Manolis Zampetakis

Orcid: 0009-0005-4967-5927

Affiliations:
  • Yale University, New Haven, CT, USA


According to our database1, Manolis Zampetakis authored at least 52 papers between 2014 and 2024.

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Bibliography

2024
Transfer Learning Beyond Bounded Density Ratios.
CoRR, 2024

On the Complexity of Computing Sparse Equilibria and Lower Bounds for No-Regret Learning in Games.
Proceedings of the 15th Innovations in Theoretical Computer Science Conference, 2024

2023
Consensus-Halving: Does It Ever Get Easier?
SIAM J. Comput., April, 2023

First-Order Algorithms for Nonlinear Generalized Nash Equilibrium Problems.
J. Mach. Learn. Res., 2023

Tree of Attacks: Jailbreaking Black-Box LLMs Automatically.
CoRR, 2023

Sorting from Crowdsourced Comparisons using Expert Verifications.
CoRR, 2023

Algorithmic Contract Design for Crowdsourced Ranking.
CoRR, 2023

What Makes a Good Fisherman? Linear Regression under Self-Selection Bias.
Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023

The Computational Complexity of Multi-player Concave Games and Kakutani Fixed Points.
Proceedings of the 24th ACM Conference on Economics and Computation, 2023

Smoothed Analysis of Online Non-parametric Auctions.
Proceedings of the 24th ACM Conference on Economics and Computation, 2023

Learning Exponential Families from Truncated Samples.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Deterministic Nonsmooth Nonconvex Optimization.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

The Computational Complexity of Finding Stationary Points in Non-Convex Optimization.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

STay-ON-the-Ridge: Guaranteed Convergence to Local Minimax Equilibrium in Nonconvex-Nonconcave Games.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Bayesian Strategy-Proof Facility Location via Robust Estimation.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Analyzing data with systematic bias.
SIGecom Exch., July, 2022

On the Complexity of Deterministic Nonsmooth and Nonconvex Optimization.
CoRR, 2022

Estimation of Standard Auction Models.
Proceedings of the EC '22: The 23rd ACM Conference on Economics and Computation, Boulder, CO, USA, July 11, 2022

Learning and Covering Sums of Independent Random Variables with Unbounded Support.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Last-Iterate Convergence of Saddle Point Optimizers via High-Resolution Differential Equations.
CoRR, 2021

The complexity of constrained min-max optimization.
Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

A Topological Characterization of Modulo-<i>p</i> Arguments and Implications for Necklace Splitting.
Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms, 2021

Robust Learning of Optimal Auctions.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Efficient Truncated Linear Regression with Unknown Noise Variance.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Private and Non-private Uniformity Testing for Ranking Data.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Identity testing for Mallows model.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Statistical Taylor Theorem and Extrapolation of Truncated Densities.
Proceedings of the Conference on Learning Theory, 2021

2020
A Topological Characterization of Modulo-p Arguments and Implications for Necklace Splitting.
CoRR, 2020

More Revenue from Two Samples via Factor Revealing SDPs.
Proceedings of the EC '20: The 21st ACM Conference on Economics and Computation, 2020

Optimal Approximation - Smoothness Tradeoffs for Soft-Max Functions.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Constant-Expansion Suffices for Compressed Sensing with Generative Priors.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Truncated Linear Regression in High Dimensions.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Estimation and Inference with Trees and Forests in High Dimensions.
Proceedings of the Conference on Learning Theory, 2020

On the Complexity of Modulo-q Arguments and the Chevalley - Warning Theorem.
Proceedings of the 35th Computational Complexity Conference, 2020

A Theoretical and Practical Framework for Regression and Classification from Truncated Samples.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Efficient Truncated Statistics with Unknown Truncation.
Proceedings of the 60th IEEE Annual Symposium on Foundations of Computer Science, 2019

Computationally and Statistically Efficient Truncated Regression.
Proceedings of the Conference on Learning Theory, 2019

Optimal Learning of Mallows Block Model.
Proceedings of the Conference on Learning Theory, 2019

2018
PPP-Completeness with Connections to Cryptography.
IACR Cryptol. ePrint Arch., 2018

A converse to Banach's fixed point theorem and its CLS-completeness.
Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, 2018

Efficient Statistics, in High Dimensions, from Truncated Samples.
Proceedings of the 59th IEEE Annual Symposium on Foundations of Computer Science, 2018

Certified Computation from Unreliable Datasets.
Proceedings of the Conference On Learning Theory, 2018

Bootstrapping EM via Power EM and Convergence in the Naive Bayes Model.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Certified Computation in Crowdsourcing.
CoRR, 2017

Faster Sublinear Algorithms using Conditional Sampling.
Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete Algorithms, 2017

Ten Steps of EM Suffice for Mixtures of Two Gaussians.
Proceedings of the 30th Conference on Learning Theory, 2017

2016
Efficient Money Burning in General Domains.
Theory Comput. Syst., 2016

Mechanism Design with Selective Verification.
Proceedings of the 2016 ACM Conference on Economics and Computation, 2016

2015
Truthfulness Flooded Domains and the Power of Verification for Mechanism Design.
ACM Trans. Economics and Comput., 2015

Who to Trust for Truthfully Maximizing Welfare?
CoRR, 2015

Scheduling MapReduce Jobs and Data Shuffle on Unrelated Processors.
Proceedings of the Experimental Algorithms - 14th International Symposium, 2015

2014
Scheduling MapReduce Jobs on Unrelated Processors.
Proceedings of the Workshops of the EDBT/ICDT 2014 Joint Conference (EDBT/ICDT 2014), 2014


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