Search Results for author: Xiuyuan Lu

Found 7 papers, 1 papers with code

Evaluating Predictive Distributions: Does Bayesian Deep Learning Work?

1 code implementation9 Oct 2021 Ian Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Botao Hao, Morteza Ibrahimi, Dieterich Lawson, Xiuyuan Lu, Brendan O'Donoghue, Benjamin Van Roy

This paper introduces \textit{The Neural Testbed}, which provides tools for the systematic evaluation of agents that generate such predictions.

Evaluating Probabilistic Inference in Deep Learning: Beyond Marginal Predictions

no code implementations20 Jul 2021 Xiuyuan Lu, Ian Osband, Benjamin Van Roy, Zheng Wen

A fundamental challenge for any intelligent system is prediction: given some inputs $X_1,.., X_\tau$ can you predict outcomes $Y_1,.., Y_\tau$.

Reinforcement Learning, Bit by Bit

no code implementations6 Mar 2021 Xiuyuan Lu, Benjamin Van Roy, Vikranth Dwaracherla, Morteza Ibrahimi, Ian Osband, Zheng Wen

Reinforcement learning agents have demonstrated remarkable achievements in simulated environments.

Event-based Motion Segmentation with Spatio-Temporal Graph Cuts

no code implementations16 Dec 2020 Yi Zhou, Guillermo Gallego, Xiuyuan Lu, SiQi Liu, Shaojie Shen

We have developed a method to identify independently moving objects acquired with an event-based camera, i. e., to solve the event-based motion segmentation problem.

Motion Segmentation Scene Understanding

Information-Theoretic Confidence Bounds for Reinforcement Learning

no code implementations NeurIPS 2019 Xiuyuan Lu, Benjamin Van Roy

We integrate information-theoretic concepts into the design and analysis of optimistic algorithms and Thompson sampling.

Ensemble Sampling

no code implementations NeurIPS 2017 Xiuyuan Lu, Benjamin Van Roy

Thompson sampling has emerged as an effective heuristic for a broad range of online decision problems.

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