
Trading the System Efficiency for the Income Equality of Drivers in Rideshare
Several scientific studies have reported the existence of the income gap...
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A Unified Model for the Twostage OfflinethenOnline Resource Allocation
With the popularity of the Internet, traditional offline resource alloca...
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Neural Contextual Bandits with Deep Representation and Shallow Exploration
We study a general class of contextual bandits, where each contextactio...
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Grouplevel Fairness Maximization in Online Bipartite Matching
In typical online matching problems, the goal is to maximize the number ...
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Faster Convergence of Stochastic Gradient Langevin Dynamics for NonLogConcave Sampling
We establish a new convergence analysis of stochastic gradient Langevin ...
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Improved Approximation Algorithms for StochasticMatching Problems
We consider the Stochastic Matching problem, which is motivated by appli...
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A Finite Time Analysis of Two TimeScale Actor Critic Methods
Actorcritic (AC) methods have exhibited great empirical success compare...
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MOTS: Minimax Optimal Thompson Sampling
Thompson sampling is one of the most widely used algorithms for many onl...
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Double ExplorethenCommit: Asymptotic Optimality and Beyond
We study the twoarmed bandit problem with subGaussian rewards. The expl...
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Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms During HighDemand Hours
Rideshare platforms, when assigning requests to drivers, tend to maximiz...
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A FiniteTime Analysis of QLearning with Neural Network Function Approximation
Qlearning with neural network function approximation (neural Qlearning...
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Rank Aggregation via Heterogeneous Thurstone Preference Models
We propose the Heterogeneous Thurstone Model (HTM) for aggregating ranke...
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Mix and Match: Markov Chains Mixing Times for Matching in Rideshare
Rideshare platforms such as Uber and Lyft dynamically dispatch drivers t...
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Sample Efficient Policy Gradient Methods with Recursive Variance Reduction
Improving the sample efficiency in reinforcement learning has been a lon...
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An Improved Convergence Analysis of Stochastic VarianceReduced Policy Gradient
We revisit the stochastic variancereduced policy gradient (SVRPG) metho...
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Sample Efficient Stochastic VarianceReduced Cubic Regularization Method
We propose a sample efficient stochastic variancereduced cubic regulari...
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Balancing Relevance and Diversity in Online Bipartite Matching via Submodularity
In bipartite matching problems, vertices on one side of a bipartite grap...
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Finding Local Minima via Stochastic Nested Variance Reduction
We propose two algorithms that can find local minima faster than the sta...
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Stochastic Nested Variance Reduction for Nonconvex Optimization
We study finitesum nonconvex optimization problems, where the objective...
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A PTAS for a Class of Stochastic Dynamic Programs
We develop a framework for obtaining polynomial time approximation schem...
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Attenuate Locally, Win Globally: An Attenuationbased Framework for Online Stochastic Matching with Timeouts
Online matching problems have garnered significant attention in recent y...
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Stochastic VarianceReduced Cubic Regularized Newton Method
We propose a stochastic variancereduced cubic regularized Newton method...
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Stochastic VarianceReduced Hamilton Monte Carlo Methods
We propose a fast stochastic Hamilton Monte Carlo (HMC) method, for samp...
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Onion Curve: A Space Filling Curve with NearOptimal Clustering
Space filling curves (SFCs) are widely used in the design of indexes for...
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Thirdorder Smoothness Helps: Even Faster Stochastic Optimization Algorithms for Finding Local Minima
We propose stochastic optimization algorithms that can find local minima...
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Allocation Problems in RideSharing Platforms: Online Matching with Offline Reusable Resources
Bipartite matching markets pair agents on one side of a market with agen...
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Algorithms to Approximate ColumnSparse Packing Problems
Columnsparse packing problems arise in several contexts in both determi...
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Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization
We present a unified framework to analyze the global convergence of Lang...
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Speeding Up Latent Variable Gaussian Graphical Model Estimation via Nonconvex Optimizations
We study the estimation of the latent variable Gaussian graphical model ...
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Communicationefficient Distributed Estimation and Inference for Transelliptical Graphical Models
We propose communicationefficient distributed estimation and inference ...
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Pan Xu
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