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07/27/2023
A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity
We investigate the fixed-budget best-arm identification (BAI) problem fo...
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06/12/2023
A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
We investigate learning the equilibria in non-stationary multi-agent sys...
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05/24/2023
No-Regret Online Prediction with Strategic Experts
We study a generalization of the online binary prediction with expert ad...
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02/02/2023
Stochastic Contextual Bandits with Long Horizon Rewards
The growing interest in complex decision-making and language modeling pr...
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10/24/2022
Offline congestion games: How feedback type affects data coverage requirement
This paper investigates when one can efficiently recover an approximate ...
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10/10/2022
Towards a Theoretical Foundation of Policy Optimization for Learning Control Policies
Gradient-based methods have been widely used for system design and optim...
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07/13/2022
Iterative Linear Quadratic Optimization for Nonlinear Control: Differentiable Programming Algorithmic Templates
We present the implementation of nonlinear control algorithms based on l...
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07/07/2022
Interactive Combinatorial Bandits: Balancing Competitivity and Complementarity
We study non-modular function maximization in the online interactive ban...
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06/06/2022
Multi-learner risk reduction under endogenous participation dynamics
Prediction systems face exogenous and endogenous distribution shift – th...
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06/04/2022
Learning in Congestion Games with Bandit Feedback
Learning Nash equilibria is a central problem in multi-agent systems. In...
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04/08/2022
Decision-Dependent Risk Minimization in Geometrically Decaying Dynamic Environments
This paper studies the problem of expected loss minimization given a dat...
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03/30/2022
System Identification via Nuclear Norm Regularization
This paper studies the problem of identifying low-order linear systems v...
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03/07/2022
Flat minima generalize for low-rank matrix recovery
Empirical evidence suggests that for a variety of overparameterized nonl...
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01/16/2022
Towards Sample-efficient Overparameterized Meta-learning
An overarching goal in machine learning is to build a generalizable mode...
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01/10/2022
Multiplayer Performative Prediction: Learning in Decision-Dependent Games
Learning problems commonly exhibit an interesting feedback mechanism whe...
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11/15/2021
Faster First-Order Algorithms for Monotone Strongly DR-Submodular Maximization
Continuous DR-submodular functions are a class of generally non-convex/n...
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10/29/2021
Computing Lewis Weights to High Precision
We present an algorithm for computing approximate ℓ_p Lewis weights to h...
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10/28/2021
Selective Sampling for Online Best-arm Identification
This work considers the problem of selective-sampling for best-arm ident...
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06/15/2021
Improved Regret Bounds for Online Submodular Maximization
In this paper, we consider an online optimization problem over T rounds ...
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02/14/2021
Sample Efficient Subspace-based Representations for Nonlinear Meta-Learning
Constructing good representations is critical for learning complex tasks...
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12/23/2020
Function Design for Improved Competitive Ratio in Online Resource Allocation with Procurement Costs
We study the problem of online resource allocation, where multiple custo...
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05/29/2020
Online DR-Submodular Maximization with Stochastic Cumulative Constraints
In this paper, we consider online continuous DR-submodular maximization ...
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06/30/2019
Online Continuous DR-Submodular Maximization with Long-Term Budget Constraints
In this paper, we study a class of online optimization problems with lon...
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06/30/2019
Competitive Algorithms for Online Budget-Constrained Continuous DR-Submodular Problems
In this paper, we study a certain class of online optimization problems,...
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06/18/2019
Escaping from saddle points on Riemannian manifolds
We consider minimizing a nonconvex, smooth function f on a Riemannian ma...
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04/10/2019
New Computational and Statistical Aspects of Regularized Regression with Application to Rare Feature Selection and Aggregation
Prior knowledge on properties of a target model often come as discrete o...
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08/07/2018
Width-Independence Beyond Linear Objectives: Distributed Fair Packing and Covering Algorithms
In network routing and resource allocation, α-fair utility functions are...
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02/05/2018
Competitive Online Algorithms for Resource Allocation over the Positive Semidefinite Cone
We consider a new and general online resource allocation problem, where ...
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01/15/2018
Global Convergence of Policy Gradient Methods for Linearized Control Problems
Direct policy gradient methods for reinforcement learning and continuous...
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12/15/2015
Relative Density and Exact Recovery in Heterogeneous Stochastic Block Models
The Stochastic Block Model (SBM) is a widely used random graph model for...
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02/28/2014
Learning Graphical Models With Hubs
We consider the problem of learning a high-dimensional graphical model i...
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03/21/2013