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07/08/2023
Market Design for Dynamic Pricing and Pooling in Capacitated Networks
We study a market mechanism that sets edge prices to incentivize strateg...
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06/21/2023
Online Resource Allocation with Convex-set Machine-Learned Advice
Decision-makers often have access to a machine-learned prediction about ...
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06/16/2023
Memory-Constrained Algorithms for Convex Optimization via Recursive Cutting-Planes
We propose a family of recursive cutting-plane algorithms to solve feasi...
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06/12/2023
DRCFS: Doubly Robust Causal Feature Selection
Knowing the features of a complex system that are highly relevant to a p...
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02/14/2023
Non-stationary Contextual Bandits and Universal Learning
We study the fundamental limits of learning in contextual bandits, where...
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02/14/2023
Effective Dimension in Bandit Problems under Censorship
In this paper, we study both multi-armed and contextual bandit problems ...
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02/09/2023
Quadratic Memory is Necessary for Optimal Query Complexity in Convex Optimization: Center-of-Mass is Pareto-Optimal
We give query complexity lower bounds for convex optimization and the re...
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02/03/2023
Multi-channel Autobidding with Budget and ROI Constraints
In digital online advertising, advertisers procure ad impressions simult...
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12/31/2022
Contextual Bandits and Optimistically Universal Learning
We consider the contextual bandit problem on general action and context ...
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11/20/2022
Additional Results and Extensions for the paper "Probabilistic bounds on the k-Traveling Salesman Problem and the Traveling Repairman Problem”
This technical report provides additional results for the main paper “Pr...
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11/20/2022
Probabilistic bounds on the k-Traveling Salesman Problem and the Traveling Repairman Problem
The k-traveling salesman problem (k-TSP) seeks a tour of minimal length ...
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10/13/2022
Sample-Then-Optimize Batch Neural Thompson Sampling
Bayesian optimization (BO), which uses a Gaussian process (GP) as a surr...
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09/10/2022
Fairness in the Autobidding World with Machine-learned Advice
The increasing availability of real-time data has fueled the prevalence ...
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08/20/2022
Weighted Maximum Entropy Inverse Reinforcement Learning
We study inverse reinforcement learning (IRL) and imitation learning (IM...
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06/14/2022
On Provably Robust Meta-Bayesian Optimization
Bayesian optimization (BO) has become popular for sequential optimizatio...
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05/28/2022
Federated Neural Bandit
Recent works on neural contextual bandit have achieved compelling perfor...
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05/05/2022
Optimal Information Provision for Strategic Hybrid Workers
We study the problem of information provision by a strategic central pla...
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03/09/2022
Universal Regression with Adversarial Responses
We provide algorithms for regression with adversarial responses under la...
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02/28/2022
Rectified Max-Value Entropy Search for Bayesian Optimization
Although the existing max-value entropy search (MES) is based on the wid...
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12/31/2021
Robust Entropy-regularized Markov Decision Processes
Stochastic and soft optimal policies resulting from entropy-regularized ...
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10/27/2021
Differentially Private Federated Bayesian Optimization with Distributed Exploration
Bayesian optimization (BO) has recently been extended to the federated l...
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07/30/2021
Trusted-Maximizers Entropy Search for Efficient Bayesian Optimization
Information-based Bayesian optimization (BO) algorithms have achieved st...
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07/16/2021
Bidding and Pricing in Budget and ROI Constrained Markets
In online advertising markets, setting budget and return on investment (...
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05/13/2021
Value-at-Risk Optimization with Gaussian Processes
Value-at-risk (VaR) is an established measure to assess risks in critica...
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04/17/2021
Convolutional Normalizing Flows for Deep Gaussian Processes
Deep Gaussian processes (DGPs), a hierarchical composition of GP models,...
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02/18/2021
Efficient Carpooling and Toll Pricing for Autonomous Transportation
In this paper, we address the existence and computation of competitive e...
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12/19/2020
An Information-Theoretic Framework for Unifying Active Learning Problems
This paper presents an information-theoretic framework for unifying acti...
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12/19/2020
Top-k Ranking Bayesian Optimization
This paper presents a novel approach to top-k ranking Bayesian optimizat...
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11/07/2020
No-regret Learning in Price Competitions under Consumer Reference Effects
We study long-run market stability for repeated price competitions betwe...
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10/24/2020
Variational Bayesian Unlearning
This paper studies the problem of approximately unlearning a Bayesian mo...
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10/20/2020
Federated Bayesian Optimization via Thompson Sampling
Bayesian optimization (BO) is a prominent approach to optimizing expensi...
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09/16/2020
Competitive Ratios for Online Multi-capacity Ridesharing
In multi-capacity ridesharing, multiple requests (e.g., customers, food ...
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09/13/2020
Zone pAth Construction (ZAC) based Approaches for Effective Real-Time Ridesharing
Real-time ridesharing systems such as UberPool, Lyft Line, GrabShare hav...
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08/18/2020
Learning Structure in Nested Logit Models
This paper introduces a new data-driven methodology for nested logit str...
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08/18/2020
A Relation Analysis of Markov Decision Process Frameworks
We study the relation between different Markov Decision Process (MDP) fr...
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06/30/2020
R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games
This paper presents a recursive reasoning formalism of Bayesian optimiza...
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12/19/2019
Robust Multi-product Pricing under General Extreme Value Models
We study robust versions of pricing problems where customers choose prod...
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11/24/2019
An Iterative Security Game for Computing Robust and Adaptive Network Flows
The recent advancement in cyberphysical systems has led to an exponentia...
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11/16/2019
Inverse Reinforcement Learning with Missing Data
We consider the problem of recovering an expert's reward function with i...
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11/16/2019
Generalized Maximum Causal Entropy for Inverse Reinforcement Learning
We consider the problem of learning from demonstrated trajectories with ...
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11/08/2019
Incentive-aware Contextual Pricing with Non-parametric Market Noise
We consider a dynamic pricing problem for repeated contextual second-pri...
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10/26/2019
Implicit Posterior Variational Inference for Deep Gaussian Processes
A multi-layer deep Gaussian process (DGP) model is a hierarchical compos...
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07/08/2019
Optimal Explanations of Linear Models
When predictive models are used to support complex and important decisio...
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07/08/2019
The Price of Interpretability
When quantitative models are used to support decision-making on complex ...
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11/20/2018
Probability Distributions on Partially Ordered Sets and Network Security Games
We consider the following problem: Does there exist a probability distri...
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09/30/2018
Online Resource Allocation under Partially Predictable Demand
For online resource allocation problems, we propose a new demand arrival...
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08/09/2018
Maximum Weight Online Matching with Deadlines
We study the problem of matching agents who arrive at a marketplace over...
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03/22/2018
Signaling Game-based Misbehavior Inspection in V2I-enabled Highway Operations
Vehicle-to-Infrastructure (V2I) communications are increasingly supporti...
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03/04/2018
Maximizing Efficiency in Dynamic Matching Markets
We study the problem of matching agents who arrive at a marketplace over...
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11/01/2017