Nika Haghtalab

According to our database1, Nika Haghtalab authored at least 47 papers between 2014 and 2023.

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Bibliography

2023
Smoothed Analysis of Sequential Probability Assignment.
CoRR, 2023

A Unifying Perspective on Multi-Calibration: Unleashing Game Dynamics for Multi-Objective Learning.
CoRR, 2023

Leveraging Reviews: Learning to Price with Buyer and Seller Uncertainty.
CoRR, 2023

Stochastic Minimum Vertex Cover in General Graphs: a 3/2-Approximation.
CoRR, 2023

2022
Competition, Alignment, and Equilibria in Digital Marketplaces.
CoRR, 2022

Learning in Stackelberg Games with Non-myopic Agents.
CoRR, 2022

Communicating with Anecdotes.
CoRR, 2022

Oracle-Efficient Online Learning for Beyond Worst-Case Adversaries.
CoRR, 2022

Learning in Stackelberg Games with Non-myopic Agents.
Proceedings of the EC '22: The 23rd ACM Conference on Economics and Computation, Boulder, CO, USA, July 11, 2022

On-Demand Sampling: Learning Optimally from Multiple Distributions.
NeurIPS, 2022

Oracle-Efficient Online Learning for Smoothed Adversaries.
NeurIPS, 2022

2021
Belief polarization in a complex world: A learning theory perspective.
Proc. Natl. Acad. Sci. USA, 2021

Structured Robust Submodular Maximization: Offline and Online Algorithms.
INFORMS J. Comput., 2021

One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

Smoothed Analysis with Adaptive Adversaries.
Proceedings of the 62nd IEEE Annual Symposium on Foundations of Computer Science, 2021

2020
<i>k</i>-center Clustering under Perturbation Resilience.
ACM Trans. Algorithms, 2020

Oracle-efficient Online Learning and Auction Design.
J. ACM, 2020

Ignorance Is Almost Bliss: Near-Optimal Stochastic Matching with Few Queries.
Oper. Res., 2020

Noise in Classification.
CoRR, 2020

Smoothed Analysis of Online and Differentially Private Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Maximizing Welfare with Incentive-Aware Evaluation Mechanisms.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

The disparate equilibria of algorithmic decision making when individuals invest rationally.
Proceedings of the FAT* '20: Conference on Fairness, 2020

Noise in Classification.
Proceedings of the Beyond the Worst-Case Analysis of Algorithms, 2020

2019
Computing Stackelberg Equilibria of Large General-Sum Games.
Proceedings of the Algorithmic Game Theory - 12th International Symposium, 2019

Toward a Characterization of Loss Functions for Distribution Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Algorithmic Greenlining: An Approach to Increase Diversity.
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

2018
The Provable Virtue of Laziness in Motion Planning.
Proceedings of the Twenty-Eighth International Conference on Automated Planning and Scheduling, 2018

Weighted Voting Via No-Regret Learning.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Algorithms for Generalized Topic Modeling.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Monitoring stealthy diffusion.
Knowl. Inf. Syst., 2017

Robust Submodular Maximization: Offline and Online Algorithms.
CoRR, 2017

Opting Into Optimal Matchings.
Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete Algorithms, 2017

Online Learning with a Hint.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Collaborative PAC Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Efficient PAC Learning from the Crowd.
Proceedings of the 30th Conference on Learning Theory, 2017

2016
Oracle-Efficient Learning and Auction Design.
CoRR, 2016

Generalized Topic Modeling.
CoRR, 2016

Three Strategies to Success: Learning Adversary Models in Security Games.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

k-Center Clustering Under Perturbation Resilience.
Proceedings of the 43rd International Colloquium on Automata, Languages, and Programming, 2016

Learning and 1-bit Compressed Sensing under Asymmetric Noise.
Proceedings of the 29th Conference on Learning Theory, 2016

2015
Symmetric and Asymmetric $k$-center Clustering under Stability.
CoRR, 2015

Commitment Without Regrets: Online Learning in Stackelberg Security Games.
Proceedings of the Sixteenth ACM Conference on Economics and Computation, 2015

Efficient Learning of Linear Separators under Bounded Noise.
Proceedings of The 28th Conference on Learning Theory, 2015

2014
Ignorance is Almost Bliss: Near-Optimal Stochastic Matching With Few Queries.
CoRR, 2014

Learning Optimal Commitment to Overcome Insecurity.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Clustering in the Presence of Background Noise.
Proceedings of the 31th International Conference on Machine Learning, 2014

Lazy Defenders Are Almost Optimal against Diligent Attackers.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014


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