12 papers
Regret and Polylogarithmic Constraint Violation for COCO
Dhruv Sarkar, Abhishek Sinha
We study constrained online convex optimization with adversarial convex costs and constraints (). At each round , a learner selects from a -dimensi…
Constrained Contextual Bandits with Adversarial Contexts
Dhruv Sarkar, Abhishek Sinha
We study constrained contextual bandits with adversarial contexts, where each action yields a random reward and incurs a random cost. The conditional mean reward and cost belong to…
A Geometric Approach to Constrained Online Learning
Dhruv Sarkar, Abhishek Sinha
We study constrained online convex optimization with adversarial time-varying constraints. At each round the learner acts before observing the loss and constraint, and is compared…
Optimal Anytime Algorithms for Online Convex Optimization with Adversarial Constraints
Dhruv Sarkar, Abhishek Sinha
We propose an anytime online algorithm for the problem of learning a sequence of adversarial convex cost functions while approximately satisfying another sequence of adversarial on…
Universal Dynamic Regret and Constraint Violation Bounds for Constrained Online Convex Optimization
Subhamon Supantha, Abhishek Sinha
We consider a generalization of the celebrated Online Convex Optimization (OCO) framework with adversarial online constraints. In this problem, an online learner interacts with an…
Online Learning for Approximately-Convex Functions with Long-term Adversarial Constraints
Dhruv Sarkar, Samrat Mukhopadhyay, Abhishek Sinha
We study an online learning problem with long-term budget constraints in the adversarial setting. In this problem, at each round , the learner selects an action from a convex de…
Beyond Constraint Violation for Online Convex Optimization with Adversarial Constraints
Abhishek Sinha, Rahul Vaze
We study Online Convex Optimization with adversarial constraints (COCO). At each round a learner selects an action from a convex decision set and then an adversary reveals a convex…
Static Regret and Instance Dependent Constraint Violation for Constrained Online Convex Optimization
Rahul Vaze, Abhishek Sinha
The constrained version of the standard online convex optimization (OCO) framework, called COCO is considered, where on every round, a convex cost function and a convex constraint…
Online Bidding Algorithms with Strict Return on Spend (ROS) Constraint
Rahul Vaze, Abhishek Sinha
Auto-bidding problem under a strict return-on-spend constraint (ROSC) is considered, where an algorithm has to make decisions about how much to bid for an ad slot depending on the…
Projection-free Algorithms for Online Convex Optimization with Adversarial Constraints
Dhruv Sarkar, Aprameyo Chakrabartty, Subhamon Supantha +2
We study a generalization of the Online Convex Optimization (OCO) framework with time-varying adversarial constraints. In this setting, at each round, the learner selects an action…
Tight Bounds for Online Convex Optimization with Adversarial Constraints
Abhishek Sinha, Rahul Vaze
A well-studied generalization of the standard online convex optimization (OCO) is constrained online convex optimization (COCO). In COCO, on every round, a convex cost function and…
Optimal Algorithms for Online Convex Optimization with Adversarial Constraints
Abhishek Sinha, Rahul Vaze
A well-studied generalization of the standard online convex optimization (OCO) framework is constrained online convex optimization (COCO). In COCO, on every round, a convex cost fu…