Anna Korba

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 32

Top Topics

Variational Inference

Efficient Optimization

Asymptotic Analysis

Top Venues

Publications

Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba
Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling. CoRR (2024)
Pierre Marion, Anna Korba, Peter Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet
Implicit Diffusion: Efficient Optimization through Stochastic Sampling. CoRR (2024)
Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba
Bayesian Off-Policy Evaluation and Learning for Large Action Spaces. CoRR (2024)
Omar Chehab, Anna Korba
A Practical Diffusion Path for Sampling. CoRR (2024)
Clément Bonet, Théo Uscidda, Adam David, Pierre-Cyril Aubin-Frankowski, Anna Korba
Mirror and Preconditioned Gradient Descent in Wasserstein Space. CoRR (2024)
Tom Huix, Anna Korba, Alain Durmus, Eric Moulines
Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians. CoRR (2024)
Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba
Exponential Smoothing for Off-Policy Learning. CoRR (2023)
Lingxiao Li, Qiang Liu, Anna Korba, Mikhail Yurochkin, Justin Solomon
Sampling with Mollified Interaction Energy Descent. ICLR (2023)
Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba
Exponential Smoothing for Off-Policy Learning. ICML (2023)
Lingxiao Li, Qiang Liu, Anna Korba, Mikhail Yurochkin, Justin Solomon
Sampling with Mollified Interaction Energy Descent. CoRR (2022)
Pierre-Cyril Aubin-Frankowski, Anna Korba, Flavien Léger
Mirror Descent with Relative Smoothness in Measure Spaces, with application to Sinkhorn and EM. NeurIPS (2022)
Anna Korba, François Portier
Adaptive Importance Sampling meets Mirror Descent : a Bias-variance Tradeoff. AISTATS (2022)
Pierre-Cyril Aubin-Frankowski, Anna Korba, Flavien Léger
Mirror Descent with Relative Smoothness in Measure Spaces, with application to Sinkhorn and EM. CoRR (2022)
Lantian Xu, Anna Korba, Dejan Slepcev
Accurate Quantization of Measures via Interacting Particle-based Optimization. ICML (2022)
Tom Huix, Szymon Majewski, Alain Durmus, Eric Moulines, Anna Korba
Variational Inference of overparameterized Bayesian Neural Networks: a theoretical and empirical study. CoRR (2022)
Anna Korba, Pierre-Cyril Aubin-Frankowski, Szymon Majewski, Pierre Ablin
Kernel Stein Discrepancy Descent. CoRR (2021)
Afsaneh Mastouri, Yuchen Zhu, Limor Gultchin, Anna Korba, Ricardo Silva, Matt J. Kusner, Arthur Gretton, Krikamol Muandet
Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction. ICML (2021)
Afsaneh Mastouri, Yuchen Zhu, Limor Gultchin, Anna Korba, Ricardo Silva, Matt J. Kusner, Arthur Gretton, Krikamol Muandet
Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction. CoRR (2021)
Anna Korba, Pierre-Cyril Aubin-Frankowski, Szymon Majewski, Pierre Ablin
Kernel Stein Discrepancy Descent. ICML (2021)
Anna Korba, Adil Salim, Michael Arbel, Giulia Luise, Arthur Gretton
A Non-Asymptotic Analysis for Stein Variational Gradient Descent. CoRR (2020)
Adil Salim, Anna Korba, Giulia Luise
The Wasserstein Proximal Gradient Algorithm. NeurIPS (2020)
Anna Korba, Adil Salim, Michael Arbel, Giulia Luise, Arthur Gretton
A Non-Asymptotic Analysis for Stein Variational Gradient Descent. NeurIPS (2020)
Michael Arbel, Anna Korba, Adil Salim, Arthur Gretton
Maximum Mean Discrepancy Gradient Flow. NeurIPS (2019)
Michael Arbel, Anna Korba, Adil Salim, Arthur Gretton
Maximum Mean Discrepancy Gradient Flow. CoRR (2019)
Mastane Achab, Anna Korba, Stéphan Clémençon
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach. ALT (2019)
Stéphan Clémençon, Anna Korba
On aggregation in ranking median regression. ESANN (2018)
Anna Korba, Alexandre Garcia, Florence d'Alché-Buc
A Structured Prediction Approach for Label Ranking. CoRR (2018)
Stéphan Clémençon, Anna Korba, Eric Sibony
Ranking Median Regression: Learning to Order through Local Consensus. ALT (2018)
Anna Korba, Alexandre Garcia, Florence d'Alché-Buc
A Structured Prediction Approach for Label Ranking. NeurIPS (2018)
Mastane Achab, Anna Korba, Stéphan Clémençon
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach. CoRR (2018)
Anna Korba, Stéphan Clémençon, Eric Sibony
A Learning Theory of Ranking Aggregation. AISTATS (2017)
Yunlong Jiao, Anna Korba, Eric Sibony
Controlling the distance to a Kemeny consensus without computing it. ICML (2016)