10 citations · 23 across the 17 of their papers we have counts for
18 papers
What is Best for Students, Numerical Scores or Letter Grades?
Evi Micha, Shreyas Sekar, Nisarg Shah
We study letter grading schemes, which are routinely employed for evaluating student performance. Typically, a numerical score obtained via one or more evaluations is converted int…
Learning Product Rankings Robust to Fake Users
Negin Golrezaei, Vahideh Manshadi, Jon Schneider +1
In many online platforms, customers' decisions are substantially influenced by product rankings as most customers only examine a few top-ranked products. Concurrently, such platfor…
Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences
Tanner Fiez, Shreyas Sekar, Liyuan Zheng +1
The design of personalized incentives or recommendations to improve user engagement is gaining prominence as digital platform providers continually emerge. We propose a multi-armed…
A Capacity-Price Game for Uncertain Renewables Resources
Pan Li, Shreyas Sekar, Baosen Zhang
Renewable resources are starting to constitute a growing portion of the total generation mix of the power system. A key difference between renewables and traditional generators is…
Multi-Armed Bandits for Correlated Markovian Environments with Smoothed Reward Feedback
Tanner Fiez, Shreyas Sekar, Lillian J. Ratliff
We study a multi-armed bandit problem in a dynamic environment where arm rewards evolve in a correlated fashion according to a Markov chain. Different than much of the work on rela…
Risk-Averse Matchings over Uncertain Graph Databases
Charalampos E. Tsourakakis, Shreyas Sekar, Johnson Lam +1
A large number of applications such as querying sensor networks, and analyzing protein-protein interaction (PPI) networks, rely on mining uncertain graph and hypergraph databases.…
Uncertainty in Multi-Commodity Routing Networks: When does it help?
Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff +1
We study the equilibrium behavior in a multi-commodity selfish routing game with many types of uncertain users where each user over- or under-estimates their congestion costs by a…
Price Doubling and Item Halving: Robust Revenue Guarantees for Item Pricing
Elliot Anshelevich, Shreyas Sekar
We study approximation algorithms for revenue maximization based on static item pricing, where a seller chooses prices for various goods in the market, and then the buyers purchase…
Truthful Mechanisms for Matching and Clustering in an Ordinal World
Elliot Anshelevich, Shreyas Sekar
We study truthful mechanisms for matching and related problems in a partial information setting, where the agents' true utilities are hidden, and the algorithm only has access to o…
Pricing to Maximize Revenue and Welfare Simultaneously in Large Markets
Elliot Anshelevich, Koushik Kar, Shreyas Sekar
We study large markets with a single seller which can produce many types of goods, and many multi-minded buyers. The seller chooses posted prices for its many items, and the buyers…
Posted Pricing sans Discrimination
Shreyas Sekar
In the quest for market mechanisms that are easy to implement, yet close to optimal, few seem as viable as posted pricing. Despite the growing body of impressive results, the perfo…
Submodular Maximization using Test Scores
Shreyas Sekar, Milan Vojnovic, Se-Young Yun
We study the canonical problem of maximizing a stochastic submodular function subject to a cardinality constraint, where the goal is to select a subset from a ground set of items w…
Blind, Greedy, and Random: Ordinal Approximation Algorithms for Matching and Clustering
Elliot Anshelevich, Shreyas Sekar
We study Matching and other related problems in a partial information setting where the agents' utilities for being matched to other agents are hidden and the mechanism only has ac…
Computing Stable Coalitions: Approximation Algorithms for Reward Sharing
Elliot Anshelevich, Shreyas Sekar
Consider a setting where selfish agents are to be assigned to coalitions or projects from a fixed set P. Each project k is characterized by a valuation function; v_k(S) is the valu…
Envy-Free Pricing in Large Markets: Approximating Revenue and Welfare
Elliot Anshelevich, Koushik Kar, Shreyas Sekar
We study the classic setting of envy-free pricing, in which a single seller chooses prices for its many items, with the goal of maximizing revenue once the items are allocated. Des…
Price Competition in Networked Markets: How do monopolies impact social welfare?
Elliot Anshelevich, Shreyas Sekar
We study the efficiency of allocations in large markets with a network structure where every seller owns an edge in a graph and every buyer desires a path connecting some nodes. Wh…
Approximate Equilibrium and Incentivizing Social Coordination
Elliot Anshelevich, Shreyas Sekar
We study techniques to incentivize self-interested agents to form socially desirable solutions in scenarios where they benefit from mutual coordination. Towards this end, we consid…
Exploiting the `Web of Trust' to improve efficiency in collaborative networks
Shreyas Sekar, Patrick Maillé
Maintaining high quality content is one of the foremost objectives of any web-based collaborative service that depends on a large number of users. In such systems, it is nearly imp…