Vasilis Kontonis

Logo

  • vkonton[at]gmail.com
  • vasilis[at]cs.utexas.edu

I am an IFML Postdoctoral Fellow at UT Austin working with Adam Klivans and Raghu Meka. I received my PhD from Computer Science Department of University of Wisconsin-Madison, where I was very fortunate to be advised by Professor Christos Tzamos. Before coming to UW-Madison, I studied Electrical and Computer Engineering at the National Technical University of Athens where I was very lucky to be advised by Professor Dimitris Fotakis.

Here is a more complete CV.

Publications

  1. Optimizing Solution-Samplers for Combinatorial Problems:
    The Landscape of Policy Gradient Methods
    C. Caramanis, D. Fotakis, A. Kalavasis, C. Tzamos
    Selected for Oral Presentation
    NeurIPS 2023

  2. SLaM: Student-Label Mixing for Distillation with Unlabeled Examples
    w/ F. Iliopoulos, K. Trinh, C. Baykal, G. Menghani, V. Erik
    NeurIPS 2023

  3. The Gain from Ordering in Online Learning
    w/ M. Ma, C. Tzamos
    NeurIPS 2023

  4. Efficient Testable Learning of Halfspaces with Adversarial Label Noise
    w/ I. Diakonikolas, D M. Kane, [S. Liu], N. Zarifis
    NeurIPS 2023

  5. Self Directed Linear Classification
    w/ I. Diakonikolas, C. Tzamos, N. Zarifis
    COLT 2023

  6. Weighted Distillation with Unlabeled Examples
    w/ F. Iliopoulos, C. Baykal, G. Menghani, K. Trinh, V. Erik
    NeurIPS 2022

  7. Linear Label Ranking with Bounded Noise
    w/ D. Fotakis, A. Kalavasis, C. Tzamos
    Selected for Oral Presentation
    NeurIPS 2022

  8. Learning General Halfspaces with Adversarial Label Noise via Online Gradient Descent
    w/ I. Diakonikolas, C. Tzamos, N. Zarifis
    ICML 2022

  9. Learning a Single Neuron with Adversarial Label Noise via Gradient Descent
    w/ I. Diakonikolas, C. Tzamos, N. Zarifis
    COLT 2022

  10. Learning General Halfspaces with General Massart Noise under the Gaussian Distribution
    w/ I. Diakonikolas, D. Kane, C. Tzamos, N. Zarifis
    STOC 2022

  11. A Statistical Taylor Theorem and Extrapolation of Truncated Densities
    w/ C. Daskalakis, C. Tzamos, M. Zampetakis
    COLT 2021

  12. Agnostic Proper Learning of Halfspaces under Gaussian Marginals
    w/ I. Diakonikolas, D. Kane, C. Tzamos, N. Zarifis
    COLT 2021

  13. Efficient Algorithms for Learning from Coarse Labels
    w/ D. Fotakis, A. Kalavasis, C. Tzamos
    COLT 2021

  14. Learning Online Algorithms with Distributional Advice
    w/ I. Diakonikolas, C. Tzamos, A. Vakilian, N. Zarifis
    ICML 2021

  15. A Polynomial Time Algorithm For Learning Halfspaces with Tsybakov Noise
    w/ I. Diakonikolas, D. Kane, C. Tzamos, N. Zarifis
    STOC 2021

  16. Learning Halfspaces with Tsybakov Noise
    w/ I. Diakonikolas, C. Tzamos, N. Zarifis
    STOC 2021
    Conference version merged with the above paper

  17. Non-Convex SGD Learns Halfspaces with Adversarial Label Noise
    w/ I. Diakonikolas, C. Tzamos, N. Zarifis
    NeurIPS 2020

  18. Learning Halfspaces with Massart Noise Under Structured Distributions
    w/ I. Diakonikolas, C. Tzamos, N. Zarifis
    COLT 2020

  19. Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks
    w/ I. Diakonikolas, D. Kane, N. Zarifis
    COLT 2020

  20. Efficient Truncated Statistics with Unknown Truncation
    w/ C. Tzamos, M. Zampetakis
    FOCS 2019

  21. Removing Bias in Maching Learning via Truncated Statistics
    w/ C. Daskalakis, C. Tzamos, M. Zampetakis
    Manuscript

  22. Opinion Dynamics with Limited Information
    w/ D. Fotakis, V. Kandiros, S. Skoulakis
    WINE 2018

  23. Learning Powers of Poisson Binomial Distributions
    w/ D. Fotakis, P. Krysta, P. Spirakis
    Manuscript

Service

Reviewer: STOC, SODA, WINE, ICML, EC, MFCS, TCS, ALT

Talks