
On AO*, Proof Number Search and Minimax Search
We discuss the interconnections between AO*, adversarial gamesearching ...
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On Computation Complexity of True Proof Number Search
We point out that the computation of true proof and disproof numbers for...
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Optimal Full Ranking from Pairwise Comparisons
We consider the problem of ranking n players from partial pairwise compa...
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SDP Achieves Exact Minimax Optimality in Phase Synchronization
We study the phase synchronization problem with noisy measurements Y=z^*...
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SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II
AlphaStar, the AI that reaches GrandMaster level in StarCraft II, is a r...
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Residual Matrix Product State for Machine Learning
Tensor network (TN), which originates from quantum physics, shows broad ...
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Exact Minimax Estimation for Phase Synchronization
We study the phase synchronization problem with measurements Y=z^*z^*H+σ...
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Convergence Rates of Empirical Bayes Posterior Distributions: A Variational Perspective
We study the convergence rates of empirical Bayes posterior distribution...
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Partial Recovery for Topk Ranking: Optimality of MLE and SubOptimality of Spectral Method
Given partially observed pairwise comparison data generated by the Bradl...
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Model Repair: Robust Recovery of OverParameterized Statistical Models
A new type of robust estimation problem is introduced where the goal is ...
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Iterative Algorithm for Discrete Structure Recovery
We propose a general modeling and algorithmic framework for discrete str...
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Testing Equivalence of Clustering
In this paper, we test whether two datasets share a common clustering st...
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A Sensitivity Analysis of AttentionGated Convolutional Neural Networks for Sentence Classification
Recently, AttentionGated Convolutional Neural Networks (AGCNNs) perform...
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NaturalLogarithmRectified Activation Function in Convolutional Neural Networks
Activation functions play a key role in providing remarkable performance...
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On Hard Exploration for Reinforcement Learning: a Case Study in Pommerman
How to best explore in domains with sparse, delayed, and deceptive rewar...
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Minimax rates in sparse, highdimensional changepoint detection
We study the detection of a sparse change in a highdimensional mean vec...
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Skynet: A Top Deep RL Agent in the Inaugural Pommerman Team Competition
The Pommerman Team Environment is a recently proposed benchmark which in...
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Safer Deep RL with Shallow MCTS: A Case Study in Pommerman
Safe reinforcement learning has many variants and it is still an open re...
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Generative Adversarial Nets for Robust Scatter Estimation: A Proper Scoring Rule Perspective
Robust scatter estimation is a fundamental task in statistics. The recen...
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Optimal estimation of variance in nonparametric regression with random design
Consider the heteroscedastic nonparametric regression model with random ...
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Bayesian Model Selection with Graph Structured Sparsity
We propose a general algorithmic framework for Bayesian model selection....
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Continual Match Based Training in Pommerman: Technical Report
Continual learning is the ability of agents to improve their capacities ...
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Minimax Rates in Network Analysis: Graphon Estimation, Community Detection and Hypothesis Testing
This paper surveys some recent developments in fundamental limits and op...
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Mixing Time of MetropolisHastings for Bayesian Community Detection
We study the computational complexity of a MetropolisHastings algorithm...
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Robust Estimation and Generative Adversarial Nets
Robust estimation under Huber's ϵcontamination model has become an impo...
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An AttentionGated Convolutional Neural Network for Sentence Classification
The classification task of sentences is very challenging because of the ...
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IoT Security: An EndtoEnd View and Case Study
In this paper, we present an endtoend view of IoT security and privacy...
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Nfold Superposition: Improving Neural Networks by Reducing the Noise in Feature Maps
Considering the use of Fully Connected (FC) layer limits the performance...
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Density Estimation with Contaminated Data: Minimax Rates and Theory of Adaptation
This paper studies density estimation under pointwise loss in the settin...
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Convergence Rates of Variational Posterior Distributions
We study convergence rates of variational posterior distributions for no...
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Phase Transitions in Approximate Ranking
We study the problem of approximate ranking from observations of pairwis...
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Semiautomated Signal Surveying Using Smartphones and Floorplans
Location fingerprinting locates devices based on pattern matching signal...
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Testing for Global Network Structure Using Small Subgraph Statistics
We study the problem of testing for community structure in networks usin...
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Stochastic Canonical Correlation Analysis
We tightly analyze the sample complexity of CCA, provide a learning algo...
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Robust Regression via Mutivariate Regression Depth
This paper studies robust regression in the settings of Huber's ϵcontam...
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Community Detection in DegreeCorrected Block Models
Community detection is a central problem of network data analysis. Given...
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Exact Exponent in Optimal Rates for Crowdsourcing
In many machine learning applications, crowdsourcing has become the prim...
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Optimal Estimation and Completion of Matrices with Biclustering Structures
Biclustering structures in data matrices were first formalized in a semi...
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Achieving Optimal Misclassification Proportion in Stochastic Block Model
Community detection is a fundamental statistical problem in network data...
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Sparse CCA via Precision Adjusted Iterative Thresholding
Sparse Canonical Correlation Analysis (CCA) has received considerable at...
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Posterior Contraction Rates of the Phylogenetic Indian Buffet Processes
By expressing prior distributions as general stochastic processes, nonpa...
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Chao Gao
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Assistant Professor, Department of Statistics and the College at University of Chicago