
Convolutional Kernel Networks for GraphStructured Data
We introduce a family of multilayer graph kernels and establish new link...
read it

Cyanure: An OpenSource Toolbox for Empirical Risk Minimization for Python, C++, and soon more
Cyanure is an opensource C++ software package with a Python interface. ...
read it

EndtoEnd Learning of Visual Representations from Uncurated Instructional Videos
Annotating videos is cumbersome, expensive and not scalable. Yet, many s...
read it

KernelBased Ensemble Learning in Python
We propose a new supervised learning algorithm, for classification and r...
read it

Automatic Curriculum Learning For Deep RL: A Short Survey
Automatic Curriculum Learning (ACL) has become a cornerstone of recent s...
read it

PRINCE: Providerside Interpretability with Counterfactual Explanations in Recommender Systems
Interpretable explanations for recommender systems and other machine lea...
read it

A subRiemannian model of the visual cortex with frequency and phase
In this paper we present a novel model of the primary visual cortex (V1)...
read it

On Fast Leverage Score Sampling and Optimal Learning
Leverage score sampling provides an appealing way to perform approximate...
read it

Automated Machine Learning with MonteCarlo Tree Search (Extended Version)
The AutoML task consists of selecting the proper algorithm in a machine ...
read it

Explainable cardiac pathology classification on cine MRI with motion characterization by semisupervised learning of apparent flow
We propose a method to classify cardiac pathology based on a novel appro...
read it

A Generative 3D Facial Model by Adversarial Training
We consider datadriven generative models for the 3D face, and focus in ...
read it

HighDimensional Control Using Generalized Auxiliary Tasks
A longstanding challenge in reinforcement learning is the design of fun...
read it

MultiDomain Adversarial Learning
Multidomain learning (MDL) aims at obtaining a model with minimal avera...
read it

Stochastic Optimization for Regularized Wasserstein Estimators
Optimal transport is a foundational problem in optimization, that allows...
read it

Language Grounding through Social Interactions and CuriosityDriven MultiGoal Learning
Autonomous reinforcement learning agents, like children, do not have acc...
read it

Elastic registration based on compliance analysis and biomechanical graph matching
An automatic elastic registration method suited for vascularized organs ...
read it

Fast Online Adaptation in Robotics through MetaLearning Embeddings of Simulated Priors
Metalearning algorithms can accelerate the modelbased reinforcement le...
read it

Selecting Relevant Features from a Universal Representation for Fewshot Classification
Popular approaches for fewshot classification consist of first learning...
read it

Multiobjective Modelbased Policy Search for Dataefficient Learning with Sparse Rewards
The most dataefficient algorithms for reinforcement learning in robotic...
read it

Gain with no Pain: Efficient KernelPCA by Nyström Sampling
In this paper, we propose and study a Nyström based approach to efficien...
read it

Recurrent Kernel Networks
Substring kernels are classical tools for representing biological sequen...
read it

On the Global Convergence of Gradient Descent for Overparameterized Models using Optimal Transport
Many tasks in machine learning and signal processing can be solved by mi...
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...
read it

Gaussian Graphical Model exploration and selection in high dimension low sample size setting
Gaussian Graphical Models (GGM) are often used to describe the condition...
read it

Deep Sets for Generalization in RL
This paper investigates the idea of encoding objectcentered representat...
read it

Efficient Topological Layer based on Persistent Landscapes
We propose a novel topological layer for general deep learning models ba...
read it

PerspectiveAware CNN For Crowd Counting
Crowd counting is the task of estimating pedestrian numbers in crowd ima...
read it

Contextadaptive neural network based prediction for image compression
This paper describes a set of neural network architectures, called Predi...
read it

Learning to Localize and Align FineGrained Actions to Sparse Instructions
Automatic generation of textual video descriptions that are timealigned...
read it

PseudoBayesian Learning with Kernel Fourier Transform as Prior
We revisit Rahimi and Recht (2007)'s kernel random Fourier features (RFF...
read it

SkeleMotion: A New Representation of Skeleton Joint Sequences Based on Motion Information for 3D Action Recognition
Due to the availability of largescale skeleton datasets, 3D human actio...
read it

Online kmeans Clustering
We study the problem of online clustering where a clustering algorithm h...
read it

Fast shared response model for fMRI data
The shared response model provides a simple but effective framework toan...
read it

Automating Representation Discovery with MAPElites
The way solutions are represented, or encoded, is usually the result of ...
read it

3D Surface Reconstruction from Voxelbased Lidar Data
To achieve fully autonomous navigation, vehicles need to compute an accu...
read it

Learning a Behavioral Repertoire from Demonstrations
Imitation Learning (IL) is a machine learning approach to learn a policy...
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...
read it

Experimental Comparison of Semiparametric, Parametric, and Machine Learning Models for TimetoEvent Analysis Through the Concordance Index
In this paper, we make an experimental comparison of semiparametric (Co...
read it

Modeling SpatioTemporal Human Track Structure for Action Localization
This paper addresses spatiotemporal localization of human actions in vi...
read it

Sparse and Dense Data with CNNs: Depth Completion and Semantic Segmentation
Convolutional neural networks are designed for dense data, but vision da...
read it

Massively scalable Sinkhorn distances via the Nyström method
The Sinkhorn distance, a variant of the Wasserstein distance with entrop...
read it

A Universal Algorithm for Variational Inequalities Adaptive to Smoothness and Noise
We consider variational inequalities coming from monotone operators, a s...
read it

Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret
Gaussian processes (GP) are a popular Bayesian approach for the optimiza...
read it

On the Inductive Bias of Neural Tangent Kernels
Stateoftheart neural networks are heavily overparameterized, making ...
read it

Effective Rotationinvariant Point CNN with Spherical Harmonics kernels
We present a novel rotation invariant architecture operating directly on...
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...
read it

Revisiting Non Local Sparse Models for Image Restoration
We propose a differentiable algorithm for image restoration inspired by ...
read it

Encoding highcardinality string categorical variables
Statistical analysis usually requires a vector representation of categor...
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...
read it

DensePose: Dense Human Pose Estimation In The Wild
In this work, we establish dense correspondences between RGB image and a...
read it
Inria
It was created under the name Institut de recherche en informatique et en automatique in 1967 at Rocquencourt near Paris, part of Plan Calcul.