17 citations · 25 across the 4 of their papers we have counts for
8 papers
Influence Diagram Bandits: Variational Thompson Sampling for Structured Bandit Problems
Tong Yu, Branislav Kveton, Zheng Wen +2
We propose a novel framework for structured bandits, which we call an influence diagram bandit. Our framework captures complex statistical dependencies between actions, latent vari…
Customized Graph Embedding: Tailoring Embedding Vectors to different Applications
Bitan Hou, Yujing Wang, Ming Zeng +4
Graph is a natural representation of data for a variety of real-word applications, such as knowledge graph mining, social network analysis and biological network comparison. For th…
Adaptive Stress Testing: Finding Likely Failure Events with Reinforcement Learning
Ritchie Lee, Ole J. Mengshoel, Anshu Saksena +5
Finding the most likely path to a set of failure states is important to the analysis of safety-critical systems that operate over a sequence of time steps, such as aircraft collisi…
Understanding and Improving Recurrent Networks for Human Activity Recognition by Continuous Attention
Ming Zeng, Haoxiang Gao, Tong Yu +4
Deep neural networks, including recurrent networks, have been successfully applied to human activity recognition. Unfortunately, the final representation learned by recurrent netwo…
CADDeLaG: Framework for distributed anomaly detection in large dense graph sequences
Aniruddha Basak, Kamalika Das, Ole J. Mengshoel
Random walk based distance measures for graphs such as commute-time distance are useful in a variety of graph algorithms, such as clustering, anomaly detection, and creating low di…
Semi-Supervised Convolutional Neural Networks for Human Activity Recognition
Ming Zeng, Tong Yu, Xiao Wang +3
Labeled data used for training activity recognition classifiers are usually limited in terms of size and diversity. Thus, the learned model may not generalize well when used in rea…