
Convolutional Kernel Networks for GraphStructured Data
We introduce a family of multilayer graph kernels and establish new link...
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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. ...
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EndtoEnd Learning of Visual Representations from Uncurated Instructional Videos
Annotating videos is cumbersome, expensive and not scalable. Yet, many s...
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KernelBased Ensemble Learning in Python
We propose a new supervised learning algorithm, for classification and r...
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Automatic Curriculum Learning For Deep RL: A Short Survey
Automatic Curriculum Learning (ACL) has become a cornerstone of recent s...
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PRINCE: Providerside Interpretability with Counterfactual Explanations in Recommender Systems
Interpretable explanations for recommender systems and other machine lea...
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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)...
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On Fast Leverage Score Sampling and Optimal Learning
Leverage score sampling provides an appealing way to perform approximate...
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DAugNet: Unsupervised, Multisource, Multitarget, and Lifelong Domain Adaptation for Semantic Segmentation of Satellite Images
The domain adaptation of satellite images has recently gained an increas...
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Automated Machine Learning with MonteCarlo Tree Search (Extended Version)
The AutoML task consists of selecting the proper algorithm in a machine ...
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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...
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A Generative 3D Facial Model by Adversarial Training
We consider datadriven generative models for the 3D face, and focus in ...
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Whittle index based Qlearning for restless bandits with average reward
A novel reinforcement learning algorithm is introduced for multiarmed re...
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HighDimensional Control Using Generalized Auxiliary Tasks
A longstanding challenge in reinforcement learning is the design of fun...
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MultiDomain Adversarial Learning
Multidomain learning (MDL) aims at obtaining a model with minimal avera...
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Stochastic Optimization for Regularized Wasserstein Estimators
Optimal transport is a foundational problem in optimization, that allows...
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Language Grounding through Social Interactions and CuriosityDriven MultiGoal Learning
Autonomous reinforcement learning agents, like children, do not have acc...
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Elastic registration based on compliance analysis and biomechanical graph matching
An automatic elastic registration method suited for vascularized organs ...
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Fast Online Adaptation in Robotics through MetaLearning Embeddings of Simulated Priors
Metalearning algorithms can accelerate the modelbased reinforcement le...
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Selecting Relevant Features from a Universal Representation for Fewshot Classification
Popular approaches for fewshot classification consist of first learning...
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StandardGAN: Multisource Domain Adaptation for Semantic Segmentation of Very High Resolution Satellite Images by Data Standardization
Domain adaptation for semantic segmentation has recently been actively s...
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Designing and Learning Trainable Priors with NonCooperative Games
We introduce a general framework for designing and learning neural netwo...
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Multiobjective Modelbased Policy Search for Dataefficient Learning with Sparse Rewards
The most dataefficient algorithms for reinforcement learning in robotic...
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Gain with no Pain: Efficient KernelPCA by Nyström Sampling
In this paper, we propose and study a Nyström based approach to efficien...
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Recurrent Kernel Networks
Substring kernels are classical tools for representing biological sequen...
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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...
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Stable safe screening and structured dictionaries for faster ℓ_1 regularization
In this paper, we propose a way to combine two acceleration techniques f...
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Gaussian Graphical Model exploration and selection in high dimension low sample size setting
Gaussian Graphical Models (GGM) are often used to describe the condition...
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Deep Sets for Generalization in RL
This paper investigates the idea of encoding objectcentered representat...
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Progressive growing of selforganized hierarchical representations for exploration
Designing agent that can autonomously discover and learn a diversity of ...
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Efficient Topological Layer based on Persistent Landscapes
We propose a novel topological layer for general deep learning models ba...
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The GeoLifeCLEF 2020 Dataset
Understanding the geographic distribution of species is a key concern in...
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PerspectiveAware CNN For Crowd Counting
Crowd counting is the task of estimating pedestrian numbers in crowd ima...
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Contextadaptive neural network based prediction for image compression
This paper describes a set of neural network architectures, called Predi...
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Learning to Localize and Align FineGrained Actions to Sparse Instructions
Automatic generation of textual video descriptions that are timealigned...
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PseudoBayesian Learning with Kernel Fourier Transform as Prior
We revisit Rahimi and Recht (2007)'s kernel random Fourier features (RFF...
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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...
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Online kmeans Clustering
We study the problem of online clustering where a clustering algorithm h...
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Fast shared response model for fMRI data
The shared response model provides a simple but effective framework toan...
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Automating Representation Discovery with MAPElites
The way solutions are represented, or encoded, is usually the result of ...
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Generalized Penalty for Circular Coordinate Representation
Topological Data Analysis (TDA) provides novel approaches that allow us ...
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VPN: Learning VideoPose Embedding for Activities of Daily Living
In this paper, we focus on the spatiotemporal aspect of recognizing Act...
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3D Surface Reconstruction from Voxelbased Lidar Data
To achieve fully autonomous navigation, vehicles need to compute an accu...
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Learning a Behavioral Repertoire from Demonstrations
Imitation Learning (IL) is a machine learning approach to learn a policy...
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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...
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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...
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Modeling SpatioTemporal Human Track Structure for Action Localization
This paper addresses spatiotemporal localization of human actions in vi...
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Sparse and Dense Data with CNNs: Depth Completion and Semantic Segmentation
Convolutional neural networks are designed for dense data, but vision da...
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Massively scalable Sinkhorn distances via the Nyström method
The Sinkhorn distance, a variant of the Wasserstein distance with entrop...
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A Universal Algorithm for Variational Inequalities Adaptive to Smoothness and Noise
We consider variational inequalities coming from monotone operators, a s...
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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.