← Authors

Zaïd Harchaoui

51 papers · 2007–2025 · 12 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (15) 🌈 Renaissance Researcher (5) 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (18) 🗺️ Taxonomy Completionist (24) 🌍 Conference Polyglot (12) 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (10) 🌱 Topic Pioneer 🔬 Deep Specialist (14) 🏆 Keyword Champion (3) 🔥 Unstoppable (8) 🚀 Conference Pioneer 🗃️ Keyword Collector (76) ⚡ Prolific Year (5) 💎 Century Club (51) 📈 Trend Setter

Conferences

NIPS (16) AISTATS (8) CVPR (6) ICML (6) JMLR (5) ICCV (3) COLT (2) EMNLP (1) ICLR (1) IJCAI (1) L4DC (1) NAACL (1)

Top co-authors

Cordelia Schmid (8) Julien Mairal (7) Yejin Choi (7) Lang Liu (7) Krishna Pillutla (6) Ronak Mehta (5) Vincent Roulet (5) Dmitriy Drusvyatskiy (4) Sean Welleck (4) Philippe Weinzaepfel (4)

Research topics

Statistics (2) Methods (1) Core AI (1)

Keywords

convex optimization (7) kernel methods (7) convolutional neural network (4) gradient descent (4) statistical learning (4) text generation (4) stochastic optimization (4) reproducing kernel hilbert space (3) oracle inequality (3) image classification (3) hypothesis testing (3) statistical testing (3) first-order method (3) optical flow (3) change-point detection (3) variance reduction (3) feature learning (2) semi-supervised learning (2) unsupervised learning (2) video understanding (2)

Papers

Spectral Differential Network Analysis for High-Dimensional Time Series AISTATS 2025
On Global and Local Convergence of Iterative Linear Quadratic Optimization Algorithms for Discrete Time Nonlinear Control JMLR 2025
A Generalization Theory for Zero-Shot Prediction ICML 2025
The Benefits of Balance: From Information Projections to Variance Reduction NIPS 2024
Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization NIPS 2024
StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style Elements EMNLP 2024
JAMDEC: Unsupervised Authorship Obfuscation using Constrained Decoding over Small Language Models NAACL 2024
Distributionally Robust Optimization with Bias and Variance Reduction ICLR 2024
Faith and Fate: Limits of Transformers on Compositionality NIPS 2023
MAUVE Scores for Generative Models: Theory and Practice JMLR 2023
Stochastic Optimization under Distributional Drift JMLR 2023
Influence Diagnostics under Self-concordance AISTATS 2023
Stochastic Optimization for Spectral Risk Measures AISTATS 2023
Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates AISTATS 2022
Orthogonal Statistical Learning with Self-Concordant Loss COLT 2022
Entropy Regularized Optimal Transport Independence Criterion AISTATS 2022
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals NIPS 2021
Faster Policy Learning with Continuous-Time Gradients L4DC 2021
A Spectral Analysis of Dot-product Kernels AISTATS 2021
Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees NIPS 2021
MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers NIPS 2021
Harmonic Decompositions of Convolutional Networks ICML 2020
A Statistical Investigation of Long Memory in Language and Music ICML 2019
Object Discovery in Videos as Foreground Motion Clustering CVPR 2019
Iterative Linearized Control: Stable Algorithms and Complexity Guarantees ICML 2019
A Kernel Multiple Change-point Algorithm via Model Selection JMLR 2019
Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice JMLR 2018
A Smoother Way to Train Structured Prediction Models NIPS 2018
Catalyst for Gradient-based Nonconvex Optimization AISTATS 2018
Efficient First-Order Algorithms for Adaptive Signal Denoising ICML 2018
Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm (Extended Abstract) IJCAI 2018
Structure-Blind Signal Recovery NIPS 2016
Learning to Detect Motion Boundaries CVPR 2015
Local Convolutional Features With Unsupervised Training for Image Retrieval ICCV 2015
Learning to Track for Spatio-Temporal Action Localization ICCV 2015
Adaptive Recovery of Signals by Convex Optimization COLT 2015
A Universal Catalyst for First-Order Optimization NIPS 2015
Semi-Proximal Mirror-Prox for Nonsmooth Composite Minimization NIPS 2015
EpicFlow: Edge-Preserving Interpolation of Correspondences for Optical Flow CVPR 2015
On learning to localize objects with minimal supervision ICML 2014
Fast and Robust Archetypal Analysis for Representation Learning CVPR 2014
Transformation Pursuit for Image Classification CVPR 2014
Convolutional Kernel Networks NIPS 2014
Label-Embedding for Attribute-Based Classification CVPR 2013
DeepFlow: Large Displacement Optical Flow with Deep Matching ICCV 2013
Lifted coordinate descent for learning with trace-norm regularization AISTATS 2012
A Fast, Consistent Kernel Two-Sample Test NIPS 2009
Kernel Change-point Analysis NIPS 2008
DIFFRAC: a discriminative and flexible framework for clustering NIPS 2007
Testing for Homogeneity with Kernel Fisher Discriminant Analysis NIPS 2007
Catching Change-points with Lasso NIPS 2007