Christos Tzamos

Orcid: 0000-0002-7560-5069

According to our database1, Christos Tzamos authored at least 93 papers between 2012 and 2024.

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Bibliography

2024
Online Learning of Halfspaces with Massart Noise.
CoRR, 2024

Fast Co-Training under Weak Dependence via Stream-Based Active Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Agnostically Learning Multi-Index Models with Queries.
Proceedings of the 65th IEEE Annual Symposium on Foundations of Computer Science, 2024

Active Learning with Simple Questions.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Contextual Pandora's Box.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Methods.
CoRR, 2023

Buy-Many Mechanisms for Many Unit-Demand Buyers.
Proceedings of the Web and Internet Economics - 19th International Conference, 2023

The Gain from Ordering in Online Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Weitzman's Rule for Pandora's Box with Correlations.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

First Order Stochastic Optimization with Oblivious Noise.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Method.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Graph Connectivity with Noisy Queries.
Proceedings of the 48th International Symposium on Mathematical Foundations of Computer Science, 2023

Buying Information for Stochastic Optimization.
Proceedings of the International Conference on Machine Learning, 2023

Self-Directed Linear Classification.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Distribution-Independent Regression for Generalized Linear Models with Oblivious Corruptions.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Approximating Pandora's Box with Correlations.
Proceedings of the Approximation, 2023

2022
Buy-many mechanisms are not much better than item pricing.
Games Econ. Behav., 2022

A Strongly Polynomial Algorithm for Approximate Forster Transforms and its Application to Halfspace Learning.
Electron. Colloquium Comput. Complex., 2022

Efficient Parameter Estimation of Truncated Boolean Product Distributions.
Algorithmica, 2022

Learning general halfspaces with general Massart noise under the Gaussian distribution.
Proceedings of the STOC '22: 54th Annual ACM SIGACT Symposium on Theory of Computing, Rome, Italy, June 20, 2022

Pricing ordered items.
Proceedings of the STOC '22: 54th Annual ACM SIGACT Symposium on Theory of Computing, Rome, Italy, June 20, 2022

Perfect Sampling from Pairwise Comparisons.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Linear Label Ranking with Bounded Noise.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Online Learning for Min Sum Set Cover and Pandora's Box.
Proceedings of the International Conference on Machine Learning, 2022

Learning General Halfspaces with Adversarial Label Noise via Online Gradient Descent.
Proceedings of the International Conference on Machine Learning, 2022

Clustering with Queries under Semi-Random Noise.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Learning a Single Neuron with Adversarial Label Noise via Gradient Descent.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021
Combinatorial Assortment Optimization.
ACM Trans. Economics and Comput., 2021

Threshold Phenomena in Learning Halfspaces with Massart Noise.
CoRR, 2021

Efficiently learning halfspaces with Tsybakov noise.
Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

Fast and Simple Modular Subset Sum.
Proceedings of the 4th Symposium on Simplicity in Algorithms, 2021

ReLU Regression with Massart Noise.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Forster Decomposition and Learning Halfspaces with Noise.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On Robust Mean Estimation under Coordinate-level Corruption.
Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Online Algorithms with Distributional Advice.
Proceedings of the 38th International Conference on Machine Learning, 2021

Efficient Algorithms for Learning from Coarse Labels.
Proceedings of the Conference on Learning Theory, 2021

Agnostic Proper Learning of Halfspaces under Gaussian Marginals.
Proceedings of the Conference on Learning Theory, 2021

Boosting in the Presence of Massart Noise.
Proceedings of the Conference on Learning Theory, 2021

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

2020
The Complexity of Black-Box Mechanism Design with Priors.
ACM Trans. Economics and Comput., 2020

Buy-many mechanisms: what are they and why should you care?
SIGecom Exch., 2020

Convergence and Sample Complexity of SGD in GANs.
CoRR, 2020

A Polynomial Time Algorithm for Learning Halfspaces with Tsybakov Noise.
CoRR, 2020

Learning Halfspaces with Tsybakov Noise.
CoRR, 2020

Robust Mean Estimation under Coordinate-level Corruption.
CoRR, 2020

Menu-size Complexity and Revenue Continuity of Buy-many Mechanisms.
Proceedings of the EC '20: The 21st ACM Conference on Economics and Computation, 2020

Optimal Private Median Estimation under Minimal Distributional Assumptions.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Non-Convex SGD Learns Halfspaces with Adversarial Label Noise.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Black-Box Methods for Restoring Monotonicity.
Proceedings of the 37th International Conference on Machine Learning, 2020

Pandora's Box with Correlations: Learning and Approximation.
Proceedings of the 61st IEEE Annual Symposium on Foundations of Computer Science, 2020

Learning Halfspaces with Massart Noise Under Structured Distributions.
Proceedings of the Conference on Learning Theory, 2020

2019
Design and Dynamic Pricing of Vertically Differentiated Inventories.
Manag. Sci., 2019

Learning Optimal Search Algorithms from Data.
CoRR, 2019

Reasonable multi-item mechanisms are not much better than item pricing.
CoRR, 2019

Diversity and Exploration in Social Learning.
Proceedings of the World Wide Web Conference, 2019

Fast Modular Subset Sum using Linear Sketching.
Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2019

Distribution-Independent PAC Learning of Halfspaces with Massart Noise.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Capacitated Dynamic Programming: Faster Knapsack and Graph Algorithms.
Proceedings of the 46th International Colloquium on Automata, Languages, and Programming, 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

Learning to Prune: Speeding up Repeated Computations.
Proceedings of the Conference on Learning Theory, 2019

2018
Anaconda: A Non-Adaptive Conditional Sampling Algorithm for Distribution Testing.
Electron. Colloquium Comput. Complex., 2018

Fast Modular Subset Sum using Linear Sketching.
CoRR, 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

Actively Avoiding Nonsense in Generative Models.
Proceedings of the Conference On Learning Theory, 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
Mechanism design: from optimal transport theory to revenue maximization.
PhD thesis, 2017

Certified Computation in Crowdsourcing.
CoRR, 2017

Truthful Facility Location with Additive Errors.
CoRR, 2017

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

Improving Viterbi is Hard: Better Runtimes Imply Faster Clique Algorithms.
Proceedings of the 34th International Conference on Machine Learning, 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

Strategyproof Facility Location for Concave Cost Functions.
Algorithmica, 2016

Anonymous Auctions Maximizing Revenue.
Proceedings of the Web and Internet Economics - 12th International Conference, 2016

A size-free CLT for poisson multinomials and its applications.
Proceedings of the 48th Annual ACM SIGACT Symposium on Theory of Computing, 2016

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

Does Information Revelation Improve Revenue?
Proceedings of the 2016 ACM Conference on Economics and Computation, 2016

Tight Hardness Results for Maximum Weight Rectangles.
Proceedings of the 43rd International Colloquium on Automata, Languages, and Programming, 2016

2015
Who to Trust for Truthfully Maximizing Welfare?
CoRR, 2015

Strong Duality for a Multiple-Good Monopolist.
Proceedings of the Sixteenth ACM Conference on Economics and Computation, 2015

Game Theory based Peer Grading Mechanisms for MOOCs.
Proceedings of the Second ACM Conference on Learning @ Scale, 2015

On the Structure, Covering, and Learning of Poisson Multinomial Distributions.
Proceedings of the IEEE 56th Annual Symposium on Foundations of Computer Science, 2015

2014
On the Power of Deterministic Mechanisms for Facility Location Games.
ACM Trans. Economics and Comput., 2014

The Value of Knowing Your Enemy.
CoRR, 2014

The Complexity of Optimal Mechanism Design.
Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014

2013
Winner-imposing strategyproof mechanisms for multiple Facility Location games.
Theor. Comput. Sci., 2013

Strategyproof facility location with concave costs.
SIGecom Exch., 2013

Strategy-Proof Facility Location for Concave Cost Functions
CoRR, 2013

Mechanism design via optimal transport.
Proceedings of the fourteenth ACM Conference on Electronic Commerce, 2013

2012
Optimal Pricing Is Hard.
Proceedings of the Internet and Network Economics - 8th International Workshop, 2012


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