Publications

Adam Klivans, Konstantinos Stavropoulos, Arsen Vasilyan (2025). Learning Constant-Depth Circuits in Malicious Noise Models. COLT 2025.

Adam Klivans, Konstantinos Stavropoulos, Kevin Tian, Arsen Vasilyan (2025). The Power of Iterative Filtering for Supervised Learning with (Heavy) Contamination. Under review.

Gautam Chandrasekaran, Adam Klivans, Lin Lin Lee, Konstantinos Stavropoulos (2025). Learning Neural Networks with Distribution Shift: Efficiently Certifiable Guarantees. ICLR 2025.

Surbhi Goel, Adam Klivans, Konstantinos Stavropoulos, Arsen Vasilyan (2025). Testing Noise Assumptions of Learning Algorithms. Under review.

Gautam Chandrasekaran, Vasilis Kontonis, Konstantinos Stavropoulos, Kevin Tian (2024). Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random. NeurIPS 2024 Spotlight.

Surbhi Goel, Abhishek Shetty, Konstantinos Stavropoulos, Arsen Vasilyan (2024). Tolerant Algorithms for Learning with Arbitrary Covariate Shift. NeurIPS 2024 Spotlight.

Gautam Chandrasekaran, Adam Klivans, Vasilis Kontonis, Konstantinos Stavropoulos, Arsen Vasilyan (2024). Efficient Discrepancy Testing for Learning with Distribution Shift. NeurIPS 2024.

Gautam Chandrasekaran, Adam Klivans, Vasilis Kontonis, Raghu Meka, Konstantinos Stavropoulos (2024). Smoothed Analysis for Learning Concepts with Low Intrinsic Dimension. COLT 2024 Best Paper.

Adam Klivans, Konstantinos Stavropoulos, Arsen Vasilyan (2024). Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds. COLT 2024.

Adam Klivans, Konstantinos Stavropoulos, Arsen Vasilyan (2024). Testable Learning with Distribution Shift. COLT 2024.

Aravind Gollakota, Adam Klivans, Konstantinos Stavropoulos, Arsen Vasilyan (2024). An Efficient Tester-Learner for Halfspaces. ICLR 2024.

Aravind Gollakota, Adam Klivans, Konstantinos Stavropoulos, Arsen Vasilyan (2023). Tester-Learners for Halfspaces: Universal Algorithms. NeurIPS 2023 Oral.

Aravind Gollakota, Parikshit Gopalan, Adam Klivans, Konstantinos Stavropoulos (2023). Agnostically Learning Single-Index Models using Omnipredictors. NeurIPS 2023.

Alkis Kalavasis, Konstantinos Stavropoulos, Emmanouil Zampetakis (2022). Learning and Covering Sums of Independent Random Variables with Unbounded Support. NeurIPS 2022 Oral.

Dimitris Fotakis, Alkis Kalavasis, Konstantinos Stavropoulos (2021). Aggregating Incomplete and Noisy Rankings. AISTATS 2021.