
DistributionBased Invariant Deep Networks for Learning MetaFeatures
Recent advances in deep learning from probability distributions enable t...
read it

Variational AutoEncoder: not all failures are equal
We claim that a source of severe failures for Variational AutoEncoders ...
read it

From abstract items to latent spaces to observed data and back: Compositional Variational AutoEncoder
Conditional Generative Models are now acknowledged an essential tool in ...
read it

Towards AutoML in the presence of Drift: first results
Research progress in AutoML has lead to state of the art solutions that ...
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

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

New Losses for Generative Adversarial Learning
Generative Adversarial Networks (Goodfellow et al., 2014), a major break...
read it

SAM: Structural Agnostic Model, Causal Discovery and Penalized Adversarial Learning
We present the Structural Agnostic Model (SAM), a framework to estimate ...
read it

Causal Generative Neural Networks
We introduce CGNN, a framework to learn functional causal models as gene...
read it

Learning Functional Causal Models with Generative Neural Networks
We introduce a new approach to functional causal modeling from observati...
read it

Stochastic Gradient Descent: Going As Fast As Possible But Not Faster
When applied to training deep neural networks, stochastic gradient desce...
read it

Multidimensional signal approximation with sparse structured priors using split Bregman iterations
This paper addresses the structurallyconstrained sparse decomposition o...
read it

Maximum Likelihoodbased Online Adaptation of Hyperparameters in CMAES
The Covariance Matrix Adaptation Evolution Strategy (CMAES) is widely a...
read it

KLbased Control of the Learning Schedule for Surrogate BlackBox Optimization
This paper investigates the control of an ML component within the Covari...
read it

Sustainable Cooperative Coevolution with a MultiArmed Bandit
This paper proposes a selfadaptation mechanism to manage the resources ...
read it

Multidimensional sparse structured signal approximation using split Bregman iterations
The paper focuses on the sparse approximation of signals using overcompl...
read it

Alternative Restart Strategies for CMAES
This paper focuses on the restart strategy of CMAES on multimodal func...
read it

Blackbox optimization benchmarking of IPOPsaACMES and BIPOPsaACMES on the BBOB2012 noiseless testbed
In this paper, we study the performance of IPOPsaACMES and BIPOPsaACM...
read it

Blackbox optimization benchmarking of IPOPsaACMES on the BBOB2012 noisy testbed
In this paper, we study the performance of IPOPsaACMES, recently propo...
read it

SelfAdaptive SurrogateAssisted Covariance Matrix Adaptation Evolution Strategy
This paper presents a novel mechanism to adapt surrogateassisted popula...
read it

Scaling Analysis of Affinity Propagation
We analyze and exploit some scaling properties of the Affinity Propagati...
read it
Michèle Sebag
is this you? claim profile
Deputy director of Laboratoire de Recherche en Informatique, CNRS, UMR 8623, Head of Équipe AO  Laboratoire de Recherche en Informatique, Cohead (with Marc Schoenauer) of ÉquipeProjet TAO  INRIA Saclay  ÎledeFrance, Principal scientist CNRS (Directrice de recherche de 1ere classe)