Liva Ralaivola

Orcid: 0000-0002-4571-1119

According to our database1, Liva Ralaivola authored at least 60 papers between 2001 and 2023.

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Bibliography

2023
Federated Wasserstein Distance.
CoRR, 2023

Personalised Federated Learning On Heterogeneous Feature Spaces.
CoRR, 2023

Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances.
Proceedings of the International Conference on Machine Learning, 2023

2022
Scalable Ridge Leverage Score Sampling for the Nyström Method.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
QuicK-means: accelerating inference for K-means by learning fast transforms.
Mach. Learn., 2021

Photonic Differential Privacy with Direct Feedback Alignment.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Differentially Private Sliced Wasserstein Distance.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Quantum bandits.
Quantum Mach. Intell., 2020

Partial Trace Regression and Low-Rank Kraus Decomposition.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Recovery and Convergence Rate of the Frank-Wolfe Algorithm for the m-Exact-Sparse Problem.
IEEE Trans. Inf. Theory, 2019

QuicK-means: Acceleration of K-means by learning a fast transform.
CoRR, 2019

Learning Rich Event Representations and Interactions for Temporal Relation Classification.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

2018
Frank-Wolfe Algorithm for the Exact Sparse Problem.
CoRR, 2018

2017
Greedy Methods, Randomization Approaches, and Multiarm Bandit Algorithms for Efficient Sparsity-Constrained Optimization.
IEEE Trans. Neural Networks Learn. Syst., 2017

Risk upper bounds for general ensemble methods with an application to multiclass classification.
Neurocomputing, 2017

Bandits Dueling on Partially Ordered Sets.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Online Learning of Task-specific Word Representations with a Joint Biconvex Passive-Aggressive Algorithm.
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, 2017

2016
Indistinguishable Bandits Dueling with Decoys on a Poset.
CoRR, 2016

2015
Dynamic Screening: Accelerating First-Order Algorithms for the Lasso and Group-Lasso.
IEEE Trans. Signal Process., 2015

Unconfused ultraconservative multiclass algorithms.
Mach. Learn., 2015

Greedy methods, randomization approaches and multi-arm bandit algorithms for efficient sparsity-constrained optimization.
CoRR, 2015

On Generalizing the C-Bound to the Multiclass and Multi-label Settings.
CoRR, 2015

Cornering Stationary and Restless Mixing Bandits with Remix-UCB.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

From cutting planes algorithms to compression schemes and active learning.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Reward-based online learning in non-stationary environments: Adapting a P300-speller with a "backspace" key.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

On Binary Reduction of Large-Scale Multiclass Classification Problems.
Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

Entropy-Based Concentration Inequalities for Dependent Variables.
Proceedings of the 32nd International Conference on Machine Learning, 2015

More efficient sparsity-inducing algorithms using inexact gradient.
Proceedings of the 23rd European Signal Processing Conference, 2015

Online multiclass learning with "bandit" feedback under a Passive-Aggressive approach.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

2014
Stationary Mixing Bandits.
CoRR, 2014

Multiple subject learning for inter-subject prediction.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2014

A dynamic screening principle for the Lasso.
Proceedings of the 22nd European Signal Processing Conference, 2014

2013
Fast online adaptivity with policy gradient: example of the BCI "P300"-speller.
Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

2012
Confusion Matrix Stability Bounds for Multiclass Classification
CoRR, 2012

Confusion-Based Online Learning and a Passive-Aggressive Scheme.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Graph-Based Inter-subject Classification of Local fMRI Patterns.
Proceedings of the Machine Learning in Medical Imaging - Third International Workshop, 2012

PAC-Bayesian Generalization Bound on Confusion Matrix for Multi-Class Classification.
Proceedings of the 29th International Conference on Machine Learning, 2012

Matching pursuit with stochastic selection.
Proceedings of the 20th European Signal Processing Conference, 2012

2011
Stochastic Low-Rank Kernel Learning for Regression.
Proceedings of the 28th International Conference on Machine Learning, 2011

MKPM: A multiclass extension to the kernel projection machine.
Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

Applying Multiclass Bandit algorithms to call-type classification.
Proceedings of the 2011 IEEE Workshop on Automatic Speech Recognition & Understanding, 2011

2010
Chromatic PAC-Bayes Bounds for Non-IID Data: Applications to Ranking and Stationary β-Mixing Processes.
J. Mach. Learn. Res., 2010

Empirical Bernstein Inequalities for U-Statistics.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009
Chromatic PAC-Bayes Bounds for Non-IID Data.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Chromatic PAC-Bayes Bounds for Non-IID Data: Applications to Ranking and Stationary \beta-Mixing Processes
CoRR, 2009

Multiple indefinite kernel learning with mixed norm regularization.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Grammatical inference as a principal component analysis problem.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Learning SVMs from Sloppily Labeled Data.
Proceedings of the Artificial Neural Networks, 2009

Semi-supervised bipartite ranking with the normalized Rayleigh coefficient.
Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

2007
One- to Four-Dimensional Kernels for Virtual Screening and the Prediction of Physical, Chemical, and Biological Properties.
J. Chem. Inf. Model., 2007

Learning Kernel Perceptrons on Noisy Data Using Random Projections.
Proceedings of the Algorithmic Learning Theory, 18th International Conference, 2007

2006
The Pharmacophore Kernel for Virtual Screening with Support Vector Machines.
J. Chem. Inf. Model., 2006

CN = CPCN.
Proceedings of the Machine Learning, 2006

Efficient learning of Naive Bayes classifiers under class-conditional classification noise.
Proceedings of the Machine Learning, 2006

2005
Graph kernels for chemical informatics.
Neural Networks, 2005

Kernels for small molecules and the prediction of mutagenicity, toxicity and anti-cancer activity.
Proceedings of the Proceedings Thirteenth International Conference on Intelligent Systems for Molecular Biology 2005, 2005

SVM and pattern-enriched common fate graphs for the game of go.
Proceedings of the 13th European Symposium on Artificial Neural Networks, 2005

2003
Dynamical Modeling with Kernels for Nonlinear Time Series Prediction.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Gene networks inference using dynamic Bayesian networks.
Proceedings of the European Conference on Computational Biology (ECCB 2003), 2003

2001
Incremental Support Vector Machine Learning: A Local Approach.
Proceedings of the Artificial Neural Networks, 2001


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