58 citations · 249 across the 21 of their papers we have counts for
8 papers · 1 filter
Reinforcement Learning with Efficient Active Feature Acquisition
Haiyan Yin, Yingzhen Li, Sinno Jialin Pan +2
Solving real-life sequential decision making problems under partial observability involves an exploration-exploitation problem. To be successful, an agent needs to efficiently gath…
A Study on Efficiency in Continual Learning Inspired by Human Learning
Philip J. Ball, Yingzhen Li, Angus Lamb +1
Humans are efficient continual learning systems; we continually learn new skills from birth with finite cells and resources. Our learning is highly optimized both in terms of capac…
DRIFT: Deep Reinforcement Learning for Functional Software Testing
Luke Harries, Rebekah Storan Clarke, Timothy Chapman +10
Efficient software testing is essential for productive software development and reliable user experiences. As human testing is inefficient and expensive, automated software testing…
Instructions and Guide for Diagnostic Questions: The NeurIPS 2020 Education Challenge
Zichao Wang, Angus Lamb, Evgeny Saveliev +9
Digital technologies are becoming increasingly prevalent in education, enabling personalized, high quality education resources to be accessible by students across the world. Import…
Meta-Learning Divergences of Variational Inference
Ruqi Zhang, Yingzhen Li, Christopher De Sa +2
Variational inference (VI) plays an essential role in approximate Bayesian inference due to its computational efficiency and broad applicability. Crucial to the performance of VI i…
VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data
Chao Ma, Sebastian Tschiatschek, José Miguel Hernández-Lobato +2
Deep generative models often perform poorly in real-world applications due to the heterogeneity of natural data sets. Heterogeneity arises from data containing different types of f…
A Causal View on Robustness of Neural Networks
Cheng Zhang, Kun Zhang, Yingzhen Li
We present a causal view on the robustness of neural networks against input manipulations, which applies not only to traditional classification tasks but also to general measuremen…
Educational Question Mining At Scale: Prediction, Analysis and Personalization
Zichao Wang, Sebastian Tschiatschek, Simon Woodhead +4
Online education platforms enable teachers to share a large number of educational resources such as questions to form exercises and quizzes for students. With large volumes of avai…