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08/01/2023
Robust Linear Regression: Phase-Transitions and Precise Tradeoffs for General Norms
In this paper, we investigate the impact of test-time adversarial attack...
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01/31/2023
Robust Linear Regression: Gradient-descent, Early-stopping, and Beyond
In this work we study the robustness to adversarial attacks, of early-st...
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11/04/2022
An Adversarial Robustness Perspective on the Topology of Neural Networks
In this paper, we investigate the impact of neural networks (NNs) topolo...
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10/18/2022
Contextual bandits with concave rewards, and an application to fair ranking
We consider Contextual Bandits with Concave Rewards (CBCR), a multi-obje...
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09/13/2022
Fast online ranking with fairness of exposure
As recommender systems become increasingly central for sorting and prior...
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07/01/2022
Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes
A determinantal point process (DPP) is an elegant model that assigns a p...
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03/25/2022
Origins of Low-dimensional Adversarial Perturbations
In this note, we initiate a rigorous study of the phenomenon of low-dime...
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03/22/2022
On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes
Neural networks are known to be highly sensitive to adversarial examples...
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01/20/2022
Scalable Sampling for Nonsymmetric Determinantal Point Processes
A determinantal point process (DPP) on a collection of M items is a mode...
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06/04/2021
Fundamental tradeoffs between memorization and robustness in random features and neural tangent regimes
This work studies the (non)robustness of two-layer neural networks in va...
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11/12/2020
Implicit bias of any algorithm: bounding bias via margin
Consider n points x_1,…,x_n in finite-dimensional euclidean space, each ...
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06/17/2020
Universal Lower-Bounds on Classification Error under Adversarial Attacks and Random Corruption
We theoretically analyse the limits of robustness to test-time adversari...
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06/17/2020
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
Determinantal point processes (DPPs) have attracted significant attentio...
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06/08/2020
Learning disconnected manifolds: a no GANs land
Typical architectures of Generative AdversarialNetworks make use of a un...
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09/20/2019
On the Convergence of Approximate and Regularized Policy Iteration Schemes
Algorithms based on the entropy regularized framework, such as Soft Q-le...
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06/27/2019
Adversarial Robustness via Adversarial Label-Smoothing
We study Label-Smoothing as a means for improving adversarial robustness...
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06/14/2019
Distributionally Robust Counterfactual Risk Minimization
This manuscript introduces the idea of using Distributionally Robust Opt...
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05/30/2019
Learning Nonsymmetric Determinantal Point Processes
Determinantal point processes (DPPs) have attracted substantial attentio...
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02/23/2019
Distributionally Robust Reinforcement Learning
Generalization to unknown/uncertain environments of reinforcement learni...
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11/17/2018
Deep Determinantal Point Processes
Determinantal point processes (DPPs) have attracted significant attentio...
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10/08/2018
Limitations of adversarial robustness: strong No Free Lunch Theorem
This manuscript presents some new results on adversarial robustness in m...
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05/31/2016
Iterative Smoothing Proximal Gradient for Regression with Structured Sparsity
In the context high-dimensionnal predictive models, we consider the prob...
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12/22/2015
FAASTA: A fast solver for total-variation regularization of ill-conditioned problems with application to brain imaging
The total variation (TV) penalty, as many other analysis-sparsity proble...
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12/12/2014
