Ralaivola, Liva

23 publications

ICLR 2024 Federated Wasserstein Distance Alain Rakotomamonjy, Kimia Nadjahi, Liva Ralaivola

TMLR 2024 Personalised Federated Learning on Heterogeneous Feature Spaces Alain Rakotomamonjy, Maxime Vono, Hamlet Jesse Medina Ruiz, Liva Ralaivola

ICML 2023 Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances Ruben Ohana, Kimia Nadjahi, Alain Rakotomamonjy, Liva Ralaivola

NeurIPS 2021 Photonic Differential Privacy with Direct Feedback Alignment Ruben Ohana, Hamlet Medina, Julien Launay, Alessandro Cappelli, Iacopo Poli, Liva Ralaivola, Alain Rakotomamonjy

MLJ 2021 QuicK-Means: Accelerating Inference for K-Means by Learning Fast Transforms Luc Giffon, Valentin Emiya, Hachem Kadri, Liva Ralaivola

NeurIPS 2017 Bandits Dueling on Partially Ordered Sets Julien Audiffren, Liva Ralaivola

NeurIPS 2015 Cornering Stationary and Restless Mixing Bandits with Remix-UCB Julien Audiffren, Liva Ralaivola

ICML 2015 Entropy-Based Concentration Inequalities for Dependent Variables Liva Ralaivola, Massih-Reza Amini

MLJ 2015 Unconfused Ultraconservative Multiclass Algorithms Ugo Louche, Liva Ralaivola

ACML 2013 Unconfused Ultraconservative Multiclass Algorithms Ugo Louche, Liva Ralaivola

NeurIPS 2012 Confusion-Based Online Learning and a Passive-Aggressive Scheme Liva Ralaivola

ICML 2012 PAC-Bayesian Generalization Bound on Confusion Matrix for Multi-Class Classification Emilie Morvant, Sokol Koço, Liva Ralaivola

CVPR 2011 MKPM: A Multiclass Extension to the Kernel Projection Machine Sylvain Takerkart, Liva Ralaivola

ICML 2011 Stochastic Low-Rank Kernel Learning for Regression Pierre Machart, Thomas Peel, Sandrine Anthoine, Liva Ralaivola, Hervé Glotin

JMLR 2010 Chromatic PAC-Bayes Bounds for Non-IID Data: Applications to Ranking and Stationary -Mixing Processes Liva Ralaivola, Marie Szafranski, Guillaume Stempfel

NeurIPS 2010 Empirical Bernstein Inequalities for U-Statistics Thomas Peel, Sandrine Anthoine, Liva Ralaivola

AISTATS 2009 Chromatic PAC-Bayes Bounds for Non-IID Data Liva Ralaivola, Marie Szafranski, Guillaume Stempfel

ICML 2009 Grammatical Inference as a Principal Component Analysis Problem Raphaël Bailly, François Denis, Liva Ralaivola

ICML 2009 Multiple Indefinite Kernel Learning with Mixed Norm Regularization Matthieu Kowalski, Marie Szafranski, Liva Ralaivola

ALT 2007 Learning Kernel Perceptrons on Noisy Data Using Random Projections Guillaume Stempfel, Liva Ralaivola

ICML 2006 CN = CPCN Liva Ralaivola, François Denis, Christophe Nicolas Magnan

ICML 2006 Efficient Learning of Naive Bayes Classifiers Under Class-Conditional Classification Noise François Denis, Christophe Nicolas Magnan, Liva Ralaivola

NeurIPS 2003 Dynamical Modeling with Kernels for Nonlinear Time Series Prediction Liva Ralaivola, Florence d'Alché-Buc