Ilias Diakonikolas

ORCID

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 237

Top Venues

Publications

Xuefeng Du, Zhen Fang, Ilias Diakonikolas, Yixuan Li
How Does Unlabeled Data Provably Help Out-of-Distribution Detection? CoRR (2024)
Daniel M. Kane, Ilias Diakonikolas, Hanshen Xiao, Sihan Liu
Online Robust Mean Estimation. SODA (2024)
Ilias Diakonikolas, Daniel M. Kane
Efficiently Learning One-Hidden-Layer ReLU Networks via SchurPolynomials. COLT (2024)
Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas
Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination. CoRR (2024)
Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
Online Learning of Halfspaces with Massart Noise. CoRR (2024)
Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis
Statistical Query Lower Bounds for Learning Truncated Gaussians. COLT (2024)
Shuyao Li, Yu Cheng, Ilias Diakonikolas, Jelena Diakonikolas, Rong Ge, Stephen J. Wright
Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing. CoRR (2024)
Ilias Diakonikolas, Daniel M. Kane, Sihan Liu
Testing Closeness of Multivariate Distributions via Ramsey Theory. STOC (2024)
Nikos Zarifis, Puqian Wang, Ilias Diakonikolas, Jelena Diakonikolas
Robustly Learning Single-Index Models via Alignment Sharpness. CoRR (2024)
Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis
Statistical Query Lower Bounds for Learning Truncated Gaussians. CoRR (2024)
Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Sihan Liu, Nikos Zarifis
Super Non-singular Decompositions of Polynomials and Their Application to Robustly Learning Low-Degree PTFs. STOC (2024)
Ilias Diakonikolas, Daniel M. Kane, Sihan Liu, Nikos Zarifis
Testable Learning of General Halfspaces with Adversarial Label Noise. COLT (2024)
Ilias Diakonikolas, Daniel Kane, Lisheng Ren, Yuxin Sun
SQ Lower Bounds for Non-Gaussian Component Analysis with Weaker Assumptions. CoRR (2024)
Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Sihan Liu, Nikos Zarifis
Super Non-singular Decompositions of Polynomials and their Application to Robustly Learning Low-degree PTFs. CoRR (2024)
Xuefeng Du, Zhen Fang, Ilias Diakonikolas, Yixuan Li
How Does Unlabeled Data Provably Help Out-of-Distribution Detection? ICLR (2024)
Ilias Diakonikolas, Daniel Kane, Vasilis Kontonis, Sihan Liu, Nikos Zarifis
Efficient Testable Learning of Halfspaces with Adversarial Label Noise. NeurIPS (2023)
Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
Agnostically Learning Multi-index Models with Queries. CoRR (2023)
Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Sihan Liu, Nikos Zarifis
Efficient Testable Learning of Halfspaces with Adversarial Label Noise. CoRR (2023)
Ilias Diakonikolas, Daniel M. Kane
Efficiently Learning One-Hidden-Layer ReLU Networks via Schur Polynomials. CoRR (2023)
Ilias Diakonikolas, Daniel Kane, Ankit Pensia, Thanasis Pittas
Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA. ICML (2023)
Ilias Diakonikolas, Christos Tzamos, Daniel M. Kane
A Strongly Polynomial Algorithm for Approximate Forster Transforms and Its Application to Halfspace Learning. STOC (2023)
Ilias Diakonikolas, Daniel M. Kane, Sihan Liu
Testing Closeness of Multivariate Distributions via Ramsey Theory. CoRR (2023)
Ilias Diakonikolas, Daniel Kane, Lisheng Ren
Near-Optimal Cryptographic Hardness of Agnostically Learning Halfspaces and ReLU Regression under Gaussian Marginals. ICML (2023)
Ilias Diakonikolas, Daniel Kane, Yuxin Sun
SQ Lower Bounds for Learning Mixtures of Linear Classifiers. NeurIPS (2023)
Ilias Diakonikolas, Jelena Diakonikolas, Daniel Kane, Puqian Wang, Nikos Zarifis
Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise. NeurIPS (2023)
Ilias Diakonikolas, Daniel Kane, Lisheng Ren, Yuxin Sun
SQ Lower Bounds for Non-Gaussian Component Analysis with Weaker Assumptions. NeurIPS (2023)
Ilias Diakonikolas, Daniel M. Kane, Yuxin Sun
SQ Lower Bounds for Learning Mixtures of Linear Classifiers. CoRR (2023)
Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, Thanasis Pittas
Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA. CoRR (2023)
Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas
Robustly Learning a Single Neuron via Sharpness. CoRR (2023)
Ilias Diakonikolas, Sushrut Karmalkar, Jong Ho Park, Christos Tzamos
Distribution-Independent Regression for Generalized Linear Models with Oblivious Corruptions. CoRR (2023)
Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis
Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise. COLT (2023)
Ilias Diakonikolas, Daniel M. Kane, Lisheng Ren
Near-Optimal Cryptographic Hardness of Agnostically Learning Halfspaces and ReLU Regression under Gaussian Marginals. CoRR (2023)
Ilias Diakonikolas, Daniel M. Kane, Yuetian Luo, Anru Zhang
Statistical and Computational Limits for Tensor-on-Tensor Association Detection. COLT (2023)
Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee, Ankit Pensia, Thanasis Pittas
A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm. CoRR (2023)
Ilias Diakonikolas, Daniel Kane, Ankit Pensia, Thanasis Pittas
Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression. NeurIPS (2023)
Ilias Diakonikolas, Sushrut Karmalkar, Jong Ho Park, Christos Tzamos
First Order Stochastic Optimization with Oblivious Noise. NeurIPS (2023)
Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
Self-Directed Linear Classification. COLT (2023)
Daniel M. Kane, Ilias Diakonikolas, Hanshen Xiao, Sihan Liu
Online Robust Mean Estimation. CoRR (2023)
Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis
Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise. CoRR (2023)
Shuyao Li, Yu Cheng, Ilias Diakonikolas, Jelena Diakonikolas, Rong Ge, Stephen J. Wright
Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing. NeurIPS (2023)
Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia
Gaussian Mean Testing Made Simple. SOSA (2023)
Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis
SQ Lower Bounds for Learning Mixtures of Separated and Bounded Covariance Gaussians. COLT (2023)
Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas
Robustly Learning a Single Neuron via Sharpness. ICML (2023)
Ilias Diakonikolas, Daniel Kane, Jasper C. H. Lee, Ankit Pensia, Thanasis Pittas
A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm. NeurIPS (2023)
Daniel Kane, Ilias Diakonikolas
A Nearly Tight Bound for Fitting an Ellipsoid to Gaussian Random Points. COLT (2023)
Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee, Thanasis Pittas
Clustering Mixtures of Bounded Covariance Distributions Under Optimal Separation. CoRR (2023)
Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis
SQ Lower Bounds for Learning Bounded Covariance GMMs. CoRR (2023)
Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
Self-Directed Linear Classification. CoRR (2023)
Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis
Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise. CoRR (2023)
Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, Thanasis Pittas
Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression. CoRR (2023)
Ilias Diakonikolas, Sushrut Karmalkar, Jong Ho Park, Christos Tzamos
Distribution-Independent Regression for Generalized Linear Models with Oblivious Corruptions. COLT (2023)
Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas
Robust Sparse Mean Estimation via Sum of Squares. CoRR (2022)
Ilias Diakonikolas, Christos Tzamos, Daniel M. Kane
A Strongly Polynomial Algorithm for Approximate Forster Transforms and its Application to Halfspace Learning. CoRR (2022)
Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi, Lisheng Ren
Cryptographic Hardness of Learning Halfspaces with Massart Noise. CoRR (2022)
Ilias Diakonikolas, Daniel Kane
Non-Gaussian Component Analysis via Lattice Basis Reduction. COLT (2022)
Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas
List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering. CoRR (2022)
Yu Cheng, Ilias Diakonikolas, Rong Ge, Shivam Gupta, Daniel Kane, Mahdi Soltanolkotabi
Outlier-Robust Sparse Estimation via Non-Convex Optimization. NeurIPS (2022)
Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
Learning General Halfspaces with Adversarial Label Noise via Online Gradient Descent. ICML (2022)
Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
Learning a Single Neuron with Adversarial Label Noise via Gradient Descent. CoRR (2022)
Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, Thanasis Pittas
Streaming Algorithms for High-Dimensional Robust Statistics. ICML (2022)
Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia
Gaussian Mean Testing Made Simple. CoRR (2022)
Ilias Diakonikolas, Daniel M. Kane, Lisheng Ren, Yuxin Sun
SQ Lower Bounds for Learning Single Neurons with Massart Noise. CoRR (2022)
Clément L. Canonne, Ilias Diakonikolas, Daniel Kane, Sihan Liu
Nearly-Tight Bounds for Testing Histogram Distributions. NeurIPS (2022)
Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee, Ankit Pensia
Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions. CoRR (2022)
Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas
List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering. NeurIPS (2022)
Ilias Diakonikolas, Daniel M. Kane, Yuxin Sun
Optimal SQ Lower Bounds for Robustly Learning Discrete Product Distributions and Ising Models. COLT (2022)
Ilias Diakonikolas, Chrystalla Pavlou, John Peebles, Alistair Stewart
Efficient Approximation Algorithms for the Inverse Semivalue Problem. AAMAS (2022)
Ilias Diakonikolas, Daniel Kane, Jasper C. H. Lee, Ankit Pensia
Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions. NeurIPS (2022)
Ilias Diakonikolas, Daniel Kane
Near-Optimal Statistical Query Hardness of Learning Halfspaces with Massart Noise. COLT (2022)
Ainesh Bakshi, Ilias Diakonikolas, He Jia, Daniel M. Kane, Pravesh K. Kothari, Santosh S. Vempala
arbitrary Gaussians. STOC (2022)
Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi, Lisheng Ren
Hardness of Learning a Single Neuron with Adversarial Label Noise. AISTATS (2022)
Ilias Diakonikolas, Christos Tzamos, Daniel Kane
A Strongly Polynomial Algorithm for Approximate Forster Transforms and its Application to Halfspace Learning. Electron. Colloquium Comput. Complex. (2022)
Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi, Lisheng Ren
Cryptographic Hardness of Learning Halfspaces with Massart Noise. NeurIPS (2022)
Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas
Robust Sparse Mean Estimation via Sum of Squares. COLT (2022)
Clément L. Canonne, Ilias Diakonikolas, Daniel M. Kane, Sihan Liu
Near-Optimal Bounds for Testing Histogram Distributions. CoRR (2022)
Xi Chen, Ilias Diakonikolas, Anthi Orfanou, Dimitris Paparas, Xiaorui Sun, Mihalis Yannakakis
On the Complexity of Optimal Lottery Pricing and Randomized Mechanisms for a Unit-Demand Buyer. SIAM J. Comput. 51 (3) (2022)
Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
Learning a Single Neuron with Adversarial Label Noise via Gradient Descent. COLT (2022)
Ilias Diakonikolas, Daniel Kane, Lisheng Ren, Yuxin Sun
SQ Lower Bounds for Learning Single Neurons with Massart Noise. NeurIPS (2022)
Ilias Diakonikolas, Daniel M. Kane, Yuxin Sun
Optimal SQ Lower Bounds for Robustly Learning Discrete Product Distributions and Ising Models. CoRR (2022)
Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, Thanasis Pittas
Streaming Algorithms for High-Dimensional Robust Statistics. CoRR (2022)
Daniel M. Kane, Ilias Diakonikolas
A Nearly Tight Bound for Fitting an Ellipsoid to Gaussian Random Points. CoRR (2022)
Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
Learning general halfspaces with general Massart noise under the Gaussian distribution. STOC (2022)
Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
Clustering mixture models in almost-linear time via list-decodable mean estimation. STOC (2022)
Ilias Diakonikolas, Daniel M. Kane
The Sample Complexity of Robust Covariance Testing. COLT (2021)
Ilias Diakonikolas, Russell Impagliazzo, Daniel M. Kane, Rex Lei, Jessica Sorrell, Christos Tzamos
Boosting in the Presence of Massart Noise. COLT (2021)
Ilias Diakonikolas, Daniel M. Kane
Non-Gaussian Component Analysis via Lattice Basis Reduction. CoRR (2021)
Yu Cheng, Ilias Diakonikolas, Daniel M. Kane, Rong Ge, Shivam Gupta, Mahdi Soltanolkotabi
Outlier-Robust Sparse Estimation via Non-Convex Optimization. CoRR (2021)
Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis
The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals. CoRR (2021)
Ilias Diakonikolas, Jongho Park, Christos Tzamos
ReLU Regression with Massart Noise. CoRR (2021)
Ilias Diakonikolas, Themis Gouleakis, Daniel M. Kane, John Peebles, Eric Price
Optimal testing of discrete distributions with high probability. STOC (2021)
Ilias Diakonikolas, Daniel Kane, Christos Tzamos
Forster Decomposition and Learning Halfspaces with Noise. NeurIPS (2021)
Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
Agnostic Proper Learning of Halfspaces under Gaussian Marginals. CoRR (2021)
Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean Estimation. CoRR (2021)
Ilias Diakonikolas, Daniel M. Kane, Christos Tzamos
Forster Decomposition and Learning Halfspaces with Noise. CoRR (2021)
Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis
The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals in the SQ Model. COLT (2021)
Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart, Yuxin Sun
Outlier-Robust Learning of Ising Models Under Dobrushin's Condition. CoRR (2021)
Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
Agnostic Proper Learning of Halfspaces under Gaussian Marginals. COLT (2021)
Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart
Robustness meets algorithms. Commun. ACM 64 (5) (2021)
Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
Threshold Phenomena in Learning Halfspaces with Massart Noise. CoRR (2021)
Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, Thanasis Pittas, Alistair Stewart
Statistical Query Lower Bounds for List-Decodable Linear Regression. CoRR (2021)

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Publication Activity (10 Years)

Top Topics

Top Venues

Ilias Diakonikolas