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Anna Korba
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2020 – today
- 2024
- [i16]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 abs/2402.05468 (2024) - [i15]Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba:
Bayesian Off-Policy Evaluation and Learning for Large Action Spaces. CoRR abs/2402.14664 (2024) - [i14]Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba:
Unified PAC-Bayesian Study of Pessimism for Offline Policy Learning with Regularized Importance Sampling. CoRR abs/2406.03434 (2024) - [i13]Tom Huix, Anna Korba, Alain Durmus, Eric Moulines:
Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians. CoRR abs/2406.04012 (2024) - [i12]Clément Bonet, Théo Uscidda, Adam David, Pierre-Cyril Aubin-Frankowski, Anna Korba:
Mirror and Preconditioned Gradient Descent in Wasserstein Space. CoRR abs/2406.08938 (2024) - [i11]Omar Chehab, Anna Korba:
A Practical Diffusion Path for Sampling. CoRR abs/2406.14040 (2024) - 2023
- [c16]Lingxiao Li, Qiang Liu, Anna Korba, Mikhail Yurochkin, Justin Solomon:
Sampling with Mollified Interaction Energy Descent. ICLR 2023 - [c15]Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba:
Exponential Smoothing for Off-Policy Learning. ICML 2023: 984-1017 - [i10]Imad Aouali, Victor-Emmanuel Brunel, David Rohde, Anna Korba:
Exponential Smoothing for Off-Policy Learning. CoRR abs/2305.15877 (2023) - 2022
- [c14]Anna Korba, François Portier:
Adaptive Importance Sampling meets Mirror Descent : a Bias-variance Tradeoff. AISTATS 2022: 11503-11527 - [c13]Lantian Xu, Anna Korba, Dejan Slepcev:
Accurate Quantization of Measures via Interacting Particle-based Optimization. ICML 2022: 24576-24595 - [c12]Pierre-Cyril Aubin-Frankowski, Anna Korba, Flavien Léger:
Mirror Descent with Relative Smoothness in Measure Spaces, with application to Sinkhorn and EM. NeurIPS 2022 - [i9]Pierre-Cyril Aubin-Frankowski, Anna Korba, Flavien Léger:
Mirror Descent with Relative Smoothness in Measure Spaces, with application to Sinkhorn and EM. CoRR abs/2206.08873 (2022) - [i8]Tom Huix, Szymon Majewski, Alain Durmus, Eric Moulines, Anna Korba:
Variational Inference of overparameterized Bayesian Neural Networks: a theoretical and empirical study. CoRR abs/2207.03859 (2022) - [i7]Lingxiao Li, Qiang Liu, Anna Korba, Mikhail Yurochkin, Justin Solomon:
Sampling with Mollified Interaction Energy Descent. CoRR abs/2210.13400 (2022) - 2021
- [c11]Anna Korba, Pierre-Cyril Aubin-Frankowski, Szymon Majewski, Pierre Ablin:
Kernel Stein Discrepancy Descent. ICML 2021: 5719-5730 - [c10]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: 7512-7523 - [i6]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 abs/2105.04544 (2021) - [i5]Anna Korba, Pierre-Cyril Aubin-Frankowski, Szymon Majewski, Pierre Ablin:
Kernel Stein Discrepancy Descent. CoRR abs/2105.09994 (2021) - 2020
- [c9]Anna Korba, Adil Salim, Michael Arbel, Giulia Luise, Arthur Gretton:
A Non-Asymptotic Analysis for Stein Variational Gradient Descent. NeurIPS 2020 - [c8]Adil Salim, Anna Korba, Giulia Luise:
The Wasserstein Proximal Gradient Algorithm. NeurIPS 2020 - [i4]Anna Korba, Adil Salim, Michael Arbel, Giulia Luise, Arthur Gretton:
A Non-Asymptotic Analysis for Stein Variational Gradient Descent. CoRR abs/2006.09797 (2020)
2010 – 2019
- 2019
- [c7]Mastane Achab, Anna Korba, Stéphan Clémençon:
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach. ALT 2019: 64-93 - [c6]Michael Arbel, Anna Korba, Adil Salim, Arthur Gretton:
Maximum Mean Discrepancy Gradient Flow. NeurIPS 2019: 6481-6491 - [i3]Michael Arbel, Anna Korba, Adil Salim, Arthur Gretton:
Maximum Mean Discrepancy Gradient Flow. CoRR abs/1906.04370 (2019) - 2018
- [c5]Stéphan Clémençon, Anna Korba, Eric Sibony:
Ranking Median Regression: Learning to Order through Local Consensus. ALT 2018: 212-245 - [c4]Stéphan Clémençon, Anna Korba:
On aggregation in ranking median regression. ESANN 2018 - [c3]Anna Korba, Alexandre Garcia, Florence d'Alché-Buc:
A Structured Prediction Approach for Label Ranking. NeurIPS 2018: 9008-9018 - [i2]Anna Korba, Alexandre Garcia, Florence d'Alché-Buc:
A Structured Prediction Approach for Label Ranking. CoRR abs/1807.02374 (2018) - [i1]Mastane Achab, Anna Korba, Stéphan Clémençon:
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach. CoRR abs/1810.06291 (2018) - 2017
- [c2]Anna Korba, Stéphan Clémençon, Eric Sibony:
A Learning Theory of Ranking Aggregation. AISTATS 2017: 1001-1010 - 2016
- [c1]Yunlong Jiao, Anna Korba, Eric Sibony:
Controlling the distance to a Kemeny consensus without computing it. ICML 2016: 2971-2980
Coauthor Index
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last updated on 2024-07-25 19:33 CEST by the dblp team
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