Zarifis, Nikos

25 publications

ICML 2025 Online Linear Classification with Massart Noise Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis

COLT 2025 Robustly Learning Monotone Generalized Linear Models via Data Augmentation Nikos Zarifis, Puqian Wang, Ilias Diakonikolas, Jelena Diakonikolas

NeurIPS 2025 Robustly Learning Monotone Single-Index Models Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas

NeurIPS 2024 A Near-Optimal Algorithm for Learning Margin Halfspaces with Massart Noise Ilias Diakonikolas, Nikos Zarifis

NeurIPS 2024 Reliable Learning of Halfspaces Under Gaussian Marginals Ilias Diakonikolas, Lisheng Ren, Nikos Zarifis

ICML 2024 Robustly Learning Single-Index Models via Alignment Sharpness Nikos Zarifis, Puqian Wang, Ilias Diakonikolas, Jelena Diakonikolas

NeurIPS 2024 Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas

COLT 2024 Statistical Query Lower Bounds for Learning Truncated Gaussians Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis

COLT 2024 Testable Learning of General Halfspaces with Adversarial Label Noise Ilias Diakonikolas, Daniel Kane, Sihan Liu, Nikos Zarifis

NeurIPS 2023 Efficient Testable Learning of Halfspaces with Adversarial Label Noise Ilias Diakonikolas, Daniel Kane, Vasilis Kontonis, Sihan Liu, Nikos Zarifis

COLT 2023 Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis

NeurIPS 2023 Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise Ilias Diakonikolas, Jelena Diakonikolas, Daniel Kane, Puqian Wang, Nikos Zarifis

ICML 2023 Robustly Learning a Single Neuron via Sharpness Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas

COLT 2023 SQ Lower Bounds for Learning Mixtures of Separated and Bounded Covariance Gaussians Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis

COLT 2023 Self-Directed Linear Classification Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis

ICML 2022 Learning General Halfspaces with Adversarial Label Noise via Online Gradient Descent Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis

COLT 2022 Learning a Single Neuron with Adversarial Label Noise via Gradient Descent Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis

COLT 2021 Agnostic Proper Learning of Halfspaces Under Gaussian Marginals Ilias Diakonikolas, Daniel M Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis

ICML 2021 Learning Online Algorithms with Distributional Advice Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Ali Vakilian, Nikos Zarifis

COLT 2021 The Optimality of Polynomial Regression for Agnostic Learning Under Gaussian Marginals in the SQ Model Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis

COLT 2020 Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Nikos Zarifis

COLT 2020 Learning Halfspaces with Massart Noise Under Structured Distributions Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis

NeurIPS 2020 Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs Under Gaussian Marginals Ilias Diakonikolas, Daniel Kane, Nikos Zarifis

NeurIPS 2020 Non-Convex SGD Learns Halfspaces with Adversarial Label Noise Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis

IJCAI 2019 Reallocating Multiple Facilities on the Line Dimitris Fotakis, Loukas Kavouras, Panagiotis Kostopanagiotis, Philip Lazos, Stratis Skoulakis, Nikos Zarifis