Anna Korba

According to our database1, Anna Korba authored at least 19 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Bayesian Off-Policy Evaluation and Learning for Large Action Spaces.
CoRR, 2024

Implicit Diffusion: Efficient Optimization through Stochastic Sampling.
CoRR, 2024

2023
Exponential Smoothing for Off-Policy Learning.
Proceedings of the International Conference on Machine Learning, 2023

Sampling with Mollified Interaction Energy Descent.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Variational Inference of overparameterized Bayesian Neural Networks: a theoretical and empirical study.
CoRR, 2022

Mirror Descent with Relative Smoothness in Measure Spaces, with application to Sinkhorn and EM.
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.
Proceedings of the International Conference on Machine Learning, 2022

Adaptive Importance Sampling meets Mirror Descent : a Bias-variance Tradeoff.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction.
Proceedings of the 38th International Conference on Machine Learning, 2021

Kernel Stein Discrepancy Descent.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
The Wasserstein Proximal Gradient Algorithm.
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.
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.
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.
Proceedings of the Algorithmic Learning Theory, 2019

2018
A Structured Prediction Approach for Label Ranking.
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.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Ranking Median Regression: Learning to Order through Local Consensus.
Proceedings of the Algorithmic Learning Theory, 2018

2017
A Learning Theory of Ranking Aggregation.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Controlling the distance to a Kemeny consensus without computing it.
Proceedings of the 33nd International Conference on Machine Learning, 2016


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