← Authors

Nikos Zarifis

24 papers · 2019–2025 · 4 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (9) 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer πŸ—ΊοΈ Taxonomy Completionist (23) 🌍 Conference Polyglot (4) πŸƒ Academic Marathon (6) 🀝 Dynamic Duo (23) πŸ† Keyword Champion (2) πŸ”¬ Deep Specialist (14) πŸ”₯ Unstoppable (7) πŸ’Ž Century Club (24) πŸ—ƒοΈ Keyword Collector (64) ⚑ Prolific Year (6)

Conferences

COLT (11) NIPS (7) ICML (5) IJCAI (1)

Top co-authors

Ilias Diakonikolas (23) Vasilis Kontonis (10) Christos Tzamos (8) Jelena Diakonikolas (6) Puqian Wang (6) Daniel M. Kane (5) Daniel Kane (4) Thanasis Pittas (3) Sihan Liu (2) Panagiotis Kostopanagiotis (1)

Research topics

Probability (1)

Keywords

sample complexity (7) gaussian distribution (7) adversarial label noise (7) statistical query (6) agnostic learning (5) pac learning (4) halfspace learning (4) log-concave distribution (3) learning theory (3) robust learning (3) stochastic gradient descent (3) lower bound (3) single neuron (2) non-convex optimization (2) halfspace classification (2) massart noise (2) relu activation (2) online algorithm (2) polynomial time algorithm (2) margin halfspace (2)

Papers

Online Linear Classification with Massart Noise ICML 2025
Robustly Learning Monotone Generalized Linear Models via Data Augmentation COLT 2025
Statistical Query Lower Bounds for Learning Truncated Gaussians COLT 2024
Reliable Learning of Halfspaces under Gaussian Marginals NIPS 2024
Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models NIPS 2024
A Near-optimal Algorithm for Learning Margin Halfspaces with Massart Noise NIPS 2024
Robustly Learning Single-Index Models via Alignment Sharpness ICML 2024
Testable Learning of General Halfspaces with Adversarial Label Noise COLT 2024
Efficient Testable Learning of Halfspaces with Adversarial Label Noise NIPS 2023
Robustly Learning a Single Neuron via Sharpness ICML 2023
Self-Directed Linear Classification COLT 2023
SQ Lower Bounds for Learning Mixtures of Separated and Bounded Covariance Gaussians COLT 2023
Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise NIPS 2023
Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise COLT 2023
Learning General Halfspaces with Adversarial Label Noise via Online Gradient Descent ICML 2022
Learning a Single Neuron with Adversarial Label Noise via Gradient Descent COLT 2022
Learning Online Algorithms with Distributional Advice ICML 2021
Agnostic Proper Learning of Halfspaces under Gaussian Marginals COLT 2021
The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals in the SQ Model COLT 2021
Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs under Gaussian Marginals NIPS 2020
Non-Convex SGD Learns Halfspaces with Adversarial Label Noise NIPS 2020
Learning Halfspaces with Massart Noise Under Structured Distributions COLT 2020
Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks COLT 2020
Reallocating Multiple Facilities on the Line IJCAI 2019