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05/29/2023
Cross-Entropy Estimators for Sequential Experiment Design with Reinforcement Learning
Reinforcement learning can effectively learn amortised design policies f...
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02/20/2023
Transformed Distribution Matching for Missing Value Imputation
We study the problem of imputing missing values in a dataset, which has ...
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02/02/2023
The Contextual Lasso: Sparse Linear Models via Deep Neural Networks
Sparse linear models are a gold standard tool for interpretable machine ...
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02/10/2022
Bayesian Optimisation for Mixed-Variable Inputs using Value Proposals
Many real-world optimisation problems are defined over both categorical ...
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02/02/2022
Optimizing Sequential Experimental Design with Deep Reinforcement Learning
Bayesian approaches developed to solve the optimal design of sequential ...
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02/19/2021
TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learning
We propose a novel approach to interactive theorem-proving (ITP) using d...
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06/28/2020
EAPS: Edge-Assisted Predictive Sleep Scheduling for 802.11 IoT Stations
The broad deployment of 802.11 (a.k.a., WiFi) access points and signific...
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02/27/2017
Semi-parametric Network Structure Discovery Models
We propose a network structure discovery model for continuous observatio...
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09/14/2016
Gray-box inference for structured Gaussian process models
We develop an automated variational inference method for Bayesian struct...
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09/02/2016