
Semiparametric Estimation for Causal Mediation Analysis with Multiple Causally Ordered Mediators
Causal mediation analysis concerns the pathways through which a treatmen...
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Some Doubly and Multiply Robust Estimators of Controlled Direct Effects
This letter introduces several doubly, triply, and quadruply robust esti...
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Projection Method for Saddle Points of Energy Functional in H^1 Metric
Saddle points play important roles as the transition states of activated...
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What Can We Learn from Collective Human Opinions on Natural Language Inference Data?
Despite the subjective nature of many NLP tasks, most NLU evaluations ha...
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Bayesian Hierarchical Models for HighDimensional Mediation Analysis with Coordinated Selection of Correlated Mediators
We consider Bayesian highdimensional mediation analysis to identify amo...
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Deep Reinforcement Learning for Online Dialogue State Tracking
Dialogue state tracking (DST) is a crucial module in dialogue management...
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Filling the Gap of Utteranceaware and Speakeraware Representation for Multiturn Dialogue
A multiturn dialogue is composed of multiple utterances from two or mor...
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Composing Answer from Multispans for Reading Comprehension
This paper presents a novel method to generate answers for nonextractio...
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Taskspecific Objectives of Pretrained Language Models for Dialogue Adaptation
Pretrained Language Models (PrLMs) have been widely used as backbones i...
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Bayesian Sparse Mediation Analysis with Targeted Penalization of Natural Indirect Effects
Causal mediation analysis aims to characterize an exposure's effect on a...
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Machine Learning and Control Theory
We survey in this article the connections between Machine Learning and C...
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Towards Robustifying NLI Models Against Lexical Dataset Biases
While deep learning models are making fast progress on the task of Natur...
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The Curse of Performance Instability in Analysis Datasets: Consequences, Source, and Suggestions
We find that the performance of stateoftheart models on Natural Langu...
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Enumerating Chemical Graphs with Two Disjoint Cycles Satisfying Given Path Frequency Specifications
Enumerating chemical graphs satisfying given constraints is a fundamenta...
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Explicit Estimation of Derivatives from Data and Differential Equations by Gaussian Process Regression
In this work, we employ the Bayesian inference framework to solve the pr...
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Stochastic Modified Equations for Continuous Limit of Stochastic ADMM
Stochastic version of alternating direction method of multiplier (ADMM) ...
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Regime Switching Bandits
We study a multiarmed bandit problem where the rewards exhibit regimes...
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Finegrained Attention and Featuresharing Generative Adversarial Networks for Single Image SuperResolution
The traditional superresolution methods that aim to minimize the mean s...
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Semanticsaware BERT for Language Understanding
The latest work on language representations carefully integrates context...
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DCMN+: Dual CoMatching Network for Multichoice Reading Comprehension
Multichoice reading comprehension is a challenging task to select an an...
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Dual CoMatching Network for Multichoice Reading Comprehension
Multichoice reading comprehension is a challenging task that requires c...
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Dependency or Span, EndtoEnd Uniform Semantic Role Labeling
Semantic role labeling (SRL) aims to discover the predicateargument stru...
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I Know What You Want: Semantic Learning for Text Comprehension
Who did what to whom is a major focus in natural language understanding,...
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Regressionwithresiduals Estimation of Marginal Effects: A Method of Adjusting for Treatmentinduced Confounders that may also be Moderators
Treatmentinduced confounders complicate analyses of timevarying treatm...
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Residual Balancing Weights for Marginal Structural Models: with Application to Analyses of Timevarying Treatments and Causal Mediation
Treatmentinduced confounding arises in analyses of timevarying treatme...
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Scalable Algorithms for Learning HighDimensional Linear Mixed Models
Linear mixed models (LMMs) are used extensively to model dependecies of ...
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varbvs: Fast Variable Selection for Largescale Regression
We introduce varbvs, a suite of functions written in R and MATLAB for re...
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Bayesian Approximate Kernel Regression with Variable Selection
Nonlinear kernel regression models are often used in statistics and mach...
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Xiang Zhou
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