
Convergent Policy Optimization for Safe Reinforcement Learning
We study the safe reinforcement learning problem with nonlinear function...
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Direct Estimation of Differential Functional Graphical Models
We consider the problem of estimating the difference between two functio...
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FuDGE: Functional Differential Graph Estimation with fully and discretely observed curves
We consider the problem of estimating the difference between two functio...
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Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees
Graph representation learning is a ubiquitous task in machine learning w...
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Natural ActorCritic Converges Globally for Hierarchical Linear Quadratic Regulator
Multiagent reinforcement learning has been successfully applied to a nu...
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Posterior Ratio Estimation for Latent Variables
Density Ratio Estimation has attracted attention from machine learning c...
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Partially Linear Additive Gaussian Graphical Models
We propose a partially linear additive Gaussian graphical model (PLAGGM...
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An InfluenceReceptivity Model for Topic based Information Cascades
We consider the problem of estimating the latent structure of a social n...
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Uniform Inference for Highdimensional Quantile Regression: Linear Functionals and Regression Rank Scores
Hypothesis tests in models whose dimension far exceeds the sample size c...
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Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and Highdimensional Data
Sketching techniques have become popular for scaling up machine learning...
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Efficient Distributed Learning with Sparsity
We propose a novel, efficient approach for distributed sparse learning i...
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Distributed MultiTask Learning with Shared Representation
We study the problem of distributed multitask learning with shared repr...
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PostRegularization Inference for Dynamic Nonparanormal Graphical Models
We propose a novel class of dynamic nonparanormal graphical models, whic...
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Distributed Multitask Learning
We consider the problem of distributed multitask learning, where each m...
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PostRegularization Confidence Bands for High Dimensional Nonparametric Models with Local Sparsity
We propose a novel high dimensional nonparametric model named ATLAS whic...
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A General Framework for Robust Testing and Confidence Regions in HighDimensional Quantile Regression
We propose a robust inferential procedure for assessing uncertainties of...
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Inference for Sparse Conditional Precision Matrices
Given n i.i.d. observations of a random vector (X,Z), where X is a high...
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Optimal variable selection in multigroup sparse discriminant analysis
This article considers the problem of multigroup classification in the ...
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Estimating Undirected Graphs Under Weak Assumptions
We consider the problem of providing nonparametric confidence guarantees...
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Optimal Feature Selection in HighDimensional Discriminant Analysis
We consider the highdimensional discriminant analysis problem. For this...
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Graph Estimation From Multiattribute Data
Many real world network problems often concern multivariate nodal attrib...
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Recovering Blockstructured Activations Using Compressive Measurements
We consider the problems of detection and localization of a contiguous b...
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Variance function estimation in highdimensions
We consider the highdimensional heteroscedastic regression model, where...
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Ultrahigh Dimensional Multiple Output Learning With Simultaneous Orthogonal Matching Pursuit: A Sure Screening Approach
We propose a novel application of the Simultaneous Orthogonal Matching P...
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Estimating Networks With Jumps
We study the problem of estimating a temporally varying coefficient and ...
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Union Support Recovery in Multitask Learning
We sharply characterize the performance of different penalization scheme...
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Distributed Stochastic MultiTask Learning with Graph Regularization
We propose methods for distributed graphbased multitask learning that ...
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Recovery of simultaneous low rank and twoway sparse coefficient matrices, a nonconvex approach
We study the problem of recovery of matrices that are simultaneously low...
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Learning InfluenceReceptivity Network Structure with Guarantee
Traditional works on community detection from observations of informatio...
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Highdimensional Varying Index Coefficient Models via Stein's Identity
We study the parameter estimation problem for a singleindex varying coe...
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Joint Nonparametric Precision Matrix Estimation with Confounding
We consider the problem of precision matrix estimation where, due to ext...
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Provable Gaussian Embedding with One Observation
The success of machine learning methods heavily relies on having an appr...
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Highdimensional Index Volatility Models via Stein's Identity
In this paper, we consider estimating the parametric components of index...
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Twosample inference for highdimensional Markov networks
Markov networks are frequently used in sciences to represent conditional...
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Simultaneous Inference for Pairwise Graphical Models with Generalized Score Matching
Probabilistic graphical models provide a flexible yet parsimonious frame...
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Tensor Canonical Correlation Analysis
In many applications, such as classification of images or videos, it is ...
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Estimating Differential Latent Variable Graphical Models with Applications to Brain Connectivity
Differential graphical models are designed to represent the difference b...
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Constrained High Dimensional Statistical Inference
In typical high dimensional statistical inference problems, confidence i...
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Postselection inference on highdimensional varyingcoefficient quantile regression model
Quantile regression has been successfully used to study heterogeneous an...
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Mladen Kolar
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Associate Professor at University of Chicago Booth School of Business