Liva Ralaivola

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 25

Top Topics

Partially Ordered

Regression Coefficients

Online Learning

Constrained Optimization

Top Venues

Publications

Alain Rakotomamonjy, Maxime Vono, Hamlet Jesse Medina Ruiz, Liva Ralaivola
Personalised Federated Learning On Heterogeneous Feature Spaces. Trans. Mach. Learn. Res. 2024 (2024)
Alain Rakotomamonjy, Kimia Nadjahi, Liva Ralaivola
Federated Wasserstein Distance. ICLR (2024)
Alain Rakotomamonjy, Kimia Nadjahi, Liva Ralaivola
Federated Wasserstein Distance. CoRR (2023)
Alain Rakotomamonjy, Maxime Vono, Hamlet Jesse Medina Ruiz, Liva Ralaivola
Personalised Federated Learning On Heterogeneous Feature Spaces. CoRR (2023)
Ruben Ohana, Kimia Nadjahi, Alain Rakotomamonjy, Liva Ralaivola
Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances. ICML (2023)
Ruben Ohana, Kimia Nadjahi, Alain Rakotomamonjy, Liva Ralaivola
Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances. CoRR (2022)
Farah Cherfaoui, Hachem Kadri, Liva Ralaivola
Scalable Ridge Leverage Score Sampling for the Nyström Method. ICASSP (2022)
Alain Rakotomamonjy, Liva Ralaivola
Differentially Private Sliced Wasserstein Distance. ICML (2021)
Ruben Ohana, Hamlet Jesse Medina Ruiz, Julien Launay, Alessandro Cappelli, Iacopo Poli, Liva Ralaivola, Alain Rakotomamonjy
Photonic Differential Privacy with Direct Feedback Alignment. NeurIPS (2021)
Alain Rakotomamonjy, Liva Ralaivola
Differentially Private Sliced Wasserstein Distance. CoRR (2021)
Luc Giffon, Valentin Emiya, Hachem Kadri, Liva Ralaivola
QuicK-means: accelerating inference for K-means by learning fast transforms. Mach. Learn. 110 (5) (2021)
Ruben Ohana, Hamlet J. Medina Ruiz, Julien Launay, Alessandro Cappelli, Iacopo Poli, Liva Ralaivola, Alain Rakotomamonjy
Photonic Differential Privacy with Direct Feedback Alignment. CoRR (2021)
Hachem Kadri, Stéphane Ayache, Riikka Huusari, Alain Rakotomamonjy, Liva Ralaivola
Partial Trace Regression and Low-Rank Kraus Decomposition. ICML (2020)
Hachem Kadri, Stéphane Ayache, Riikka Huusari, Alain Rakotomamonjy, Liva Ralaivola
Partial Trace Regression and Low-Rank Kraus Decomposition. CoRR (2020)
Balthazar Casalé, Giuseppe Di Molfetta, Hachem Kadri, Liva Ralaivola
Quantum bandits. Quantum Mach. Intell. 2 (1) (2020)
Balthazar Casalé, Giuseppe Di Molfetta, Hachem Kadri, Liva Ralaivola
Quantum Bandits. CoRR (2020)
Luc Giffon, Valentin Emiya, Liva Ralaivola, Hachem Kadri
QuicK-means: Acceleration of K-means by learning a fast transform. CoRR (2019)
Farah Cherfaoui, Valentin Emiya, Liva Ralaivola, Sandrine Anthoine
Recovery and Convergence Rate of the Frank-Wolfe Algorithm for the m-Exact-Sparse Problem. IEEE Trans. Inf. Theory 65 (11) (2019)
Onkar Arun Pandit, Pascal Denis, Liva Ralaivola
Learning Rich Event Representations and Interactions for Temporal Relation Classification. ESANN (2019)
Farah Cherfaoui, Valentin Emiya, Liva Ralaivola, Sandrine Anthoine
Frank-Wolfe Algorithm for the Exact Sparse Problem. CoRR (2018)
Pascal Denis, Liva Ralaivola
Online Learning of Task-specific Word Representations with a Joint Biconvex Passive-Aggressive Algorithm. EACL (1) (2017)
Julien Audiffren, Liva Ralaivola
Bandits Dueling on Partially Ordered Sets. NIPS (2017)
Alain Rakotomamonjy, Sokol Koço, Liva Ralaivola
Greedy Methods, Randomization Approaches, and Multiarm Bandit Algorithms for Efficient Sparsity-Constrained Optimization. IEEE Trans. Neural Networks Learn. Syst. 28 (11) (2017)
François Laviolette, Emilie Morvant, Liva Ralaivola, Jean-Francis Roy
Risk upper bounds for general ensemble methods with an application to multiclass classification. Neurocomputing 219 (2017)
Julien Audiffren, Liva Ralaivola
Indistinguishable Bandits Dueling with Decoys on a Poset. CoRR (2016)
Alain Rakotomamonjy, Sokol Koço, Liva Ralaivola
More efficient sparsity-inducing algorithms using inexact gradient. EUSIPCO (2015)
Ugo Louche, Liva Ralaivola
Unconfused ultraconservative multiclass algorithms. Mach. Learn. 99 (2) (2015)
Liva Ralaivola, Ugo Louche
From Cutting Planes Algorithms to Compression Schemes and Active Learning. CoRR (2015)
Ugo Louche, Liva Ralaivola
Unconfused ultraconservative multiclass algorithms. CoRR (2015)
Alain Rakotomamonjy, Sokol Koço, Liva Ralaivola
Greedy methods, randomization approaches and multi-arm bandit algorithms for efficient sparsity-constrained optimization. CoRR (2015)
Bikash Joshi, Massih-Reza Amini, Ioannis Partalas, Liva Ralaivola, Nicolas Usunier, Éric Gaussier
On Binary Reduction of Large-Scale Multiclass Classification Problems. IDA (2015)
Julien Audiffren, Liva Ralaivola
Cornering Stationary and Restless Mixing Bandits with Remix-UCB. NIPS (2015)
Emmanuel Daucé, Timothée Proix, Liva Ralaivola
Reward-based online learning in non-stationary environments: Adapting a P300-speller with a "backspace" key. IJCNN (2015)
Ugo Louche, Liva Ralaivola
From cutting planes algorithms to compression schemes and active learning. IJCNN (2015)
Antoine Bonnefoy, Valentin Emiya, Liva Ralaivola, Rémi Gribonval
Dynamic Screening: Accelerating First-Order Algorithms for the Lasso and Group-Lasso. IEEE Trans. Signal Process. 63 (19) (2015)
Liva Ralaivola, Massih-Reza Amini
Entropy-Based Concentration Inequalities for Dependent Variables. ICML (2015)
Hongliang Zhong, Emmanuel Daucé, Liva Ralaivola
Online multiclass learning with "bandit" feedback under a Passive-Aggressive approach. ESANN (2015)
François Laviolette, Emilie Morvant, Liva Ralaivola, Jean-Francis Roy
On Generalizing the C-Bound to the Multiclass and Multi-label Settings. CoRR (2015)
Ugo Louche, Liva Ralaivola
Unconfused Ultraconservative Multiclass Algorithms. CoRR (2014)
Julien Audiffren, Liva Ralaivola
Stationary Mixing Bandits. CoRR (2014)
Antoine Bonnefoy, Valentin Emiya, Liva Ralaivola, Rémi Gribonval
A dynamic screening principle for the Lasso. EUSIPCO (2014)
Antoine Bonnefoy, Valentin Emiya, Liva Ralaivola, Rémi Gribonval
Dynamic Screening: Accelerating First-Order Algorithms for the Lasso and Group-Lasso. CoRR (2014)
Sylvain Takerkart, Liva Ralaivola
Multiple subject learning for inter-subject prediction. PRNI (2014)
Ugo Louche, Liva Ralaivola
Unconfused Ultraconservative Multiclass Algorithms. ACML (2013)
Emmanuel Daucé, Timothée Proix, Liva Ralaivola
Fast online adaptivity with policy gradient: example of the BCI "P300"-speller. ESANN (2013)
Emilie Morvant, Sokol Koço, Liva Ralaivola
PAC-Bayesian Generalization Bound on Confusion Matrix for Multi-Class Classification CoRR (2012)
Pierre Machart, Liva Ralaivola
Confusion Matrix Stability Bounds for Multiclass Classification CoRR (2012)
Emilie Morvant, Sokol Koço, Liva Ralaivola
PAC-Bayesian Generalization Bound on Confusion Matrix for Multi-Class Classification. ICML (2012)
Thomas Peel, Valentin Emiya, Liva Ralaivola, Sandrine Anthoine
Matching pursuit with stochastic selection. EUSIPCO (2012)
Sylvain Takerkart, Guillaume Auzias, Bertrand Thirion, Daniele Schön, Liva Ralaivola
Graph-Based Inter-subject Classification of Local fMRI Patterns. MLMI (2012)
Pierre Machart, Thomas Peel, Liva Ralaivola, Sandrine Anthoine, Hervé Glotin
Stochastic Low-Rank Kernel Learning for Regression CoRR (2012)
Liva Ralaivola
Confusion-Based Online Learning and a Passive-Aggressive Scheme. NIPS (2012)
Liva Ralaivola, Benoît Favre, Pierre Gotab, Frédéric Béchet, Géraldine Damnati
Applying Multiclass Bandit algorithms to call-type classification. ASRU (2011)
Pierre Machart, Thomas Peel, Sandrine Anthoine, Liva Ralaivola, Hervé Glotin
Stochastic Low-Rank Kernel Learning for Regression. ICML (2011)
Sylvain Takerkart, Liva Ralaivola
MKPM: A multiclass extension to the kernel projection machine. CVPR (2011)
Thomas Peel, Sandrine Anthoine, Liva Ralaivola
Empirical Bernstein Inequalities for U-Statistics. NIPS (2010)
Liva Ralaivola, Marie Szafranski, Guillaume Stempfel
Chromatic PAC-Bayes Bounds for Non-IID Data: Applications to Ranking and Stationary β-Mixing Processes. J. Mach. Learn. Res. 11 (2010)
Guillaume Stempfel, Liva Ralaivola
Learning SVMs from Sloppily Labeled Data. ICANN (1) (2009)
Liva Ralaivola, Marie Szafranski, Guillaume Stempfel
Chromatic PAC-Bayes Bounds for Non-IID Data: Applications to Ranking and Stationary \beta-Mixing Processes CoRR (2009)
Liva Ralaivola
Semi-supervised bipartite ranking with the normalized Rayleigh coefficient. ESANN (2009)
Liva Ralaivola, Marie Szafranski, Guillaume Stempfel
Chromatic PAC-Bayes Bounds for Non-IID Data. AISTATS (2009)
Raphaël Bailly, François Denis, Liva Ralaivola
Grammatical inference as a principal component analysis problem. ICML (2009)
Matthieu Kowalski, Marie Szafranski, Liva Ralaivola
Multiple indefinite kernel learning with mixed norm regularization. ICML (2009)
Chloé-Agathe Azencott, Alexandre Ksikes, S. Joshua Swamidass, Jonathan H. Chen, Liva Ralaivola, Pierre Baldi
One- to Four-Dimensional Kernels for Virtual Screening and the Prediction of Physical, Chemical, and Biological Properties. J. Chem. Inf. Model. 47 (3) (2007)
Guillaume Stempfel, Liva Ralaivola
Learning Kernel Perceptrons on Noisy Data Using Random Projections. ALT (2007)
François Denis, Christophe Nicolas Magnan, Liva Ralaivola
Efficient learning of Naive Bayes classifiers under class-conditional classification noise. ICML (2006)
Pierre Mahé, Liva Ralaivola, Véronique Stoven, Jean-Philippe Vert
The Pharmacophore Kernel for Virtual Screening with Support Vector Machines. J. Chem. Inf. Model. 46 (5) (2006)
Liva Ralaivola, François Denis, Christophe Nicolas Magnan
CN = CPCN. ICML (2006)
Liva Ralaivola, Lin Wu, Pierre Baldi
SVM and pattern-enriched common fate graphs for the game of go. ESANN (2005)
Liva Ralaivola, Sanjay Joshua Swamidass, Hiroto Saigo, Pierre Baldi
Graph kernels for chemical informatics. Neural Networks 18 (8) (2005)
Sanjay Joshua Swamidass, Jonathan H. Chen, Jocelyne Bruand, Peter Phung, Liva Ralaivola, Pierre Baldi
Kernels for small molecules and the prediction of mutagenicity, toxicity and anti-cancer activity. ISMB (Supplement of Bioinformatics) (2005)
Bruno-Edouard Perrin, Liva Ralaivola, Aurélien Mazurie, Samuele Bottani, Jacques Mallet, Florence d'Alché-Buc
Gene networks inference using dynamic Bayesian networks. ECCB (2003)
Liva Ralaivola, Florence d'Alché-Buc
Dynamical Modeling with Kernels for Nonlinear Time Series Prediction. NIPS (2003)
Liva Ralaivola, Florence d'Alché-Buc
Incremental Support Vector Machine Learning: A Local Approach. ICANN (2001)