85 citations · 155 across the 17 of their papers we have counts for
8 papers · 1 filter
Adversarial Linear Contextual Bandits with Graph-Structured Side Observations
Lingda Wang, Bingcong Li, Huozhi Zhou +3
This paper studies the adversarial graphical contextual bandits, a variant of adversarial multi-armed bandits that leverage two categories of the most common side information: \emp…
Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms
Arjun Gupta, E. A. Huerta, Zhizhen Zhao +1
Myocardial infarction is the leading cause of death worldwide. In this paper, we design domain-inspired neural network models to detect myocardial infarction. First, we study the c…
Nearly Optimal Algorithms for Piecewise-Stationary Cascading Bandits
Lingda Wang, Huozhi Zhou, Bingcong Li +2
Cascading bandit (CB) is a popular model for web search and online advertising, where an agent aims to learn the most attractive items out of a ground set of size during th…
Multi-Frequency Vector Diffusion Maps
Yifeng Fan, Zhizhen Zhao
We introduce multi-frequency vector diffusion maps (MFVDM), a new framework for organizing and analyzing high dimensional datasets. The new method is a mathematical and algorithmic…
Unsupervised Co-Learning on -Manifolds Across Irreducible Representations
Yifeng Fan, Tingran Gao, Zhizhen Zhao
We introduce a novel co-learning paradigm for manifolds naturally equipped with a group action, motivated by recent developments on learning a manifold from attached fibre bundle s…
Max-Sliced Wasserstein Distance and its use for GANs
Ishan Deshpande, Yuan-Ting Hu, Ruoyu Sun +6
Generative adversarial nets (GANs) and variational auto-encoders have significantly improved our distribution modeling capabilities, showing promise for dataset augmentation, image…