Zaïd Harchaoui

Orcid: 0000-0003-1186-1343

According to our database1, Zaïd Harchaoui authored at least 116 papers between 2004 and 2024.

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Bibliography

2024
Federated learning with superquantile aggregation for heterogeneous data.
Mach. Learn., May, 2024

StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style Elements.
CoRR, 2024

The Benefits of Balance: From Information Projections to Variance Reduction.
CoRR, 2024

From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models.
CoRR, 2024

A Primal-Dual Algorithm for Faster Distributionally Robust Optimization.
CoRR, 2024

JAMDEC: Unsupervised Authorship Obfuscation using Constrained Decoding over Small Language Models.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Distributionally Robust Optimization with Bias and Variance Reduction.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

The Rao, Wald, And Likelihood-Ratio Tests under Generalized Self-Concordance.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
Target Propagation via Regularized Inversion for Recurrent Neural Networks.
Trans. Mach. Learn. Res., 2023

MAUVE Scores for Generative Models: Theory and Practice.
J. Mach. Learn. Res., 2023

Stochastic Optimization under Distributional Drift.
J. Mach. Learn. Res., 2023

Revisiting Convolutional Neural Networks from the Viewpoint of Kernel-Based Methods.
J. Comput. Graph. Stat., 2023

FiLM: Fill-in Language Models for Any-Order Generation.
CoRR, 2023

Modified Gauss-Newton Algorithms under Noise.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2023

Faith and Fate: Limits of Transformers on Compositionality.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Stochastic Optimization for Spectral Risk Measures.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Influence Diagnostics under Self-concordance.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Superquantile-Based Learning: A Direct Approach Using Gradient-Based Optimization.
J. Signal Process. Syst., 2022

Robust Aggregation for Federated Learning.
IEEE Trans. Signal Process., 2022

Discriminative clustering with representation learning with any ratio of labeled to unlabeled data.
Stat. Comput., 2022

A Bayesian approach to modeling phytoplankton population dynamics from size distribution time series.
PLoS Comput. Biol., 2022

Statistical and Computational Guarantees for Influence Diagnostics.
CoRR, 2022

Stochastic optimization on matrices and a graphon McKean-Vlasov limit.
CoRR, 2022

Iterative Linear Quadratic Optimization for Nonlinear Control: Differentiable Programming Algorithmic Templates.
CoRR, 2022

Differentiable Programming A La Moreau.
Proceedings of the IEEE International Conference on Acoustics, 2022

Orthogonal Statistical Learning with Self-Concordant Loss.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Entropy Regularized Optimal Transport Independence Criterion.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Advances and Open Problems in Federated Learning.
Found. Trends Mach. Learn., 2021

Federated Learning with Heterogeneous Data: A Superquantile Optimization Approach.
CoRR, 2021

Target Propagation via Regularized Inversion.
CoRR, 2021

Stochastic optimization under time drift: iterate averaging, step decay, and high probability guarantees.
CoRR, 2021

Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral.
CoRR, 2021

MAUVE: Human-Machine Divergence Curves for Evaluating Open-Ended Text Generation.
CoRR, 2021

MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Faster Policy Learning with Continuous-Time Gradients.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Score-Based Change Detection For Gradient-Based Learning Machines.
Proceedings of the IEEE International Conference on Acoustics, 2021

On the Smoothing of Deep Networks.
Proceedings of the 55th Annual Conference on Information Sciences and Systems, 2021

A Superquantile Approach to Federated Learning with Heterogeneous Devices.
Proceedings of the 55th Annual Conference on Information Sciences and Systems, 2021

A Spectral Analysis of Dot-product Kernels.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Risk Bounds for Multi-layer Perceptrons through Spectra of Integral Operators.
CoRR, 2020

Device Heterogeneity in Federated Learning: A Superquantile Approach.
CoRR, 2020

First-Order Optimization for Superquantile-Based Supervised Learning.
Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

End-to-End Learning for Retrospective Change-Point Estimation.
Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

Harmonic Decompositions of Convolutional Networks.
Proceedings of the 37th International Conference on Machine Learning, 2020

On the Convergence of the Iterative Linear Exponential Quadratic Gaussian Algorithm to Stationary Points.
Proceedings of the 2020 American Control Conference, 2020

2019
An Inexact Variable Metric Proximal Point Algorithm for Generic Quasi-Newton Acceleration.
SIAM J. Optim., 2019

A Kernel Multiple Change-point Algorithm via Model Selection.
J. Mach. Learn. Res., 2019

Robust Aggregation for Federated Learning.
CoRR, 2019

End-to-end Learning, with or without Labels.
CoRR, 2019

Advances and Open Problems in Federated Learning.
CoRR, 2019

Kernel-based Translations of Convolutional Networks.
CoRR, 2019

Coupled Recurrent Models for Polyphonic Music Composition.
Proceedings of the 20th International Society for Music Information Retrieval Conference, 2019

A Simple Adaptive Tracker with Reminiscences.
Proceedings of the International Conference on Robotics and Automation, 2019

Iterative Linearized Control: Stable Algorithms and Complexity Guarantees.
Proceedings of the 36th International Conference on Machine Learning, 2019

A Statistical Investigation of Long Memory in Language and Music.
Proceedings of the 36th International Conference on Machine Learning, 2019

Object Discovery in Videos as Foreground Motion Clustering.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

An Elementary Approach to Convergence Guarantees of Optimization Algorithms for Deep Networks.
Proceedings of the 57th Annual Allerton Conference on Communication, 2019

2018
Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm.
J. Artif. Intell. Res., 2018

A Smoother Way to Train Structured Prediction Models.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm (Extended Abstract).
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Efficient First-Order Algorithms for Adaptive Signal Denoising.
Proceedings of the 35th International Conference on Machine Learning, 2018

Invariances and Data Augmentation for Supervised Music Transcription.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Catalyst for Gradient-based Nonconvex Optimization.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice.
J. Mach. Learn. Res., 2017

Convolutional Patch Representations for Image Retrieval: An Unsupervised Approach.
Int. J. Comput. Vis., 2017

Inferring the Structure of Action Movies.
Proceedings of the 6th Workshop on Intelligent Cinematography and Editing, 2017

Learning Features of Music From Scratch.
Proceedings of the 5th International Conference on Learning Representations, 2017

The group k-support norm for learning with structured sparsity.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016
Label-Embedding for Image Classification.
IEEE Trans. Pattern Anal. Mach. Intell., 2016

DeepMatching: Hierarchical Deformable Dense Matching.
Int. J. Comput. Vis., 2016

Rademacher Complexity Bounds for a Penalized Multiclass Semi-Supervised Algorithm.
CoRR, 2016

Fast and Simple Optimization for Poisson Likelihood Models.
CoRR, 2016

Structure-Blind Signal Recovery.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Conditional gradient algorithms for norm-regularized smooth convex optimization.
Math. Program., 2015

Deep Convolutional Matching.
CoRR, 2015

Beat-Event Detection in Action Movie Franchises.
CoRR, 2015

A Universal Catalyst for First-Order Optimization.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Semi-Proximal Mirror-Prox for Nonsmooth Composite Minimization.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Learning to Track for Spatio-Temporal Action Localization.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Local Convolutional Features with Unsupervised Training for Image Retrieval.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Learning to detect Motion Boundaries.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

EpicFlow: Edge-preserving interpolation of correspondences for optical flow.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

Adaptive Recovery of Signals by Convex Optimization.
Proceedings of The 28th Conference on Learning Theory, 2015

2014
Good Practice in Large-Scale Learning for Image Classification.
IEEE Trans. Pattern Anal. Mach. Intell., 2014

Activity representation with motion hierarchies.
Int. J. Comput. Vis., 2014

One-Bit Object Detection: On learning to localize objects with minimal supervision.
CoRR, 2014

The INRIA-LIM-VocR and AXES submissions to TrecVid 2014 Multimedia Event Detection.
Proceedings of the 2014 TREC Video Retrieval Evaluation, 2014

Convolutional Kernel Networks.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

On learning to localize objects with minimal supervision.
Proceedings of the 31th International Conference on Machine Learning, 2014

Category-Specific Video Summarization.
Proceedings of the Computer Vision - ECCV 2014, 2014

Transformation Pursuit for Image Classification.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

Fast and Robust Archetypal Analysis for Representation Learning.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013
Kernel-Based Methods for Hypothesis Testing: A Unified View.
IEEE Signal Process. Mag., 2013

Temporal Localization of Actions with Actoms.
IEEE Trans. Pattern Anal. Mach. Intell., 2013

Automatic Recognition of Human Activities in Realistic Videos.
ERCIM News, 2013


DeepFlow: Large Displacement Optical Flow with Deep Matching.
Proceedings of the IEEE International Conference on Computer Vision, 2013

Label-Embedding for Attribute-Based Classification.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

2012
Lifted coordinate descent for learning with trace-norm regularization.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012


Towards good practice in large-scale learning for image classification.
Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

Large-scale image classification with trace-norm regularization.
Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

Recognizing activities with cluster-trees of tracklets.
Proceedings of the British Machine Vision Conference, 2012

2011
Actom sequence models for efficient action detection.
Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

A time series kernel for action recognition.
Proceedings of the British Machine Vision Conference, 2011

2009
A Fast, Consistent Kernel Two-Sample Test.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

A regularized kernel-based approach to unsupervised audio segmentation.
Proceedings of the IEEE International Conference on Acoustics, 2009

2008
Kernel Change-point Analysis.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007
Catching Change-points with Lasso.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Testing for Homogeneity with Kernel Fisher Discriminant Analysis.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

DIFFRAC: a discriminative and flexible framework for clustering.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Image Classification with Segmentation Graph Kernels.
Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2007), 2007

2004
A Machine Learning Approach to Conjoint Analysis.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004


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