Nikos Zarifis
24 papers · 2019–2025 · 4 venues · across top CS/AI venues
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Machine Learning
(22)
Optimization & Theory Β· Machine Learning
(22)
Core Methods
(19)
Mathematics & Optimization
(10)
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(8)
Optimization
(7)
Mathematics
(4)
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Optimization & Theory Β· Deep Learning
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Keywords
sample complexity
(9)
gaussian distribution
(8)
adversarial label noise
(7)
statistical query
(6)
halfspace learning
(6)
agnostic learning
(5)
pac learning
(5)
lower bound
(4)
robust learning
(4)
learning theory
(3)
massart noise
(3)
statistical query lower bound
(3)
constant-factor approximation
(3)
stochastic gradient descent
(3)
log-concave distribution
(3)
polynomial time algorithm
(2)
single neuron
(2)
non-convex optimization
(2)
mistake bound
(2)
relu activation
(2)
Papers
Online Linear Classification with Massart Noise
ICML 2025
Robustly Learning Monotone Generalized Linear Models via Data Augmentation
COLT 2025
A Near-optimal Algorithm for Learning Margin Halfspaces with Massart Noise
NeurIPS 2024
Reliable Learning of Halfspaces under Gaussian Marginals
NeurIPS 2024
Robustly Learning Single-Index Models via Alignment Sharpness
ICML 2024
Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models
NeurIPS 2024
Statistical Query Lower Bounds for Learning Truncated Gaussians
COLT 2024
Testable Learning of General Halfspaces with Adversarial Label Noise
COLT 2024
Efficient Testable Learning of Halfspaces with Adversarial Label Noise
NeurIPS 2023
Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise
COLT 2023
Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise
NeurIPS 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
Learning a Single Neuron with Adversarial Label Noise via Gradient Descent
COLT 2022
Learning General Halfspaces with Adversarial Label Noise via Online Gradient Descent
ICML 2022
Agnostic Proper Learning of Halfspaces under Gaussian Marginals
COLT 2021
Learning Online Algorithms with Distributional Advice
ICML 2021
The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals in the SQ Model
COLT 2021
Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks
COLT 2020
Learning Halfspaces with Massart Noise Under Structured Distributions
COLT 2020
Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs under Gaussian Marginals
NeurIPS 2020
Non-Convex SGD Learns Halfspaces with Adversarial Label Noise
NeurIPS 2020
Reallocating Multiple Facilities on the Line
IJCAI 2019