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Sampath Kannan

Sampath Kannan

· Professor

University of Pennsylvania · Computer and Information Science

Active 1988–2025

h-index33
Citations4.5k
Papers15018 last 5y
Funding$610k

Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.

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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 authorCorresponding

    Bandit 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 authorCorresponding

    How 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 authorCorresponding
  • Fairness in Algorithmic Decision Making

    SMARTech Repository (Georgia Institute of Technology) · 2018-10-29 · 3 citations

    article1st authorCorresponding

    Presented 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 access

    There 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

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Labs

  • Penn Engineering's TeamPI

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