Search Results for author: Ruo-Chun Tzeng

Found 7 papers, 3 papers with code

Matroid Semi-Bandits in Sublinear Time

no code implementations28 May 2024 Ruo-Chun Tzeng, Naoto Ohsaka, Kaito Ariu

We study the matroid semi-bandits problem, where at each round the learner plays a subset of $K$ arms from a feasible set, and the goal is to maximize the expected cumulative linear rewards.

Best Arm Identification with Fixed Budget: A Large Deviation Perspective

1 code implementation NeurIPS 2023 Po-An Wang, Ruo-Chun Tzeng, Alexandre Proutiere

In particular, we present \sred (Continuous Rejects), a truly adaptive algorithm that can reject arms in {\it any} round based on the observed empirical gaps between the rewards of various arms.

Multi-Armed Bandits

Improved analysis of randomized SVD for top-eigenvector approximation

no code implementations16 Feb 2022 Ruo-Chun Tzeng, Po-An Wang, Florian Adriaens, Aristides Gionis, Chi-Jen Lu

We present a novel analysis of the randomized SVD algorithm of \citet{halko2011finding} and derive tight bounds in many cases of interest.

Fast Pure Exploration via Frank-Wolfe

no code implementations NeurIPS 2021 Po-An Wang, Ruo-Chun Tzeng, Alexandre Proutiere

For this problem, instance-specific lower bounds on the expected sample complexity reveal the optimal proportions of arm draws an Oracle algorithm would apply.

Discovering conflicting groups in signed networks

1 code implementation NeurIPS 2020 Ruo-Chun Tzeng, Bruno Ordozgoiti, Aristides Gionis

In this paper we study the problem of detecting $k$ conflicting groups in a signed network.


Ego-CNN: An Ego Network-based Representation of Graphs Detecting Critical Structures

no code implementations ICLR 2018 Ruo-Chun Tzeng, Shan-Hung Wu

While existing graph embedding models can generate useful embedding vectors that perform well on graph-related tasks, what valuable information can be jointly learned by a graph embedding model is less discussed.

Graph Embedding

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