Inria

∙ Rocquencourt , France ∙ 0 followers

It was created under the name Institut de recherche en informatique et en automatique in 1967 at Rocquencourt near Paris, part of Plan Calcul.

Featured Researchers

Francis Bach
104 publications
Ji Liu
68 publications
Cordelia Schmid
67 publications
Remi Munos
54 publications
Julien Mairal
45 publications
Alexandre Gramfort
44 publications
Fabrice Rossi
37 publications
Gaël Varoquaux
36 publications
Radu Horaud
35 publications
Mark Schmidt
35 publications
Mohammad Ghavamzadeh
35 publications

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. ...
12/17/2019 ∙ by Julien Mairal, et al. ∙ 39 ∙ share

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

Annotating videos is cumbersome, expensive and not scalable. Yet, many s...
12/13/2019 ∙ by Antoine Miech, et al. ∙ 35 ∙ share

read it
Kernel-Based Ensemble Learning in Python

We propose a new supervised learning algorithm, for classification and r...
12/17/2019 ∙ by Benjamin Guedj, et al. ∙ 35 ∙ share

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

Interpretable explanations for recommender systems and other machine lea...
11/19/2019 ∙ by Azin Ghazimatin, et al. ∙ 28 ∙ share

read it
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)...
10/11/2019 ∙ by E. Baspinar, et al. ∙ 26 ∙ share

read it
On Fast Leverage Score Sampling and Optimal Learning

Leverage score sampling provides an appealing way to perform approximate...
10/31/2018 ∙ by Alessandro Rudi, et al. ∙ 24 ∙ share

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

The AutoML task consists of selecting the proper algorithm in a machine ...
06/01/2019 ∙ by Herilalaina Rakotoarison, et al. ∙ 22 ∙ share

read it
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...
11/08/2018 ∙ by Qiao Zheng, et al. ∙ 18 ∙ share

read it
A Generative 3D Facial Model by Adversarial Training

We consider data-driven generative models for the 3D face, and focus in ...
02/10/2019 ∙ by Victoria Fernandez Abrevaya, et al. ∙ 18 ∙ share

read it
High-Dimensional Control Using Generalized Auxiliary Tasks

A long-standing challenge in reinforcement learning is the design of fun...
09/26/2019 ∙ by Yannis Flet-Berliac, et al. ∙ 17 ∙ share

read it
Multi-Domain Adversarial Learning

Multi-domain learning (MDL) aims at obtaining a model with minimal avera...
03/21/2019 ∙ by Alice Schoenauer-Sebag, et al. ∙ 14 ∙ share

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

Autonomous reinforcement learning agents, like children, do not have acc...
11/08/2019 ∙ by Nicolas Lair, et al. ∙ 12 ∙ share

read it
Elastic registration based on compliance analysis and biomechanical graph matching

An automatic elastic registration method suited for vascularized organs ...
12/13/2019 ∙ by Jaime Garcia Guevara, et al. ∙ 12 ∙ share

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

The most data-efficient algorithms for reinforcement learning in robotic...
06/25/2018 ∙ by Rituraj Kaushik, et al. ∙ 10 ∙ share

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

In this paper, we propose and study a Nyström based approach to efficien...
07/11/2019 ∙ by Nicholas Sterge, et al. ∙ 10 ∙ share

read it
Recurrent Kernel Networks

Substring kernels are classical tools for representing biological sequen...
06/07/2019 ∙ by Dexiong Chen, et al. ∙ 9 ∙ share

read it
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...
05/24/2018 ∙ by Lenaïc Chizat, et al. ∙ 8 ∙ share

read it
Stable safe screening and structured dictionaries for faster ℓ_1 regularization

In this paper, we propose a way to combine two acceleration techniques f...
12/17/2018 ∙ by Cassio Dantas, et al. ∙ 8 ∙ share

read it
Efficient Topological Layer based on Persistent Landscapes

We propose a novel topological layer for general deep learning models ba...
02/07/2020 ∙ by Kwangho Kim, et al. ∙ 7 ∙ share

read it
Perspective-Aware CNN For Crowd Counting

Crowd counting is the task of estimating pedestrian numbers in crowd ima...
07/05/2018 ∙ by Miaojing Shi, et al. ∙ 6 ∙ share

read it
Context-adaptive neural network based prediction for image compression

This paper describes a set of neural network architectures, called Predi...
07/17/2018 ∙ by Thierry Dumas, et al. ∙ 6 ∙ share

read it
Learning to Localize and Align Fine-Grained Actions to Sparse Instructions

Automatic generation of textual video descriptions that are time-aligned...
09/22/2018 ∙ by Meera Hahn, et al. ∙ 6 ∙ share

read it
Pseudo-Bayesian Learning with Kernel Fourier Transform as Prior

We revisit Rahimi and Recht (2007)'s kernel random Fourier features (RFF...
10/30/2018 ∙ by Gaël Letarte, et al. ∙ 6 ∙ share

read it
SkeleMotion: A New Representation of Skeleton Joint Sequences Based on Motion Information for 3D Action Recognition

Due to the availability of large-scale skeleton datasets, 3D human actio...
07/30/2019 ∙ by Carlos Caetano, et al. ∙ 6 ∙ share

read it
Online k-means Clustering

We study the problem of online clustering where a clustering algorithm h...
09/15/2019 ∙ by Vincent Cohen-Addad, et al. ∙ 6 ∙ share

read it
Fast shared response model for fMRI data

The shared response model provides a simple but effective framework toan...
09/27/2019 ∙ by Hugo Richard, et al. ∙ 6 ∙ share

read it
3D Surface Reconstruction from Voxel-based Lidar Data

To achieve fully autonomous navigation, vehicles need to compute an accu...
06/25/2019 ∙ by Luis Roldao, et al. ∙ 5 ∙ share

read it
Learning a Behavioral Repertoire from Demonstrations

Imitation Learning (IL) is a machine learning approach to learn a policy...
07/05/2019 ∙ by Niels Justesen, et al. ∙ 5 ∙ share

read it
Skeleton Image Representation for 3D Action Recognition based on Tree Structure and Reference Joints

In the last years, the computer vision research community has studied on...
09/11/2019 ∙ by Carlos Caetano, et al. ∙ 5 ∙ share

read it
Modeling Spatio-Temporal Human Track Structure for Action Localization

This paper addresses spatio-temporal localization of human actions in vi...
06/28/2018 ∙ by Guilhem Chéron, et al. ∙ 4 ∙ share

read it
Sparse and Dense Data with CNNs: Depth Completion and Semantic Segmentation

Convolutional neural networks are designed for dense data, but vision da...
08/02/2018 ∙ by Maximilian Jaritz, et al. ∙ 4 ∙ share

read it
Massively scalable Sinkhorn distances via the Nyström method

The Sinkhorn distance, a variant of the Wasserstein distance with entrop...
12/12/2018 ∙ by Jason Altschuler, et al. ∙ 4 ∙ share

read it
A Universal Algorithm for Variational Inequalities Adaptive to Smoothness and Noise

We consider variational inequalities coming from monotone operators, a s...
02/05/2019 ∙ by Francis Bach, et al. ∙ 4 ∙ share

read it
Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret

Gaussian processes (GP) are a popular Bayesian approach for the optimiza...
03/13/2019 ∙ by Daniele Calandriello, et al. ∙ 4 ∙ share

read it
On the Inductive Bias of Neural Tangent Kernels

State-of-the-art neural networks are heavily over-parameterized, making ...
05/29/2019 ∙ by Alberto Bietti, et al. ∙ 4 ∙ share

read it
Effective Rotation-invariant Point CNN with Spherical Harmonics kernels

We present a novel rotation invariant architecture operating directly on...
06/27/2019 ∙ by Adrien Poulenard, et al. ∙ 4 ∙ share

read it
CAMUS: A Framework to Build Formal Specifications for Deep Perception Systems Using Simulators

The topic of provable deep neural network robustness has raised consider...
11/25/2019 ∙ by Julien Girard-Satabin, et al. ∙ 4 ∙ share

read it
Revisiting Non Local Sparse Models for Image Restoration

We propose a differentiable algorithm for image restoration inspired by ...
12/05/2019 ∙ by Bruno Lecouat, et al. ∙ 4 ∙ share

read it
Encoding high-cardinality string categorical variables

Statistical analysis usually requires a vector representation of categor...
07/03/2019 ∙ by Patricio Cerda, et al. ∙ 3 ∙ share

read it
3D Reconstruction of Deformable Revolving Object under Heavy Hand Interaction

We reconstruct 3D deformable object through time, in the context of a li...
08/05/2019 ∙ by Raoul de Charette, et al. ∙ 3 ∙ share

read it
DensePose: Dense Human Pose Estimation In The Wild

In this work, we establish dense correspondences between RGB image and a...
02/01/2018 ∙ by Rıza Alp Güler, et al. ∙ 2 ∙ share

read it
A Comprehensive Analysis of Deep Regression

Deep learning revolutionized data science, and recently, its popularity ...
03/22/2018 ∙ by Stéphane Lathuilière, et al. ∙ 2 ∙ share

read it
Learning with SGD and Random Features

Sketching and stochastic gradient methods are arguably the most common t...
07/17/2018 ∙ by Luigi Carratino, et al. ∙ 2 ∙ share

read it
Optimizing deep video representation to match brain activity

The comparison of observed brain activity with the statistics generated ...
09/07/2018 ∙ by Hugo Richard, et al. ∙ 2 ∙ share

read it
MULAN: A Blind and Off-Grid Method for Multichannel Echo Retrieval

This paper addresses the general problem of blind echo retrieval, i.e., ...
10/31/2018 ∙ by Helena Peic Tukuljac, et al. ∙ 2 ∙ share

read it
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks

We present a comprehensive study of multilayer neural networks with bina...
05/24/2019 ∙ by Gaël Letarte, et al. ∙ 2 ∙ share

read it
Intrinsically Motivated Exploration for Automated Discovery of Patterns in Morphogenetic Systems

Exploration is a cornerstone both for machine learning algorithms and fo...
08/19/2019 ∙ by Chris Reinke, et al. ∙ 2 ∙ share

read it
Learning Semantic Correspondence Exploiting an Object-level Prior

We address the problem of semantic correspondence, that is, establishing...
11/29/2019 ∙ by Junghyup Lee, et al. ∙ 2 ∙ share

read it
Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic Loss

Neural networks trained to minimize the logistic (a.k.a. cross-entropy) ...
02/11/2020 ∙ by Lenaïc Chizat, et al. ∙ 2 ∙ share

read it
Fast Decomposable Submodular Function Minimization using Constrained Total Variation

We consider the problem of minimizing the sum of submodular set function...
05/27/2019 ∙ by K. S. Sesh Kumar, et al. ∙ 1 ∙ share

read it