Ludovic Denoyer

research

∙ 08/28/2023

Policy Diversity for Cooperative Agents

Standard cooperative multi-agent reinforcement learning (MARL) methods a...

0 Mingxi Tan, et al. ∙

research

∙ 08/18/2023

Learning Computational Efficient Bots with Costly Features

Deep reinforcement learning (DRL) techniques have become increasingly us...

0 Anthony Kobanda, et al. ∙

research

∙ 11/18/2022

Building a Subspace of Policies for Scalable Continual Learning

The ability to continuously acquire new knowledge and skills is crucial ...

0 Jean-Baptiste Gaya, et al. ∙

research

∙ 09/27/2022

Regularized Soft Actor-Critic for Behavior Transfer Learning

Existing imitation learning methods mainly focus on making an agent effe...

0 Mingxi Tan, et al. ∙

research

∙ 05/31/2022

Interactive Query Clarification and Refinement via User Simulation

When users initiate search sessions, their queries are often unclear or ...

0 Pierre Erbacher, et al. ∙

research

∙ 03/21/2022

Temporal Abstractions-Augmented Temporally Contrastive Learning: An Alternative to the Laplacian in RL

In reinforcement learning, the graph Laplacian has proved to be a valuab...

0 Akram Erraqabi, et al. ∙

research

∙ 03/11/2022

Can I see an Example? Active Learning the Long Tail of Attributes and Relations

There has been significant progress in creating machine learning models ...

0 Tyler L. Hayes, et al. ∙

research

∙ 01/10/2022

State of the Art of User Simulation approaches for conversational information retrieval

Conversational Information Retrieval (CIR) is an emerging field of Infor...

0 Pierre Erbacher, et al. ∙

research

∙ 10/27/2021

Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching

Learning meaningful behaviors in the absence of reward is a difficult pr...

0 Pierre-Alexandre Kamienny, et al. ∙

research

∙ 10/15/2021

SaLinA: Sequential Learning of Agents

SaLinA is a simple library that makes implementing complex sequential le...

0 Ludovic Denoyer, et al. ∙

research

∙ 10/11/2021

Learning a subspace of policies for online adaptation in Reinforcement Learning

Deep Reinforcement Learning (RL) is mainly studied in a setting where th...

0 Jean-Baptiste Gaya, et al. ∙

research

∙ 06/17/2021

On Anytime Learning at Macroscale

Classical machine learning frameworks assume access to a possibly large ...

1 Lucas Caccia, et al. ∙

research

∙ 12/23/2020

Efficient Continual Learning with Modular Networks and Task-Driven Priors

Existing literature in Continual Learning (CL) has focused on overcoming...

0 Tom Véniat, et al. ∙

research

∙ 06/01/2020

Concept Matching for Low-Resource Classification

We propose a model to tackle classification tasks in the presence of ver...

7 Federico Errica, 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

∙ 09/11/2019

Learning Dynamic Author Representations with Temporal Language Models

Language models are at the heart of numerous works, notably in the text ...

2 Edouard Delasalles, et al. ∙

research

∙ 07/10/2019

Large Memory Layers with Product Keys

This paper introduces a structured memory which can be easily integrated...

0 Guillaume Lample, et al. ∙

research

∙ 06/24/2019

Binary Stochastic Representations for Large Multi-class Classification

Classification with a large number of classes is a key problem in machin...

2 Thomas Gerald, et al. ∙

research

∙ 06/12/2019

Unsupervised Question Answering by Cloze Translation

Obtaining training data for Question Answering (QA) is time-consuming an...

9 Patrick Lewis, et al. ∙

research

∙ 05/28/2019

EDUCE: Explaining model Decisions through Unsupervised Concepts Extraction

With the advent of deep neural networks, some research focuses towards u...

1 Diane Bouchacourt, et al. ∙

research

∙ 05/27/2019

Unsupervised Object Segmentation by Redrawing

Object segmentation is a crucial problem that is usually solved by using...

6 Mickaël Chen, et al. ∙

research

∙ 11/16/2018

Stochastic Adaptive Neural Architecture Search for Keyword Spotting

The problem of keyword spotting i.e. identifying keywords in a real-time...

8 Tom Véniat, et al. ∙

research

∙ 11/01/2018

Multiple-Attribute Text Style Transfer

The dominant approach to unsupervised "style transfer" in text is based ...

0 Sandeep Subramanian, et al. ∙

research

∙ 08/29/2018

A Reinforcement Learning-driven Translation Model for Search-Oriented Conversational Systems

Search-oriented conversational systems rely on information needs express...

0 Wafa Aissa, et al. ∙

research

∙ 04/23/2018

Spatio-Temporal Neural Networks for Space-Time Series Forecasting and Relations Discovery

We introduce a dynamical spatio-temporal model formalized as a recurrent...

0 Ali Ziat, et al. ∙

research

∙ 04/20/2018

Phrase-Based & Neural Unsupervised Machine Translation

Machine translation systems achieve near human-level performance on some...

0 Guillaume Lample, et al. ∙

research

∙ 11/01/2017

Multi-View Data Generation Without View Supervision

The development of high-dimensional generative models has recently gaine...

0 Mickaël Chen, et al. ∙

research

∙ 10/31/2017

Unsupervised Machine Translation Using Monolingual Corpora Only

Machine translation has recently achieved impressive performance thanks ...

0 Guillaume Lample, et al. ∙

research

∙ 10/11/2017

Word Translation Without Parallel Data

State-of-the-art methods for learning cross-lingual word embeddings have...

0 Alexis Conneau, 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

∙ 11/21/2016

Options Discovery with Budgeted Reinforcement Learning

We consider the problem of learning hierarchical policies for Reinforcem...

0 Aurélia Léon, et al. ∙

research

∙ 12/20/2013

Sequentially Generated Instance-Dependent Image Representations for Classification

In this paper, we investigate a new framework for image classification t...

0 Gabriel Dulac-Arnold, et al. ∙

research

∙ 04/11/2012

Probabilistic Latent Tensor Factorization Model for Link Pattern Prediction in Multi-relational Networks

This paper aims at the problem of link pattern prediction in collections...

0 Sheng Gao, et al. ∙

research

∙ 04/11/2012

Modeling Relational Data via Latent Factor Blockmodel

In this paper we address the problem of modeling relational data, which ...

0 Sheng Gao, et al. ∙

research

∙ 02/29/2012

Fast Reinforcement Learning with Large Action Sets using Error-Correcting Output Codes for MDP Factorization

The use of Reinforcement Learning in real-world scenarios is strongly li...

0 Gabriel Dulac-Arnold, et al. ∙

research

∙ 08/29/2011

Datum-Wise Classification: A Sequential Approach to Sparsity

We propose a novel classification technique whose aim is to select an ap...

0 Gabriel Dulac-Arnold, et al. ∙

research

∙ 07/07/2011

Text Classification: A Sequential Reading Approach

We propose to model the text classification process as a sequential deci...

0 Gabriel Dulac-Arnold, et al. ∙

Ludovic Denoyer

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