Liva Ralaivola

75 papers A* 13A 1B 10C 4Misc 1Journal 33Unranked 13

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