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08/12/2022
Pre-training Tasks for User Intent Detection and Embedding Retrieval in E-commerce Search
BERT-style models pre-trained on the general corpus (e.g., Wikipedia) an...
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01/09/2022
Smooth Nested Simulation: Bridging Cubic and Square Root Convergence Rates in High Dimensions
Nested simulation concerns estimating functionals of a conditional expec...
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08/28/2021
Self-fulfilling Bandits: Endogeneity Spillover and Dynamic Selection in Algorithmic Decision-making
In this paper, we study endogeneity problems in algorithmic decision-mak...
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07/19/2021
High-Dimensional Simulation Optimization via Brownian Fields and Sparse Grids
High-dimensional simulation optimization is notoriously challenging. We ...
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05/09/2021
Surrogate-Based Simulation Optimization
Simulation models are widely used in practice to facilitate decision-mak...
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03/06/2021
Causal Reinforcement Learning: An Instrumental Variable Approach
In the standard data analysis framework, data is first collected (once f...
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10/14/2020
Sample and Computationally Efficient Simulation Metamodeling in High Dimensions
Stochastic kriging has been widely employed for simulation metamodeling ...
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02/20/2020
MODMA dataset: a Multi-modal Open Dataset for Mental-disorder Analysis
According to the World Health Organization, the number of mental disorde...
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02/20/2020
MODMA dataset: a Multi-model Open Dataset for Mental-disorder Analysis
According to the World Health Organization, the number of mental disorde...
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11/20/2019
Rule-Guided Compositional Representation Learning on Knowledge Graphs
Representation learning on a knowledge graph (KG) is to embed entities a...
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06/12/2019
Knowledge Gradient for Selection with Covariates: Consistency and Computation
Knowledge gradient is a design principle for developing Bayesian sequent...
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03/14/2019
Distributionally Robust Selection of the Best
Specifying a proper input distribution is often a challenging task in si...
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12/07/2018
Local Distribution in Neighborhood for Classification
The k-nearest-neighbor method performs classification tasks for a query ...
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03/07/2018
Scalable Stochastic Kriging with Markovian Covariances
Stochastic kriging is a popular technique for simulation metamodeling du...
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02/02/2018
Stochastic Kriging for Inadequate Simulation Models
Stochastic kriging is a popular metamodeling technique for representing ...
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10/07/2017
Ranking and Selection with Covariates for Personalized Decision Making
We consider a ranking and selection problem in the context of personaliz...
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03/26/2017
Multivariate Regression with Gross Errors on Manifold-valued Data
We consider the topic of multivariate regression on manifold-valued outp...
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01/16/2017
Sparse Kernel Canonical Correlation Analysis via ℓ_1-regularization
Canonical correlation analysis (CCA) is a multivariate statistical techn...
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01/11/2017
Multivariate Regression with Grossly Corrupted Observations: A Robust Approach and its Applications
This paper studies the problem of multivariate linear regression where a...
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02/19/2014