Yitao Liang

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Handling Missing Data in Decision Trees: A Probabilistic Approach

Decision trees are a popular family of models due to their attractive pr...
06/29/2020 ∙ by Pasha Khosravi, et al. ∙ 12 ∙ share

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On Effective Parallelization of Monte Carlo Tree Search

Despite its groundbreaking success in Go and computer games, Monte Carlo...
06/15/2020 ∙ by Anji Liu, et al. ∙ 0 ∙ share

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Off-Policy Deep Reinforcement Learning with Analogous Disentangled Exploration

Off-policy reinforcement learning (RL) is concerned with learning a rewa...
02/25/2020 ∙ by Anji Liu, et al. ∙ 13 ∙ share

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LaTeS: Latent Space Distillation for Teacher-Student Driving Policy Learning

We describe a policy learning approach to map visual inputs to driving c...
12/06/2019 ∙ by Albert Zhao, et al. ∙ 19 ∙ share

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On Tractable Computation of Expected Predictions

Computing expected predictions has many interesting applications in area...
10/05/2019 ∙ by Pasha Khosravi, et al. ∙ 14 ∙ share

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What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features

While discriminative classifiers often yield strong predictive performan...
03/05/2019 ∙ by Pasha Khosravi, et al. ∙ 16 ∙ share

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Learning Logistic Circuits

This paper proposes a new classification model called logistic circuits....
02/27/2019 ∙ by Yitao Liang, et al. ∙ 8 ∙ share

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Horizon: Facebook's Open Source Applied Reinforcement Learning Platform

In this paper we present Horizon, Facebook's open source applied reinfor...
11/01/2018 ∙ by Jason Gauci, et al. ∙ 0 ∙ share

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Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing

Incentive mechanisms for crowdsourcing are designed to incentivize finan...
06/01/2018 ∙ by Zehong Hu, et al. ∙ 0 ∙ share

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A Semantic Loss Function for Deep Learning with Symbolic Knowledge

This paper develops a novel methodology for using symbolic knowledge in ...
11/29/2017 ∙ by Jingyi Xu, et al. ∙ 0 ∙ share

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Yitao Liang

Featured Co-authors

Yang Liu

Ji Liu

Jie Zhang

Stefano Soatto

Guy Van den Broeck

Jianshu Chen

Tong He

Haibin Huang

Antonio Vergari

Yuchen He

Jingyi Xu

Handling Missing Data in Decision Trees: A Probabilistic Approach

On Effective Parallelization of Monte Carlo Tree Search

Off-Policy Deep Reinforcement Learning with Analogous Disentangled Exploration

LaTeS: Latent Space Distillation for Teacher-Student Driving Policy Learning

On Tractable Computation of Expected Predictions

What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features

Learning Logistic Circuits

Horizon: Facebook's Open Source Applied Reinforcement Learning Platform

Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing

A Semantic Loss Function for Deep Learning with Symbolic Knowledge