no code implementations • 16 Mar 2021 • Jad Salem, Swati Gupta, Vijay Kamble
The goal of this paper is to highlight the rich interface between temporal notions of fairness and online decision-making through a novel meta-objective of ensuring fairness at the time of decision.
no code implementations • 11 Jun 2020 • Eren Ozbay, Vijay Kamble
In this paper, motivated by certain operational concerns in online platforms, we consider a new objective in the classical setup.
no code implementations • 10 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.
no code implementations • 18 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.
1 code implementation • 16 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.
no code implementations • 15 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.
no code implementations • 25 Jul 2015 • Vijay Kamble, Nihar Shah, David Marn, Abhay Parekh, Kannan Ramachandran
This paper proposes the Square Root Agreement Rule (SRA): a simple reward mechanism that incentivizes truthful responses to objective evaluations on such platforms.
no code implementations • 6 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.