b'Inria'

research

∙ 07/31/2020

Uncovering the structure of clinical EEG signals with self-supervised learning

Objective. Supervised learning paradigms are often limited by the amount...

Hubert Banville, et al. ∙

research

∙ 03/28/2021

TransCenter: Transformers with Dense Queries for Multiple-Object Tracking

Transformer networks have proven extremely powerful for a wide variety o...

Yihong Xu, et al. ∙

research

∙ 03/11/2020

Convolutional Kernel Networks for Graph-Structured Data

We introduce a family of multilayer graph kernels and establish new link...

Dexiong Chen, et al. ∙

research

∙ 08/20/2021

Airbert: In-domain Pretraining for Vision-and-Language Navigation

Vision-and-language navigation (VLN) aims to enable embodied agents to n...

Pierre-Louis Guhur, et al. ∙

research

∙ 03/17/2021

Infinite-Horizon Offline Reinforcement Learning with Linear Function Approximation: Curse of Dimensionality and Algorithm

In this paper, we investigate the sample complexity of policy evaluation...

Lin Chen, et al. ∙

research

∙ 12/17/2019

Cyanure: An Open-Source Toolbox for Empirical Risk Minimization for Python, C++, and soon more

Cyanure is an open-source C++ software package with a Python interface. ...

Julien Mairal, et al. ∙

research

∙ 03/12/2021

3D Semantic Scene Completion: a Survey

Semantic Scene Completion (SSC) aims to jointly estimate the complete ge...

Luis Roldao, et al. ∙

research

∙ 12/01/2021

MonoScene: Monocular 3D Semantic Scene Completion

MonoScene proposes a 3D Semantic Scene Completion (SSC) framework, where...

Anh-Quan Cao, et al. ∙

research

∙ 12/13/2019

End-to-End Learning of Visual Representations from Uncurated Instructional Videos

Annotating videos is cumbersome, expensive and not scalable. Yet, many s...

Antoine Miech, et al. ∙

research

∙ 12/17/2019

Kernel-Based Ensemble Learning in Python

We propose a new supervised learning algorithm, for classification and r...

Benjamin Guedj, et al. ∙

research

∙ 04/21/2022

OSSO: Obtaining Skeletal Shape from Outside

We address the problem of inferring the anatomic skeleton of a person, i...

Marilyn Keller, et al. ∙

research

∙ 03/10/2020

Automatic Curriculum Learning For Deep RL: A Short Survey

Automatic Curriculum Learning (ACL) has become a cornerstone of recent s...

Rémy Portelas, et al. ∙

research

∙ 02/11/2022

On change of measure inequalities for f-divergences

We propose new change of measure inequalities based on f-divergences (of...

Antoine Picard-Weibel, et al. ∙

research

∙ 11/19/2019

PRINCE: Provider-side Interpretability with Counterfactual Explanations in Recommender Systems

Interpretable explanations for recommender systems and other machine lea...

Azin Ghazimatin, et al. ∙

research

∙ 07/31/2021

DCT2net: an interpretable shallow CNN for image denoising

This work tackles the issue of noise removal from images, focusing on th...

Sébastien Herbreteau, et al. ∙

research

∙ 10/11/2019

A sub-Riemannian model of the visual cortex with frequency and phase

In this paper we present a novel model of the primary visual cortex (V1)...

E. Baspinar, et al. ∙

research

∙ 10/31/2018

On Fast Leverage Score Sampling and Optimal Learning

Leverage score sampling provides an appealing way to perform approximate...

Alessandro Rudi, et al. ∙

research

∙ 05/13/2020

DAugNet: Unsupervised, Multi-source, Multi-target, and Life-long Domain Adaptation for Semantic Segmentation of Satellite Images

The domain adaptation of satellite images has recently gained an increas...

Onur Tasar, et al. ∙

research

∙ 12/23/2021

DILF-EN framework for Class-Incremental Learning

Deep learning models suffer from catastrophic forgetting of the classes ...

Mohammed Asad Karim, et al. ∙

research

∙ 01/12/2022

Beyond the Visible: A Survey on Cross-spectral Face Recognition

Cross-spectral face recognition (CFR) is aimed at recognizing individual...

David Anghelone, et al. ∙

research

∙ 06/01/2019

Automated Machine Learning with Monte-Carlo Tree Search (Extended Version)

The AutoML task consists of selecting the proper algorithm in a machine ...

Herilalaina Rakotoarison, et al. ∙

research

∙ 11/08/2018

Explainable cardiac pathology classification on cine MRI with motion characterization by semi-supervised learning of apparent flow

We propose a method to classify cardiac pathology based on a novel appro...

Qiao Zheng, et al. ∙

research

∙ 02/10/2019

A Generative 3D Facial Model by Adversarial Training

We consider data-driven generative models for the 3D face, and focus in ...

Victoria Fernandez Abrevaya, et al. ∙

research

∙ 04/29/2020

Whittle index based Q-learning for restless bandits with average reward

A novel reinforcement learning algorithm is introduced for multiarmed re...

Konstantin Avrachenkov, et al. ∙

research

∙ 09/26/2019

High-Dimensional Control Using Generalized Auxiliary Tasks

A long-standing challenge in reinforcement learning is the design of fun...

Yannis Flet-Berliac, et al. ∙

research

∙ 03/21/2019

Multi-Domain Adversarial Learning

Multi-domain learning (MDL) aims at obtaining a model with minimal avera...

Alice Schoenauer-Sebag, et al. ∙

research

∙ 12/20/2021

Interpretable Preference-based Reinforcement Learning with Tree-Structured Reward Functions

The potential of reinforcement learning (RL) to deliver aligned and perf...

Tom Bewley, et al. ∙

research

∙ 02/20/2020

Stochastic Optimization for Regularized Wasserstein Estimators

Optimal transport is a foundational problem in optimization, that allows...

Marin Ballu, et al. ∙

research

∙ 03/17/2022

Latent Image Animator: Learning to Animate Images via Latent Space Navigation

Due to the remarkable progress of deep generative models, animating imag...

Yaohui Wang, et al. ∙

research

∙ 05/03/2022

Neural Language Taskonomy: Which NLP Tasks are the most Predictive of fMRI Brain Activity?

Several popular Transformer based language models have been found to be ...

Subba Reddy Oota, et al. ∙

research

∙ 11/08/2019

Language Grounding through Social Interactions and Curiosity-Driven Multi-Goal Learning

Autonomous reinforcement learning agents, like children, do not have acc...

Nicolas Lair, et al. ∙

research

∙ 12/13/2019

Elastic registration based on compliance analysis and biomechanical graph matching

An automatic elastic registration method suited for vascularized organs ...

Jaime Garcia Guevara, et al. ∙

research

∙ 03/10/2020

Fast Online Adaptation in Robotics through Meta-Learning Embeddings of Simulated Priors

Meta-learning algorithms can accelerate the model-based reinforcement le...

Rituraj Kaushik, et al. ∙

research

∙ 03/20/2020

Selecting Relevant Features from a Universal Representation for Few-shot Classification

Popular approaches for few-shot classification consist of first learning...

Nikita Dvornik, et al. ∙

research

∙ 12/18/2020

Upper and Lower Bounds on the Performance of Kernel PCA

Principal Component Analysis (PCA) is a popular method for dimension red...

Maxime Haddouche, et al. ∙

research

∙ 09/17/2021

What we see and What we don't see: Imputing Occluded Crowd Structures from Robot Sensing

We consider the navigation of mobile robots in crowded environments, for...

Javad Amirian, et al. ∙

research

∙ 05/01/2022

Differentially Private Multivariate Time Series Forecasting of Aggregated Human Mobility With Deep Learning: Input or Gradient Perturbation?

This paper investigates the problem of forecasting multivariate aggregat...

Héber H. Arcolezi, et al. ∙

research

∙ 04/14/2020

StandardGAN: Multi-source Domain Adaptation for Semantic Segmentation of Very High Resolution Satellite Images by Data Standardization

Domain adaptation for semantic segmentation has recently been actively s...

Onur Tasar, et al. ∙

research

∙ 06/26/2020

Designing and Learning Trainable Priors with Non-Cooperative Games

We introduce a general framework for designing and learning neural netwo...

Bruno Lecouat, et al. ∙

research

∙ 07/13/2022

Goal-Oriented Sensitivity Analysis of Hyperparameters in Deep Learning

Tackling new machine learning problems with neural networks always means...

Paul Novello, et al. ∙

research

∙ 06/25/2018

Multi-objective Model-based Policy Search for Data-efficient Learning with Sparse Rewards

The most data-efficient algorithms for reinforcement learning in robotic...

Rituraj Kaushik, et al. ∙

research

∙ 07/11/2019

Gain with no Pain: Efficient Kernel-PCA by Nyström Sampling

In this paper, we propose and study a Nyström based approach to efficien...

Nicholas Sterge, et al. ∙

research

∙ 07/06/2020

VPN: Learning Video-Pose Embedding for Activities of Daily Living

In this paper, we focus on the spatio-temporal aspect of recognizing Act...

Srijan Das, et al. ∙

research

∙ 07/21/2020

Multi-modal Transformer for Video Retrieval

The task of retrieving video content relevant to natural language querie...

Valentin Gabeur, et al. ∙

research

∙ 11/05/2021

Frugal Machine Learning

Machine learning, already at the core of increasingly many systems and a...

Mikhail Evchenko, et al. ∙

research

∙ 06/07/2019

Recurrent Kernel Networks

Substring kernels are classical tools for representing biological sequen...

Dexiong Chen, et al. ∙

research

∙ 10/18/2021

Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits

In the fixed budget thresholding bandit problem, an algorithm sequential...

Reda Ouhamma, et al. ∙

research

∙ 06/22/2022

DP-Parse: Finding Word Boundaries from Raw Speech with an Instance Lexicon

Finding word boundaries in continuous speech is challenging as there is ...

Robin Algayres, et al. ∙

research

∙ 05/24/2018

On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport

Many tasks in machine learning and signal processing can be solved by mi...

Lenaïc Chizat, et al. ∙

research

∙ 12/17/2018

Stable safe screening and structured dictionaries for faster ℓ_1 regularization

In this paper, we propose a way to combine two acceleration techniques f...

Cassio Dantas, et al. ∙

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