Anna Korba

According to our database, Anna Korba authored at least 27 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics.

Omar Chehab, Anna Korba, Austin Stromme, Adrien Vacher

CoRR, 2024

(De)-regularized Maximum Mean Discrepancy Gradient Flow.

Zonghao Chen, Aratrika Mustafi, Pierre Glaser, Anna Korba, Arthur Gretton, Bharath K. Sriperumbudur

CoRR, 2024

Statistical and Geometrical properties of regularized Kernel Kullback-Leibler divergence.

Clémentine Chazal, Anna Korba, Francis Bach

CoRR, 2024

A Practical Diffusion Path for Sampling.

Omar Chehab, Anna Korba

CoRR, 2024

Mirror and Preconditioned Gradient Descent in Wasserstein Space.

Clément Bonet, Théo Uscidda, Adam David, Pierre-Cyril Aubin-Frankowski, Anna Korba

CoRR, 2024

Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling.

Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba

CoRR, 2024

Bayesian Off-Policy Evaluation and Learning for Large Action Spaces.

Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba

CoRR, 2024

Implicit Diffusion: Efficient Optimization through Stochastic Sampling.

Pierre Marion, Anna Korba, Peter Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet

CoRR, 2024

Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians.

Tom Huix, Anna Korba, Alain Oliviero Durmus, Eric Moulines

Proceedings of the Forty-first International Conference on Machine Learning, 2024

A connection between Tempering and Entropic Mirror Descent.

Nicolas Chopin, Francesca R. Crucinio, Anna Korba

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Exponential Smoothing for Off-Policy Learning.

Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba

Proceedings of the International Conference on Machine Learning, 2023

Sampling with Mollified Interaction Energy Descent.

Lingxiao Li, Qiang Liu, Anna Korba, Mikhail Yurochkin, Justin Solomon

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Variational Inference of overparameterized Bayesian Neural Networks: a theoretical and empirical study.

Tom Huix, Szymon Majewski, Alain Durmus, Eric Moulines, Anna Korba

CoRR, 2022

Mirror Descent with Relative Smoothness in Measure Spaces, with application to Sinkhorn and EM.

Pierre-Cyril Aubin-Frankowski, Anna Korba, Flavien Léger

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Accurate Quantization of Measures via Interacting Particle-based Optimization.

Lantian Xu, Anna Korba, Dejan Slepcev

Proceedings of the International Conference on Machine Learning, 2022

Adaptive Importance Sampling meets Mirror Descent : a Bias-variance Tradeoff.

Anna Korba, François Portier

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction.

Afsaneh Mastouri, Yuchen Zhu, Limor Gultchin, Anna Korba, Ricardo Silva, Matt J. Kusner, Arthur Gretton, Krikamol Muandet

Proceedings of the 38th International Conference on Machine Learning, 2021

Kernel Stein Discrepancy Descent.

Anna Korba, Pierre-Cyril Aubin-Frankowski, Szymon Majewski, Pierre Ablin

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

The Wasserstein Proximal Gradient Algorithm.

Adil Salim, Anna Korba, Giulia Luise

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A Non-Asymptotic Analysis for Stein Variational Gradient Descent.

Anna Korba, Adil Salim, Michael Arbel, Giulia Luise, Arthur Gretton

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Maximum Mean Discrepancy Gradient Flow.

Michael Arbel, Anna Korba, Adil Salim, Arthur Gretton

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach.

Mastane Achab, Anna Korba, Stéphan Clémençon

Proceedings of the Algorithmic Learning Theory, 2019

2018

A Structured Prediction Approach for Label Ranking.

Anna Korba, Alexandre Garcia, Florence d'Alché-Buc

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

On aggregation in ranking median regression.

Stéphan Clémençon, Anna Korba

Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Ranking Median Regression: Learning to Order through Local Consensus.

Stéphan Clémençon, Anna Korba, Eric Sibony

Proceedings of the Algorithmic Learning Theory, 2018

2017

A Learning Theory of Ranking Aggregation.

Anna Korba, Stéphan Clémençon, Eric Sibony

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Controlling the distance to a Kemeny consensus without computing it.

Yunlong Jiao, Anna Korba, Eric Sibony

Proceedings of the 33nd International Conference on Machine Learning, 2016