Contact:
john.lazarsfeld [at] yale.edu
About:
I am a fifth year PhD student in computer science at Yale, advised
by James Aspnes.
My research interests are broadly at the intersection
of algorithms, theoretical machine learning,
and the foundations of data science, including:
- distributed algorithms, opinion dynamics,
and computation in multi-agent settings
- bandits, decision making, and games
- differentially private statistics and optimization
I am actively seeking postdoctoral opportunities
beginning in fall 2024!
News:
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December 2023: will be attending OPT2023 @ NeurIPS
to present our work on decentralized learning dynamics.
-
August 2023: presented at the
Yale Theory Student Seminar.
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August 2023: gave a short talk and poster at
WOLA 2023.
-
During the Winter/Spring 2023 semester, I was a visitor at
IST Austria hosted by Dan Alistarh.
-
In Summer 2022, I interned with the privacy-preserving machine learning
research group at Meta in NYC, where I collaborated with Sen Yuan
and Huanyu Zhang.
Publications:
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Dan Alistarh, Krishnendu Chatterjee, Mehrdad Karrabi, and John Lazarsfeld
Repeated Game Dynamics in Population Protocols
July 2023 -- preprint
[ArXiv]
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John Lazarsfeld and Dan Alistarh
The Power of Populations in Decentralized Learning Dynamics
June 2023 -- preprint (preliminary version to appear in OPT workshop at NeurIPS 2023)
[ArXiv]
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Talley Amir, James Aspnes, Petra Berenbrink, Felix Biermeier, Christopher Hahn,
Dominik Kaaser, and John Lazarsfeld
Fast Convergence of k-Opinion Undecided State Dynamics in the
Population Protocol Model
PODC 2023
[ArXiv]
[Proceedings]
-
John Lazarsfeld, Aaron Johnson, and Emmanuel Adeniran
Differentially Private Maximal Information Coefficients
ICML 2022
[ArXiv]
[Proceedings]
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John Lazarsfeld and Aaron Johnson
Consistency of the Maximal Information Coefficient Estimator
July 2021 -- corrects an error in previous work of Reshef et al. (JMLR, 2016)
[ArXiv]
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Talley Amir, James Aspnes, and John Lazarsfeld
Approximate Majority With Catalytic Inputs
OPODIS 2020
[ArXiv]
[Proceedings]
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John Lazarsfeld, Jonathan RodrÃguez, Mert Erden, Yuelin Liu, and Lenore Cowen
Majority Vote Cascading: A Semi-Supervised Framework for Improving
Protein Function Prediction
ACM BCB 2019 -
Companion poster named Best Poster
[Conf. Proceedings]
[Code and Data]
Teaching:
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Yale CPSC 565: Distributed Algorithms
Graduate Teaching Fellow
Fall 2023, Fall 2022
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Yale CPSC 365: Introduction to Algorithms
Graduate Teaching Fellow
Spring 2022, Spring 2021
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Yale CPSC 202: Mathematical Tools for Computer Science
Graduate Teaching Fellow
Fall 2021, Fall 2020
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Tufts COMP 160: Introduction to Algorithms
Graduate Teaching Assistant
Spring 2019; Summer 2019
Other:
Member of Yale CS Graduate Student Advisory Council (2022-)
Graduate Student Representative on Yale CS Climate & Diversity Committee (2020-2021)
Franklin College Graduate Affiliate (2020-)
Last Updated: November 2023