
Sampath Kannan
· ProfessorUniversity of Pennsylvania · Computer and Information Science
Active 1988–2025
Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.
Research topics
- Computer Science
- Political Science
- Sociology
- Artificial Intelligence
- Demography
- Actuarial science
- Mathematical optimization
- Mathematics education
- Medicine
- Econometrics
Selected publications
A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual\n Bandit Problem
arXiv (Cornell University) · 2018-01-10 · 29 citations
preprintOpen access1st authorCorrespondingBandit learning is characterized by the tension between long-term exploration\nand short-term exploitation. However, as has recently been noted, in settings\nin which the choices of the learning algorithm correspond to important\ndecisions about individual people (such as criminal recidivism prediction,\nlending, and sequential drug trials), exploration corresponds to explicitly\nsacrificing the well-being of one individual for the potential future benefit\nof others. This raises a fairness conc…
Graph Reconstruction and Verification
ACM Transactions on Algorithms · 2018-08-09 · 19 citations
articleOpen access1st authorCorrespondingHow efficiently can we find an unknown graph using distance or shortest path queries between its vertices? We assume that the unknown graph G is connected, unweighted, and has bounded degree. In the reconstruction problem, the goal is to find the graph G . In the verification problem, we are given a hypothetical graph Ĝ and want to check whether G is equal to Ĝ . We provide a randomized algorithm for reconstruction using Õ( n 3/2 ) distance queries, based on Voronoi cell decomposition. Next, we…
A Retrospective Look at the Monitoring and Checking (MaC) Framework
Lecture notes in computer science · 2019-01-01 · 3 citations
book-chapter1st authorCorrespondingFairness in Algorithmic Decision Making
SMARTech Repository (Georgia Institute of Technology) · 2018-10-29 · 3 citations
article1st authorCorrespondingPresented on October 29, 2018 at 11:00 a.m. in the Klaus Advanced Computing Building, Room 1116E.
Algorithmic Collusion Without Threats
arXiv (Cornell University) · 2024-09-06 · 2 citations
preprintOpen accessThere has been substantial recent concern that pricing algorithms might learn to ``collude.'' Supra-competitive prices can emerge as a Nash equilibrium of repeated pricing games, in which sellers play strategies which threaten to punish their competitors who refuse to support high prices, and these strategies can be automatically learned. In fact, a standard economic intuition is that supra-competitive prices emerge from either the use of threats, or a failure of one party to optimize their payo…
Recent grants
Frequent coauthors
- 29 shared
Aaron Roth
- 14 shared
Insup Lee
- 13 shared
Jamie Morgenstern
University of Washington
- 13 shared
Sanjeev Khanna
- 11 shared
Juba Ziani
- 10 shared
Oleg Sokolsky
University of Pennsylvania
- 10 shared
Li‐San Wang
University of Pennsylvania
- 10 shared
Tandy Warnow
University of Illinois Urbana-Champaign
Labs
Penn Engineering's TeamPI
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