Korba, Anna

33 publications

JMLR 2025 (De)-Regularized Maximum Mean Discrepancy Gradient Flow Zonghao Chen, Aratrika Mustafi, Pierre Glaser, Anna Korba, Arthur Gretton, Bharath K. Sriperumbudur

AISTATS 2025 Bayesian Off-Policy Evaluation and Learning for Large Action Spaces Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba

AISTATS 2025 DDEQs: Distributional Deep Equilibrium Models Through Wasserstein Gradient Flows Jonathan Geuter, Clément Bonet, Anna Korba, David Alvarez-Melis

ICML 2025 Density Ratio Estimation with Conditional Probability Paths Hanlin Yu, Arto Klami, Aapo Hyvarinen, Anna Korba, Omar Chehab

ICML 2025 Flowing Datasets with Wasserstein over Wasserstein Gradient Flows Clément Bonet, Christophe Vauthier, Anna Korba

AISTATS 2025 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

ICLR 2025 Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics Omar Chehab, Anna Korba, Austin J Stromme, Adrien Vacher

NeurIPS 2025 Sampling from Multi-Modal Distributions with Polynomial Query Complexity in Fixed Dimension via Reverse Diffusion Adrien Vacher, Omar Chehab, Anna Korba

ICML 2025 Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis Christophe Vauthier, Anna Korba, Quentin Mérigot

NeurIPS 2025 Variational Inference with Mixtures of Isotropic Gaussians Marguerite Petit-Talamon, Marc Lambert, Anna Korba

ICML 2024 A Connection Between Tempering and Entropic Mirror Descent Nicolas Chopin, Francesca Crucinio, Anna Korba

ICMLW 2024 A Practical Diffusion Path for Sampling Omar Chehab, Anna Korba

NeurIPS 2024 Constrained Sampling with Primal-Dual Langevin Monte Carlo Luiz F. O. Chamon, Mohammad Reza Karimi, Anna Korba

ICMLW 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

NeurIPS 2024 Mirror and Preconditioned Gradient Descent in Wasserstein Space Clément Bonet, Théo Uscidda, Adam David, Pierre-Cyril Aubin-Frankowski, Anna Korba

NeurIPS 2024 Statistical and Geometrical Properties of the Kernel Kullback-Leibler Divergence Clémentine Chazal, Anna Korba, Francis Bach

ICML 2024 Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians Tom Huix, Anna Korba, Alain Oliviero Durmus, Eric Moulines

UAI 2024 Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba

ICML 2023 Exponential Smoothing for Off-Policy Learning Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba

ICLR 2023 Sampling with Mollified Interaction Energy Descent Lingxiao Li, Qiang Liu, Anna Korba, Mikhail Yurochkin, Justin Solomon

AISTATS 2022 Adaptive Importance Sampling Meets Mirror Descent : A Bias-Variance Tradeoff Anna Korba, François Portier

ICML 2022 Accurate Quantization of Measures via Interacting Particle-Based Optimization Lantian Xu, Anna Korba, Dejan Slepcev

NeurIPS 2022 Mirror Descent with Relative Smoothness in Measure Spaces, with Application to Sinkhorn and EM Pierre-Cyril Aubin-Frankowski, Anna Korba, Flavien Léger

ICML 2021 Kernel Stein Discrepancy Descent Anna Korba, Pierre-Cyril Aubin-Frankowski, Szymon Majewski, Pierre Ablin

ICML 2021 Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction Afsaneh Mastouri, Yuchen Zhu, Limor Gultchin, Anna Korba, Ricardo Silva, Matt Kusner, Arthur Gretton, Krikamol Muandet

NeurIPS 2020 A Non-Asymptotic Analysis for Stein Variational Gradient Descent Anna Korba, Adil Salim, Michael Arbel, Giulia Luise, Arthur Gretton

NeurIPS 2020 The Wasserstein Proximal Gradient Algorithm Adil Salim, Anna Korba, Giulia Luise

ALT 2019 Dimensionality Reduction and (Bucket) Ranking: A Mass Transportation Approach Mastane Achab, Anna Korba, Stephan Clémençon

NeurIPS 2019 Maximum Mean Discrepancy Gradient Flow Michael Arbel, Anna Korba, Adil Salim, Arthur Gretton

NeurIPS 2018 A Structured Prediction Approach for Label Ranking Anna Korba, Alexandre Garcia, Florence d'Alché-Buc

ALT 2018 Ranking Median Regression: Learning to Order Through Local Consensus Stephan Clémençon, Anna Korba, Eric Sibony

AISTATS 2017 A Learning Theory of Ranking Aggregation Anna Korba, Stéphan Clémençon, Eric Sibony

ICML 2016 Controlling the Distance to a Kemeny Consensus Without Computing It Yunlong Jiao, Anna Korba, Eric Sibony