Po-An Wang

According to our database, Po-An Wang authored at least 9 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

On Uniformly Optimal Algorithms for Best Arm Identification in Two-Armed Bandits with Fixed Budget.

Po-An Wang, Kaito Ariu, Alexandre Proutière

CoRR, 2023

Best Arm Identification with Fixed Budget: A Large Deviation Perspective.

Po-An Wang, Ruo-Chun Tzeng, Alexandre Proutière

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Closing the Computational-Statistical Gap in Best Arm Identification for Combinatorial Semi-bandits.

Ruo-Chun Tzeng, Po-An Wang, Alexandre Proutière, Chi-Jen Lu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Improved analysis of randomized SVD for top-eigenvector approximation.

Ruo-Chun Tzeng, Po-An Wang, Florian Adriaens, Aristides Gionis, Chi-Jen Lu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Fast Pure Exploration via Frank-Wolfe.

Po-An Wang, Ruo-Chun Tzeng, Alexandre Proutière

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Optimal Algorithms for Multiplayer Multi-Armed Bandits.

Po-An Wang, Alexandre Proutière, Kaito Ariu, Yassir Jedra, Alessio Russo

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

An Optimal Algorithm in Multiplayer Multi-Armed Bandits.

Alexandre Proutière, Po-An Wang

CoRR, 2019

Lifelong Optimization with Low Regret.

Yi-Shan Wu, Po-An Wang, Chi-Jen Lu

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2017

Tensor Decomposition via Simultaneous Power Iteration.

Po-An Wang, Chi-Jen Lu

Proceedings of the 34th International Conference on Machine Learning, 2017