Anna Korba

58 papers A* 20A 6B 3Journal 29
YearRankTypeTitle / Venue / Authors
2026 J jnl
Generalized Discrete Diffusion from Snapshots.
CoRR
Oussama Zekri, Théo Uscidda, Nicolas Boullé, Anna Korba
2025 J jnl
(De)-regularized Maximum Mean Discrepancy Gradient Flow.
J. Mach. Learn. Res.
Zonghao Chen, Aratrika Mustafi, Pierre Glaser, Anna Korba, Arthur Gretton, Bharath K. Sriperumbudur
2025 A conf
Bayesian Off-Policy Evaluation and Learning for Large Action Spaces.
AISTATS
Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba
2025 A conf
DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows.
AISTATS
Jonathan Geuter, Clément Bonet, Anna Korba, David Alvarez-Melis
2025 J jnl
DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows.
CoRR
Jonathan Geuter, Clément Bonet, Anna Korba, David Alvarez-Melis
2025 A* conf
Density Ratio Estimation with Conditional Probability Paths.
ICML
Hanlin Yu, Arto Klami, Aapo Hyvärinen, Anna Korba, Omar Chehab
2025 J jnl
Density Ratio Estimation with Conditional Probability Paths.
CoRR
Hanlin Yu, Arto Klami, Aapo Hyvärinen, Anna Korba, Omar Chehab
2025 A* conf
Flowing Datasets with Wasserstein over Wasserstein Gradient Flows.
ICML
Clément Bonet, Christophe Vauthier, Anna Korba
2025 J jnl
Flowing Datasets with Wasserstein over Wasserstein Gradient Flows.
CoRR
Clément Bonet, Christophe Vauthier, Anna Korba
2025 A conf
Implicit Diffusion: Efficient optimization through stochastic sampling.
AISTATS
Pierre Marion, Anna Korba, Peter L. Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet
2025 J jnl
Kernel Trace Distance: Quantum Statistical Metric between Measures through RKHS Density Operators.
CoRR
Arturo Castellanos, Anna Korba, Pavlo Mozharovskyi, Hicham Janati
2025 J jnl
Polynomial time sampling from log-smooth distributions in fixed dimension under semi-log-concavity of the forward diffusion with application to strongly dissipative distributions.
CoRR
Adrien Vacher, Omar Chehab, Anna Korba
2025 J jnl
Properties of Wasserstein Gradient Flows for the Sliced-Wasserstein Distance.
CoRR
Christophe Vauthier, Quentin Mérigot, Anna Korba
2025 A* conf
Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics.
ICLR
Omar Chehab, Anna Korba, Austin J. Stromme, Adrien Vacher
2025 A* conf
Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis.
ICML
Christophe Vauthier, Anna Korba, Quentin Mérigot
2025 J jnl
Variational Inference with Mixtures of Isotropic Gaussians.
CoRR
Marguerite Petit-Talamon, Marc Lambert, Anna Korba
2024 J jnl
(De)-regularized Maximum Mean Discrepancy Gradient Flow.
CoRR
Zonghao Chen, Aratrika Mustafi, Pierre Glaser, Anna Korba, Arthur Gretton, Bharath K. Sriperumbudur
2024 J jnl
A Practical Diffusion Path for Sampling.
CoRR
Omar Chehab, Anna Korba
2024 A* conf
A connection between Tempering and Entropic Mirror Descent.
ICML
Nicolas Chopin, Francesca R. Crucinio, Anna Korba
2024 J jnl
Bayesian Off-Policy Evaluation and Learning for Large Action Spaces.
CoRR
Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba
2024 A* conf
Constrained Sampling with Primal-Dual Langevin Monte Carlo.
NeurIPS
Luiz F. O. Chamon, Mohammad Reza Karimi Jaghargh, Anna Korba
2024 J jnl
Constrained Sampling with Primal-Dual Langevin Monte Carlo.
CoRR
Luiz F. O. Chamon, Mohammad Reza Karimi, Anna Korba
2024 J jnl
Implicit Diffusion: Efficient Optimization through Stochastic Sampling.
CoRR
Pierre Marion, Anna Korba, Peter L. Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet
2024 A* conf
Mirror and Preconditioned Gradient Descent in Wasserstein Space.
NeurIPS
Clément Bonet, Théo Uscidda, Adam David, Pierre-Cyril Aubin-Frankowski, Anna Korba
2024 J jnl
Mirror and Preconditioned Gradient Descent in Wasserstein Space.
CoRR
Clément Bonet, Théo Uscidda, Adam David, Pierre-Cyril Aubin-Frankowski, Anna Korba
2024 J jnl
Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics.
CoRR
Omar Chehab, Anna Korba, Austin J. Stromme, Adrien Vacher
2024 J jnl
Statistical and Geometrical properties of regularized Kernel Kullback-Leibler divergence.
CoRR
Clémentine Chazal, Anna Korba, Francis R. Bach
2024 A* conf
Statistical and Geometrical properties of the Kernel Kullback-Leibler divergence.
NeurIPS
Anna Korba, Francis R. Bach, Clémentine Chazal
2024 A* conf
Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians.
ICML
Tom Huix, Anna Korba, Alain Oliviero Durmus, Eric Moulines
2024 J jnl
Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians.
CoRR
Tom Huix, Anna Korba, Alain Durmus, Eric Moulines
2024 A conf
Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling.
UAI
Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba
2024 J jnl
Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling.
CoRR
Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba
2023 A* conf
Exponential Smoothing for Off-Policy Learning.
ICML
Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba
2023 J jnl
Exponential Smoothing for Off-Policy Learning.
CoRR
Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba
2023 A* conf
Sampling with Mollified Interaction Energy Descent.
ICLR
Lingxiao Li, Qiang Liu, Anna Korba, Mikhail Yurochkin, Justin Solomon
2022 A* conf
Accurate Quantization of Measures via Interacting Particle-based Optimization.
ICML
Lantian Xu, Anna Korba, Dejan Slepcev
2022 A conf
Adaptive Importance Sampling meets Mirror Descent : a Bias-variance Tradeoff.
AISTATS
Anna Korba, François Portier
2022 A* conf
Mirror Descent with Relative Smoothness in Measure Spaces, with application to Sinkhorn and EM.
NeurIPS
Pierre-Cyril Aubin-Frankowski, Anna Korba, Flavien Léger
2022 J jnl
Mirror Descent with Relative Smoothness in Measure Spaces, with application to Sinkhorn and EM.
CoRR
Pierre-Cyril Aubin-Frankowski, Anna Korba, Flavien Léger
2022 J jnl
Sampling with Mollified Interaction Energy Descent.
CoRR
Lingxiao Li, Qiang Liu, Anna Korba, Mikhail Yurochkin, Justin Solomon
2022 J jnl
Variational Inference of overparameterized Bayesian Neural Networks: a theoretical and empirical study.
CoRR
Tom Huix, Szymon Majewski, Alain Durmus, Eric Moulines, Anna Korba
2021 A* conf
Kernel Stein Discrepancy Descent.
ICML
Anna Korba, Pierre-Cyril Aubin-Frankowski, Szymon Majewski, Pierre Ablin
2021 J jnl
Kernel Stein Discrepancy Descent.
CoRR
Anna Korba, Pierre-Cyril Aubin-Frankowski, Szymon Majewski, Pierre Ablin
2021 A* conf
Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction.
ICML
Afsaneh Mastouri, Yuchen Zhu, Limor Gultchin, Anna Korba, Ricardo Silva, Matt J. Kusner, Arthur Gretton, Krikamol Muandet
2021 J jnl
Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction.
CoRR
Afsaneh Mastouri, Yuchen Zhu, Limor Gultchin, Anna Korba, Ricardo Silva, Matt J. Kusner, Arthur Gretton, Krikamol Muandet
2020 A* conf
A Non-Asymptotic Analysis for Stein Variational Gradient Descent.
NeurIPS
Anna Korba, Adil Salim, Michael Arbel, Giulia Luise, Arthur Gretton
2020 J jnl
A Non-Asymptotic Analysis for Stein Variational Gradient Descent.
CoRR
Anna Korba, Adil Salim, Michael Arbel, Giulia Luise, Arthur Gretton
2020 A* conf
The Wasserstein Proximal Gradient Algorithm.
NeurIPS
Adil Salim, Anna Korba, Giulia Luise
2019 B conf
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach.
ALT
Mastane Achab, Anna Korba, Stéphan Clémençon
2019 A* conf
Maximum Mean Discrepancy Gradient Flow.
NeurIPS
Michael Arbel, Anna Korba, Adil Salim, Arthur Gretton
2019 J jnl
Maximum Mean Discrepancy Gradient Flow.
CoRR
Michael Arbel, Anna Korba, Adil Salim, Arthur Gretton
2018 A* conf
A Structured Prediction Approach for Label Ranking.
NeurIPS
Anna Korba, Alexandre Garcia, Florence d'Alché-Buc
2018 J jnl
A Structured Prediction Approach for Label Ranking.
CoRR
Anna Korba, Alexandre Garcia, Florence d'Alché-Buc
2018 J jnl
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach.
CoRR
Mastane Achab, Anna Korba, Stéphan Clémençon
2018 B conf
On aggregation in ranking median regression.
ESANN
Stéphan Clémençon, Anna Korba
2018 B conf
Ranking Median Regression: Learning to Order through Local Consensus.
ALT
Stéphan Clémençon, Anna Korba, Eric Sibony
2017 A conf
A Learning Theory of Ranking Aggregation.
AISTATS
Anna Korba, Stéphan Clémençon, Eric Sibony
2016 A* conf
Controlling the distance to a Kemeny consensus without computing it.
ICML
Yunlong Jiao, Anna Korba, Eric Sibony