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08/25/2023
Nonparametric Additive Value Functions: Interpretable Reinforcement Learning with an Application to Surgical Recovery
We propose a nonparametric additive model for estimating interpretable v...
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06/12/2023
FADI: Fast Distributed Principal Component Analysis With High Accuracy for Large-Scale Federated Data
Principal component analysis (PCA) is one of the most popular methods fo...
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05/31/2023
Knowledge Graph Embedding with Electronic Health Records Data via Latent Graphical Block Model
Due to the increasing adoption of electronic health records (EHR), large...
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05/19/2023
LATTE: Label-efficient Incident Phenotyping from Longitudinal Electronic Health Records
Electronic health record (EHR) data are increasingly used to support rea...
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01/28/2023
Combinatorial Inference on the Optimal Assortment in Multinomial Logit Models
Assortment optimization has received active explorations in the past few...
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06/11/2022
Federated Offline Reinforcement Learning
Evidence-based or data-driven dynamic treatment regimes are essential fo...
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02/01/2022
Penalized Estimation of Frailty-Based Illness-Death Models for Semi-Competing Risks
Semi-competing risks refers to the survival analysis setting where the o...
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10/01/2021
Lagrangian Inference for Ranking Problems
We propose a novel combinatorial inference framework to conduct general ...
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08/23/2021
StarTrek: Combinatorial Variable Selection with False Discovery Rate Control
Variable selection on the large-scale networks has been extensively stud...
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05/21/2021
BELT: Block-wise Missing Embedding Learning Transformer
Matrix completion has attracted attention in many fields, including stat...
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10/28/2020
Combinatorial-Probabilistic Trade-Off: Community Properties Test in the Stochastic Block Models
In this paper, we propose an inferential framework testing the general c...
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06/29/2020
Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization
Real-world large-scale datasets are heteroskedastic and imbalanced – lab...
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06/23/2020
Expert-Supervised Reinforcement Learning for Offline Policy Learning and Evaluation
Offline Reinforcement Learning (RL) is a promising approach for learning...
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02/18/2020
MoTiAC: Multi-Objective Actor-Critics for Real-Time Bidding
Online real-time bidding (RTB) is known as a complex auction game where ...
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05/28/2019
Estimating and Inferring the Maximum Degree of Stimulus-Locked Time-Varying Brain Connectivity Networks
Neuroscientists have enjoyed much success in understanding brain functio...
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05/24/2019
Inference of Dynamic Graph Changes for Functional Connectome
Dynamic functional connectivity is an effective measure to characterize ...
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06/13/2018
On Tighter Generalization Bound for Deep Neural Networks: CNNs, ResNets, and Beyond
Our paper proposes a generalization error bound for a general family of ...
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09/20/2017
Inter-Subject Analysis: Inferring Sparse Interactions with Dense Intra-Graphs
We develop a new modeling framework for Inter-Subject Analysis (ISA). Th...
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07/28/2017
Adaptive Inferential Method for Monotone Graph Invariants
We consider the problem of undirected graphical model inference. In many...
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12/29/2016
Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization
We propose a general theory for studying the geometry of nonconvex objec...
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08/10/2016
Combinatorial Inference for Graphical Models
We propose a new family of combinatorial inference problems for graphica...
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12/28/2015
Post-Regularization Inference for Dynamic Nonparanormal Graphical Models
We propose a novel class of dynamic nonparanormal graphical models, whic...
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04/23/2015
Graphical Fermat's Principle and Triangle-Free Graph Estimation
We consider the problem of estimating undirected triangle-free graphs of...
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03/10/2015
Post-Regularization 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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02/05/2015
