6 papers
Replicable Bandits with UCB based Exploration
Rohan Deb, Udaya Ghai, Karan Singh +1
We study replicable algorithms for stochastic multi-armed bandits (MAB) and linear bandits with UCB (Upper Confidence Bound) based exploration. A bandit algorithm is -replicabl…
Introduction to Online Control
Elad Hazan, Karan Singh
This text presents an introduction to an emerging paradigm in control of dynamical systems and differentiable reinforcement learning called online nonstochastic control. The new ap…
How to Sell High-Dimensional Data Optimally
Andrew Li, R. Ravi, Karan Singh +2
Motivated by the problem of selling large, proprietary data, we consider an information pricing problem proposed by Bergemann et al. that involves a decision-making buyer and a mon…
Inverse Optimization Without Inverse Optimization: Direct Solution Prediction with Transformer Models
Macarena Navarro, Willem-Jan van Hoeve, Karan Singh
We present an end-to-end framework for generating solutions to combinatorial optimization problems with unknown components using transformer-based sequence-to-sequence neural netwo…
Faster Global Minimum Cut with Predictions
Benjamin Moseley, Helia Niaparast, Karan Singh
Global minimum cut is a fundamental combinatorial optimization problem with wide-ranging applications. Often in practice, these problems are solved repeatedly on families of simila…
Sample-Optimal Agnostic Boosting with Unlabeled Data
Udaya Ghai, Karan Singh
Boosting provides a practical and provably effective framework for constructing accurate learning algorithms from inaccurate rules of thumb. It extends the promise of sample-effici…