Research

Broadly speaking, I am interested in most areas of theoretical computer science. My recent focus has been on understanding computational complexity of combinatorial problems such as Clustering, Set Packing, Diversification problems and Graph problems.

  • Generalized Clustering problems. Since almost all of the fundamental clustering problems are hard to approximate, my focus is to understand the parameterized approximability of the general clustering problems. One concrete problem that generalizes most of the known clustering problems is Norm Clustering, where the clustering objective is any monotone norm.

    Another generalization of the fundamental clustering problems is when we have additional constraints. For example, how does the complexity of these problems change under fairness, diversity and robustness constraints?

  • Unconditional lower bounds. I enjoy studying computational complexity of graph problems under restricted models of computation. For example, how good or bad are the standard strengthenings (Sherali-Adams, Sum-of-Squares) of the natural convex programs for these problems?

  • Others. I am also interested in showing conditional lower bounds such as hardness of (parameterized) approximations, etc. I have also spent some time solving problems in learning theory, space bounded derandomization, and foundations of cryptography.

Publications

  • Independent set in k-Claw-Free Graphs: Conditional chi-boundedness and the Power of LP/SDP Relaxations
  • Parinya Chalermsook, Ameet Gadekar, Kamyar Khodamoradi, Joachim Spoerhase.
  • Parameterized Approximation Schemes for Clustering with General Norm Objectives
  • Fateme Abbasi, Sandip Banerjee, Jarosław Byrka, Parinya Chalermsook, Ameet Gadekar, Kamyar Khodamoradi, Dániel Marx, Roohani Sharma, Joachim Spoerhase.
  • Parameterized Approximation for Robust Clustering in Discrete Geometric Spaces
  • Fateme Abbasi, Sandip Banerjee, Jarosław Byrka, Parinya Chalermsook, Ameet Gadekar, Kamyar Khodamoradi, Dániel Marx, Roohani Sharma, Joachim Spoerhase.
  • On the parameterized complexity of Compact Set Packing
  • Ameet Gadekar.
  • Clustering with Fair-Center Representation: Parameterized Approximation Algorithms and Heuristics
  • Suhas Thejaswi, Ameet Gadekar, Bruno Ordozgoiti, Michał Osadnik.
  • Improved learning of k-parities
  • Arnab Bhattacharyya, Ameet Gadekar, Ninad Rajgopal.
  • On the hardness of learning sparse parities
  • Arnab Bhattacharyya, Ameet Gadekar, Suprovat Ghoshal, Rishi Saket.
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