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06/03/2022
Towards Evading the Limits of Randomized Smoothing: A Theoretical Analysis
Randomized smoothing is the dominant standard for provable defenses agai...
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05/20/2022
Towards Consistency in Adversarial Classification
In this paper, we study the problem of consistency in the context of adv...
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12/08/2021
Non parametric estimation of causal populations in a counterfactual scenario
In causality, estimating the effect of a treatment without confounding i...
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10/28/2021
Two-sided fairness in rankings via Lorenz dominance
We consider the problem of generating rankings that are fair towards bot...
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05/19/2021
Online Selection of Diverse Committees
Citizens' assemblies need to represent subpopulations according to their...
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04/29/2021
Online certification of preference-based fairness for personalized recommender systems
We propose to assess the fairness of personalized recommender systems in...
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02/22/2021
On the robustness of randomized classifiers to adversarial examples
This paper investigates the theory of robustness against adversarial att...
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02/13/2021
Mixed Nash Equilibria in the Adversarial Examples Game
This paper tackles the problem of adversarial examples from a game theor...
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09/07/2020
Detecting and adapting to crisis pattern with context based Deep Reinforcement Learning
Deep reinforcement learning (DRL) has reached super human levels in comp...
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06/15/2020
Fast Accurate Method for Bounding the Singular Values of Convolutional Layers with Application to Lipschitz Regularization
This paper tackles the problem of Lipschitz regularization of Convolutio...
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06/12/2020
Handling Multiple Costs in Optimal Transport: Strong Duality and Efficient Computation
We introduce an extension of the optimal transportation (OT) problem whe...
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02/26/2020
Randomization matters. How to defend against strong adversarial attacks
Is there a classifier that ensures optimal robustness against all advers...
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10/05/2019
Yet another but more efficient black-box adversarial attack: tiling and evolution strategies
We introduce a new black-box attack achieving state of the art performan...
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06/19/2019
A unified view on differential privacy and robustness to adversarial examples
This short note highlights some links between two lines of research with...
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05/14/2019
NGO-GM: Natural Gradient Optimization for Graphical Models
This paper deals with estimating model parameters in graphical models. W...
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03/25/2019
Robust Neural Networks using Randomized Adversarial Training
Since the discovery of adversarial examples in machine learning, researc...
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02/04/2019
Theoretical evidence for adversarial robustness through randomization: the case of the Exponential family
This paper investigates the theory of robustness against adversarial att...
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01/29/2019
On the Expressive Power of Deep Fully Circulant Neural Networks
In this paper, we study deep fully circulant neural networks, that is de...
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12/27/2018
A discrete version of CMA-ES
Modern machine learning uses more and more advanced optimization techniq...
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10/02/2018
Training compact deep learning models for video classification using circulant matrices
In real world scenarios, model accuracy is hardly the only factor to con...
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03/10/2018
Graph-based Clustering under Differential Privacy
In this paper, we present the first differentially private clustering me...
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03/05/2018
Explanatory relations in arbitrary logics based on satisfaction systems, cutting and retraction
The aim of this paper is to introduce a new framework for defining abduc...
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02/12/2018
On the Needs for Rotations in Hypercubic Quantization Hashing
The aim of this paper is to endow the well-known family of hypercubic qu...
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09/29/2016
Multi-dimensional signal approximation with sparse structured priors using split Bregman iterations
This paper addresses the structurally-constrained sparse decomposition o...
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05/29/2016
TripleSpin - a generic compact paradigm for fast machine learning computations
We present a generic compact computational framework relying on structur...
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02/26/2015
Relaxation-based revision operators in description logics
As ontologies and description logics (DLs) reach out to a broader audien...
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03/21/2013
Multi-dimensional sparse structured signal approximation using split Bregman iterations
The paper focuses on the sparse approximation of signals using overcompl...
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02/18/2013
