Academic Work - Publications

Research Publications

  • SLaM: Student-Label Mixing for Distillation with Unlabeled Examples
    with Vasilis Kontonis, Cenk Baykal, Gaurav Menghani, Khoa Trinh and Erik Vee. Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS), November 2023.
    [Arxiv]

  • Robust Active Distillation
    with Cenk Baykal, Khoa Trihn, Gaurav Menghani and Erik Vee. Proceedings of the 11th International Conference on Learning Representations (ICLR), May 2023.
    [Arxiv]

  • Weighted Distillation with Unlabeled Examples
    with Vasilis Kontonis, Cenk Baykal, Gaurav Menghani, Khoa Trinh and Erik Vee. Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS), November 2022.
    [Arxiv]

  • Improved bounds for coloring locally sparse hypergraphs
    Proceedings of Approximation, Randomization, and Combinatorial Optimization (APPROX/RANDOM), August 2021, pp 39:1-39:16
    Invited to to the Theory of Computing (ToC) Special Issue for APPROX/RANDOM 2021
    [Arxiv]

  • A new notion of commutativity for the algorithmic Lovasz Local Lemma
    with David G. Harris and Vladimir Kolmogorov. Proceedings of Approximation, Randomization, and Combinatorial Optimization (APPROX/RANDOM), August 2021, pp. 31:1-31:25
    [Arxiv]

  • Group testing and local search: is there a computational-statistical gap?
    with Ilias Zadik. Proceedings of the 34th Annual Conference on Learning Theory (COLT), August 2021, pp. 2499-2551.
    [Arxiv]

  • Simple Local Computation Algorithms for the General Lovasz Local Lemma
    with Dimitris Achlioptas and Themis Gouleakis. Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), July 2020, pp. 1-10.
    [Arxiv]

  • Efficiently list-edge coloring multigraphs asymptotically optimally
    with Alistair Sinclair. Random Stuctures & Algorithms, Volume 61, pp. 724-753, 2022. A preliminary version appeared in the proceedings of the 31st ACM-SIAM Symposium on Discrete Algorithms (SODA), January 2020, pp. 2319-2336.
    [Arxiv]

  • Beyond the Lovasz Local Lemma: Point to Set Correlations and Their Algorithmic Applications
    with Dimitris Achlioptas and Alistair Sinclair. Proceedings of the 60th IEEE Symposium on Foundations of Computer Science (FOCS), November 2019, pp. 725-744.
    [Arxiv]

  • A Local Lemma for Focused Stochastic Algorithms
    with Dimitris Achlioptas and Vladimir Kolmogorov. SIAM Journal on Computing (SICOMP), Volume 48(5):1583-602; 2019.
    [Arxiv][local copy]

  • Commutative Algorithms Approximate the LLL-distribution
    Proceedings of Approximation, Randomization, and Combinatorial Optimization (APPROX/RANDOM), August 2018, pp. 44:1 - 44:20
    [Arxiv]

  • Stochastic Control via Entropy Compression
    with Dimitris Achlioptas and Nikos Vlassis. Proceedings of the 44th International Colloquium on Automata, Language and Programming (ICALP), July 2017, pp. 83:1 - 83:13.
    [Arxiv]

  • Focused Stochastic Local Search and the Lovasz Local Lemma
    with Dimitris Achlioptas. Proceedings of the 27th ACM-SIAM Symposium on Discrete Algorithms (SODA), January 2016, pp. 2024-2038.
    [Arxiv]

  • Random walks that Find Perfect Objects and the Lovasz Local Lemma
    with Dimitris Achlioptas. Journal of the ACM (J. ACM), Volume 63(3): 22:1-22:29; 2016. A preliminary version appeared in the proceedings of the 55th IEEE Annual Symposium on Foundations of Computer Science (FOCS), November 2014, pp. 494-503
    [Arxiv]

Dissertation