Nicolas Usunier

research

∙ 08/24/2023

Code Llama: Open Foundation Models for Code

We release Code Llama, a family of large language models for code based ...

0 Baptiste Roziere, et al. ∙

research

∙ 05/19/2023

Group fairness without demographics using social networks

Group fairness is a popular approach to prevent unfavorable treatment of...

0 David Liu, et al. ∙

research

∙ 02/16/2023

Towards Reliable Assessments of Demographic Disparities in Multi-Label Image Classifiers

Disaggregated performance metrics across demographic groups are a hallma...

8 Melissa Hall, et al. ∙

research

∙ 10/26/2022

Leveraging Demonstrations with Latent Space Priors

Demonstrations provide insight into relevant state or action space regio...

0 Jonas Gehring, et al. ∙

research

∙ 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...

0 Virginie Do, et al. ∙

research

∙ 10/05/2022

Parity in Markets – Methods, Costs, and Consequences

Fisher markets are those where buyers with budgets compete for scarce it...

0 Alexander Peysakhovich, et al. ∙

research

∙ 09/13/2022

Fast online ranking with fairness of exposure

As recommender systems become increasingly central for sorting and prior...

0 Nicolas Usunier, et al. ∙

research

∙ 07/20/2022

Measuring and signing fairness as performance under multiple stakeholder distributions

As learning machines increase their influence on decisions concerning hu...

0 David Lopez-Paz, et al. ∙

research

∙ 04/02/2022

Optimizing generalized Gini indices for fairness in rankings

There is growing interest in designing recommender systems that aim at b...

0 Virginie Do, et al. ∙

research

∙ 02/15/2022

Fairness Indicators for Systematic Assessments of Visual Feature Extractors

Does everyone equally benefit from computer vision systems? Answers to t...

0 Priya Goyal, et al. ∙

research

∙ 10/28/2021

Two-sided fairness in rankings via Lorenz dominance

We consider the problem of generating rankings that are fair towards bot...

0 Virginie Do, et al. ∙

research

∙ 10/20/2021

Hierarchical Skills for Efficient Exploration

In reinforcement learning, pre-trained low-level skills have the potenti...

3 Jonas Gehring, et al. ∙

research

∙ 05/19/2021

Online Selection of Diverse Committees

Citizens' assemblies need to represent subpopulations according to their...

0 Virginie Do, et al. ∙

research

∙ 04/29/2021

Online certification of preference-based fairness for personalized recommender systems

We propose to assess the fairness of personalized recommender systems in...

0 Virginie Do, et al. ∙

research

∙ 04/20/2021

Gradient Matching for Domain Generalization

Machine learning systems typically assume that the distributions of trai...

0 Yuge Shi, et al. ∙

research

∙ 04/17/2021

A Self-Supervised Auxiliary Loss for Deep RL in Partially Observable Settings

In this work we explore an auxiliary loss useful for reinforcement learn...

0 Eltayeb Ahmed, et al. ∙

research

∙ 05/26/2020

End-to-End Object Detection with Transformers

We present a new method that views object detection as a direct set pred...

23 Nicolas Carion, et al. ∙

research

∙ 05/06/2020

Learning Adaptive Exploration Strategies in Dynamic Environments Through Informed Policy Regularization

We study the problem of learning exploration-exploitation strategies tha...

5 Pierre-Alexandre Kamienny, et al. ∙

research

∙ 04/10/2020

Tensor Decompositions for temporal knowledge base completion

Most algorithms for representation learning and link prediction in relat...

2 Timothée Lacroix, et al. ∙

research

∙ 03/05/2020

On the Convergence of Adam and Adagrad

We provide a simple proof of the convergence of the optimization algorit...

19 Alexandre Défossez, et al. ∙

research

∙ 11/27/2019

Music Source Separation in the Waveform Domain

Source separation for music is the task of isolating contributions, or s...

0 Alexandre Défossez, et al. ∙

research

∙ 10/19/2019

A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement Learning

Effective coordination is crucial to solve multi-agent collaborative (MA...

14 Nicolas Carion, et al. ∙

research

∙ 09/03/2019

Demucs: Deep Extractor for Music Sources with extra unlabeled data remixed

We study the problem of source separation for music using deep learning ...

5 Alexandre Défossez, et al. ∙

research

∙ 06/28/2019

Growing Action Spaces

In complex tasks, such as those with large combinatorial action spaces, ...

7 Gregory Farquhar, et al. ∙

research

∙ 12/17/2018

Fully Convolutional Speech Recognition

Current state-of-the-art speech recognition systems build on recurrent n...

0 Neil Zeghidour, et al. ∙

research

∙ 12/09/2018

To Reverse the Gradient or Not: An Empirical Comparison of Adversarial and Multi-task Learning in Speech Recognition

Transcribed datasets typically contain speaker identity for each instanc...

14 Yossi Adi, et al. ∙

research

∙ 11/30/2018

Forward Modeling for Partial Observation Strategy Games - A StarCraft Defogger

We formulate the problem of defogging as state estimation and future sta...

0 Gabriel Synnaeve, et al. ∙

research

∙ 11/21/2018

High-Level Strategy Selection under Partial Observability in StarCraft: Brood War

We consider the problem of high-level strategy selection in the adversar...

2 Jonas Gehring, et al. ∙

research

∙ 10/23/2018

SING: Symbol-to-Instrument Neural Generator

Recent progress in deep learning for audio synthesis opens the way to mo...

0 Alexandre Défossez, et al. ∙

research

∙ 06/19/2018

Canonical Tensor Decomposition for Knowledge Base Completion

The problem of Knowledge Base Completion can be framed as a 3rd-order bi...

0 Timothée Lacroix, et al. ∙

research

∙ 06/19/2018

End-to-End Speech Recognition From the Raw Waveform

State-of-the-art speech recognition systems rely on fixed, hand-crafted ...

0 Neil Zeghidour, et al. ∙

research

∙ 05/28/2018

Value Propagation Networks

We present Value Propagation (VProp), a parameter-efficient differentiab...

0 Nantas Nardelli, et al. ∙

research

∙ 11/03/2017

Learning Filterbanks from Raw Speech for Phone Recognition

We train a bank of complex filters that operates on the raw waveform and...

0 Neil Zeghidour, et al. ∙

research

∙ 06/01/2017

Fader Networks: Manipulating Images by Sliding Attributes

This paper introduces a new encoder-decoder architecture that is trained...

0 Guillaume Lample, et al. ∙

research

∙ 04/28/2017

Parseval Networks: Improving Robustness to Adversarial Examples

We introduce Parseval networks, a form of deep neural networks in which ...

0 Moustapha Cisse, et al. ∙

research

∙ 12/13/2016

Improving Neural Language Models with a Continuous Cache

We propose an extension to neural network language models to adapt their...

0 Edouard Grave, et al. ∙

research

∙ 11/01/2016

TorchCraft: a Library for Machine Learning Research on Real-Time Strategy Games

We present TorchCraft, a library that enables deep learning research on ...

0 Gabriel Synnaeve, et al. ∙

research

∙ 09/21/2016

How should we evaluate supervised hashing?

Hashing produces compact representations for documents, to perform tasks...

0 Alexandre Sablayrolles, et al. ∙

research

∙ 09/10/2016

Episodic Exploration for Deep Deterministic Policies: An Application to StarCraft Micromanagement Tasks

We consider scenarios from the real-time strategy game StarCraft as new ...

0 Nicolas Usunier, et al. ∙

research

∙ 06/02/2015

Combining Two And Three-Way Embeddings Models for Link Prediction in Knowledge Bases

This paper tackles the problem of endogenous link prediction for Knowled...

0 Alberto García-Durán, et al. ∙

research

∙ 12/08/2012

An Empirical Comparison of V-fold Penalisation and Cross Validation for Model Selection in Distribution-Free Regression

Model selection is a crucial issue in machine-learning and a wide variet...

0 Charanpal Dhanjal, et al. ∙

Nicolas Usunier

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