3.6k citations · 4.3k across the 44 of their papers we have counts for
13 papers · 1 filter
A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity
Zhihan Xiong, Romain Camilleri, Maryam Fazel +2
We investigate the fixed-budget best-arm identification (BAI) problem for linear bandits in a potentially non-stationary environment. Given a finite arm set $\mathcal{X}\subset\mat…
A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
Haozhe Jiang, Qiwen Cui, Zhihan Xiong +2
We investigate learning the equilibria in non-stationary multi-agent systems and address the challenges that differentiate multi-agent learning from single-agent learning. Specific…
No-Regret Online Prediction with Strategic Experts
Omid Sadeghi, Maryam Fazel
We study a generalization of the online binary prediction with expert advice framework where at each round, the learner is allowed to pick experts from a pool of expe…
Stochastic Contextual Bandits with Long Horizon Rewards
Yuzhen Qin, Yingcong Li, Fabio Pasqualetti +2
The growing interest in complex decision-making and language modeling problems highlights the importance of sample-efficient learning over very long horizons. This work takes a ste…
Online SuBmodular + SuPermodular (BP) Maximization with Bandit Feedback
Adhyyan Narang, Omid Sadeghi, Lillian J Ratliff +2
In the context of online interactive machine learning with combinatorial objectives, we extend purely submodular prior work to more general non-submodular objectives. This includes…
Emergent specialization from participation dynamics and multi-learner retraining
Sarah Dean, Mihaela Curmei, Lillian J. Ratliff +2
Numerous online services are data-driven: the behavior of users affects the system's parameters, and the system's parameters affect the users' experience of the service, which in t…
Flat minima generalize for low-rank matrix recovery
Lijun Ding, Dmitriy Drusvyatskiy, Maryam Fazel +1
Empirical evidence suggests that for a variety of overparameterized nonlinear models, most notably in neural network training, the growth of the loss around a minimizer strongly im…
Selective Sampling for Online Best-arm Identification
Romain Camilleri, Zhihan Xiong, Maryam Fazel +2
This work considers the problem of selective-sampling for best-arm identification. Given a set of potential options , a learner aims to compute with…
Fast First-Order Methods for Monotone Strongly DR-Submodular Maximization
Omid Sadeghi, Maryam Fazel
Continuous DR-submodular functions are a class of functions that satisfy the Diminishing Returns (DR) property, which implies that they are concave along non-negative directions. E…
Improved Regret Bounds for Online Submodular Maximization
Omid Sadeghi, Prasanna Raut, Maryam Fazel
In this paper, we consider an online optimization problem over rounds where at each step , the algorithm chooses an action from the fixed convex and compact doma…
Sample Efficient Subspace-based Representations for Nonlinear Meta-Learning
Halil Ibrahim Gulluk, Yue Sun, Samet Oymak +1
Constructing good representations is critical for learning complex tasks in a sample efficient manner. In the context of meta-learning, representations can be constructed from comm…
Near-Optimal Randomized Exploration for Tabular Markov Decision Processes
Zhihan Xiong, Ruoqi Shen, Qiwen Cui +2
We study algorithms using randomized value functions for exploration in reinforcement learning. This type of algorithms enjoys appealing empirical performance. We show that when we…
Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator
Maryam Fazel, Rong Ge, Sham M. Kakade +1
Direct policy gradient methods for reinforcement learning and continuous control problems are a popular approach for a variety of reasons: 1) they are easy to implement without exp…