Konstantinos Stavropoulos

According to our database, Konstantinos Stavropoulos authored at least 23 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2026

Iterative Chow Filtering for Learning with Distribution Shift.

Gautam Chandrasekaran, Georgios Gkrinias, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan

CoRR, May, 2026

Equivalence of Coarse and Fine-Grained Models for Learning with Distribution Shift.

Adam R. Klivans, Shyamal Patel, Konstantinos Stavropoulos, Arsen Vasilyan

CoRR, May, 2026

Sandwiching Polynomials for Geometric Concepts with Low Intrinsic Dimension.

Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan

CoRR, February, 2026

Efficient Calibration for Decision Making.

Parikshit Gopalan, Konstantinos Stavropoulos, Kunal Talwar, Pranay Tankala

Proceedings of the 58th Annual ACM Symposium on Theory of Computing, 2026

Sparse Linear Regression Is Easy on Random Supports.

Gautam Chandrasekaran, Raghu Meka, Konstantinos Stavropoulos

Proceedings of the 58th Annual ACM Symposium on Theory of Computing, 2026

A Fully Polynomial-Time Algorithm for Robustly Learning Halfspaces over the Hypercube.

Gautam Chandrasekaran, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan

Proceedings of the 58th Annual ACM Symposium on Theory of Computing, 2026

The Importance of Being Smoothly Calibrated.

Parikshit Gopalan, Konstantinos Stavropoulos, Kunal Talwar, Pranay Tankala

Proceedings of the 7th Symposium on Foundations of Responsible Computing, 2026

2025

Testing Noise Assumptions of Learning Algorithms.

Surbhi Goel, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan

CoRR, January, 2025

The Power of Iterative Filtering for Supervised Learning with (Heavy) Contamination.

Adam R. Klivans, Konstantinos Stavropoulos, Kevin Tian, Arsen Vasilyan

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Learning Neural Networks with Distribution Shift: Efficiently Certifiable Guarantees.

Gautam Chandrasekaran, Adam R. Klivans, Lin Lin Lee, Konstantinos Stavropoulos

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Learning Constant-Depth Circuits in Malicious Noise Models.

Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan

Proceedings of the Thirty Eighth Annual Conference on Learning Theory, 2025

2024

Tolerant Algorithms for Learning with Arbitrary Covariate Shift.

Surbhi Goel, Abhishek Shetty, Konstantinos Stavropoulos, Arsen Vasilyan

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Efficient Discrepancy Testing for Learning with Distribution Shift.

Gautam Chandrasekaran, Adam R. Klivans, Vasilis Kontonis, Konstantinos Stavropoulos, Arsen Vasilyan

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random.

Gautam Chandrasekaran, Vasilis Kontonis, Konstantinos Stavropoulos, Kevin Tian

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

An Efficient Tester-Learner for Halfspaces.

Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds.

Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Testable Learning with Distribution Shift.

Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Smoothed Analysis for Learning Concepts with Low Intrinsic Dimension.

Gautam Chandrasekaran, Adam R. Klivans, Vasilis Kontonis, Raghu Meka, Konstantinos Stavropoulos

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

Tester-Learners for Halfspaces: Universal Algorithms.

Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Agnostically Learning Single-Index Models using Omnipredictors.

Aravind Gollakota, Parikshit Gopalan, Adam R. Klivans, Konstantinos Stavropoulos

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Disjoint dijoins for classes of dicuts in finite and infinite digraphs.

Jochen Pascal Gollin, Karl Heuer, Konstantinos Stavropoulos

Comb. Theory, 2022

Learning and Covering Sums of Independent Random Variables with Unbounded Support.

Alkis Kalavasis, Konstantinos Stavropoulos, Emmanouil Zampetakis

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Aggregating Incomplete and Noisy Rankings.

Dimitris Fotakis, Alkis Kalavasis, Konstantinos Stavropoulos

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021