (2014) - 2013
- [j2]Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid:
Temporal Localization of Actions with Actoms. IEEE Trans. Pattern Anal. Mach. Intell. 35(11): 2782-2795 (2013) - [j1]Zaïd Harchaoui, Francis R. Bach, Olivier Cappé, Eric Moulines:
Kernel-Based Methods for Hypothesis Testing: A Unified View. IEEE Signal Process. Mag. 30(4): 87-97 (2013) - [c18]Zeynep Akata, Florent Perronnin, Zaïd Harchaoui, Cordelia Schmid:
Label-Embedding for Attribute-Based Classification. CVPR 2013: 819-826 - [c17]Philippe Weinzaepfel, Jérôme Revaud, Zaïd Harchaoui, Cordelia Schmid:
DeepFlow: Large Displacement Optical Flow with Deep Matching. ICCV 2013: 1385-1392 - [c16]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:
The AXES submissions at TRECVID 2013. TRECVID 2013 - [i1]Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid:
Automatic Recognition of Human Activities in Realistic Videos. ERCIM News 2013(95) (2013) - 2012
- [c15]Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid:
Recognizing activities with cluster-trees of tracklets. BMVC 2012: 1-13 - [c14]Zaïd Harchaoui, Matthijs Douze, Mattis Paulin, Miroslav Dudík, Jérôme Malick:
Large-scale image classification with trace-norm regularization. CVPR 2012: 3386-3393 - [c13]Florent Perronnin, Zeynep Akata, Zaïd Harchaoui, Cordelia Schmid:
Towards good practice in large-scale learning for image classification. CVPR 2012: 3482-3489 - [c12]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:
AXES at TRECVID 2012: KIS, INS, and MED. TRECVID 2012 - [c11]Miroslav Dudík, Zaïd Harchaoui, Jérôme Malick:
Lifted coordinate descent for learning with trace-norm regularization. AISTATS 2012: 327-336 - 2011
- [c10]Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid:
A time series kernel for action recognition. BMVC 2011: 1-11 - [c9]Adrien Gaidon, Zaïd Harchaoui, Cordelia Schmid:
Actom sequence models for efficient action detection. CVPR 2011: 3201-3208
2000 – 2009
- 2009
- [c8]Zaïd Harchaoui, Félicien Vallet, Alexandre Lung-Yut-Fong, Olivier Cappé:
A regularized kernel-based approach to unsupervised audio segmentation. ICASSP 2009: 1665-1668 - [c7]Arthur Gretton, Kenji Fukumizu, Zaïd Harchaoui, Bharath K. Sriperumbudur:
A Fast, Consistent Kernel Two-Sample Test. NIPS 2009: 673-681 - 2008
- [c6]Zaïd Harchaoui, Francis R. Bach, Eric Moulines:
Kernel Change-point Analysis. NIPS 2008: 609-616 - 2007
- [c5]Zaïd Harchaoui, Francis R. Bach:
Image Classification with Segmentation Graph Kernels. CVPR 2007 - [c4]Francis R. Bach, Zaïd Harchaoui:
DIFFRAC: a discriminative and flexible framework for clustering. NIPS 2007: 49-56 - [c3]Zaïd Harchaoui, Francis R. Bach, Eric Moulines:
Testing for Homogeneity with Kernel Fisher Discriminant Analysis. NIPS 2007: 609-616 - [c2]Zaïd Harchaoui, Céline Lévy-Leduc:
Catching Change-points with Lasso. NIPS 2007: 617-624 - 2004
- [c1]Olivier Chapelle, Zaïd Harchaoui:
A Machine Learning Approach to Conjoint Analysis. NIPS 2004: 257-264
Coauthor Index
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