Search Results for author: Vijay Kamble

Found 8 papers, 1 papers with code

Taming Wild Price Fluctuations: Monotone Stochastic Convex Optimization with Bandit Feedback

no code implementations16 Mar 2021 Jad Salem, Swati Gupta, Vijay Kamble

Prices generated by automated price experimentation algorithms often display wild fluctuations, leading to unfavorable customer perceptions and violations of individual fairness: e. g., the price seen by a customer can be significantly higher than what was seen by her predecessors, only to fall once again later.

Fairness

Training a Single Bandit Arm

no code implementations11 Jun 2020 Eren Ozbay, Vijay Kamble

In several applications of the stochastic multi-armed bandit problem, the traditional objective of maximizing the expected sum of rewards obtained can be inappropriate.

Decision Making

Individual Fairness in Hindsight

no code implementations10 Dec 2018 Swati Gupta, Vijay Kamble

In this paper, we extend the notion of IF to account for the time at which a decision is made, in settings where there exists a notion of conduciveness of decisions as perceived by the affected individuals.

Decision Making Fairness

Exploration vs. Exploitation in Team Formation

no code implementations18 Sep 2018 Ramesh Johari, Vijay Kamble, Anilesh K. Krishnaswamy, Hannah Li

An online labor platform faces an online learning problem in matching workers with jobs and using the performance on these jobs to create better future matches.

An Approximate Dynamic Programming Approach to Adversarial Online Learning

1 code implementation16 Mar 2016 Vijay Kamble, Patrick Loiseau, Jean Walrand

We describe an approximate dynamic programming (ADP) approach to compute approximations of the optimal strategies and of the minimal losses that can be guaranteed in discounted repeated games with vector-valued losses.

Decision Making

Matching while Learning

no code implementations15 Mar 2016 Ramesh Johari, Vijay Kamble, Yash Kanoria

We introduce a benchmark model with heterogeneous "workers" (demand) and a limited supply of "jobs" that arrive over time.

A Truth Serum for Large-Scale Evaluations

no code implementations25 Jul 2015 Vijay Kamble, David Marn, Nihar Shah, Abhay Parekh, Kannan Ramachandran

A major challenge in obtaining large-scale evaluations, e. g., product or service reviews on online platforms, labeling images, grading in online courses, etc., is that of eliciting honest responses from agents in the absence of verifiability.

Sequential Relevance Maximization with Binary Feedback

no code implementations6 Mar 2015 Vijay Kamble, Nadia Fawaz, Fernando Silveira

For every product category, each type has an associated relevance feedback that is assumed to be binary: the category is either relevant or irrelevant.

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