Ilias Diakonikolas

387 papers A* 154A 7Misc 1Journal 213Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Expressivity-Efficiency Tradeoffs for Hybrid Sequence Models. CoRR John Cooper, Ilias Diakonikolas, Mingchen Ma, Frederic Sala
2026	J	`jnl`	High-Dimensional Gaussian Mean Estimation under Realizable Contamination. CoRR Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas
2026	J	`jnl`	Sample Complexity Bounds for Robust Mean Estimation with Mean-Shift Contamination. CoRR Ilias Diakonikolas, Giannis Iakovidis, Daniel M. Kane, Sihan Liu
2026	J	`jnl`	Statistical Query Lower Bounds for Smoothed Agnostic Learning. CoRR Ilias Diakonikolas, Daniel M. Kane
2026	J	`jnl`	Testable Learning of General Halfspaces under Massart Noise. CoRR Ilias Diakonikolas, Giannis Iakovidis, Daniel M. Kane, Sihan Liu
2025	J	`jnl`	A Near-optimal Algorithm for Learning Margin Halfspaces with Massart Noise. CoRR Ilias Diakonikolas, Nikos Zarifis
2025	J	`jnl`	Active Learning of General Halfspaces: Label Queries vs Membership Queries. CoRR Ilias Diakonikolas, Daniel M. Kane, Mingchen Ma
2025	J	`jnl`	Agnostic Product Mixed State Tomography via Robust Statistics. CoRR Alvan Arulandu, Ilias Diakonikolas, Daniel M. Kane, Jerry Zheng Li
2025	J	`jnl`	Algorithms and SQ Lower Bounds for Robustly Learning Real-valued Multi-index Models. CoRR Ilias Diakonikolas, Giannis Iakovidis, Daniel M. Kane, Lisheng Ren
2025	A*	`conf`	Batch List-Decodable Linear Regression via Higher Moments. ICML Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Sihan Liu, Thanasis Pittas
2025	J	`jnl`	Batch List-Decodable Linear Regression via Higher Moments. CoRR Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Sihan Liu, Thanasis Pittas
2025	A*	`conf`	Clustering Mixtures of Bounded Covariance Distributions Under Optimal Separation. SODA Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee, Thanasis Pittas
2025	J	`jnl`	Distributionally Robust Optimization with Adversarial Data Contamination. CoRR Shuyao Li, Ilias Diakonikolas, Jelena Diakonikolas
2025	A*	`conf`	Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination. ICML Ilias Diakonikolas, Giannis Iakovidis, Daniel Kane, Thanasis Pittas
2025	J	`jnl`	Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination. CoRR Ilias Diakonikolas, Giannis Iakovidis, Daniel M. Kane, Thanasis Pittas
2025	A*	`conf`	Entangled Mean Estimation in High Dimensions. STOC Ilias Diakonikolas, Daniel M. Kane, Sihan Liu, Thanasis Pittas
2025	J	`jnl`	Entangled Mean Estimation in High-Dimensions. CoRR Ilias Diakonikolas, Daniel M. Kane, Sihan Liu, Thanasis Pittas
2025	A*	`conf`	Faster Algorithms for Agnostically Learning Disjunctions and their Implications. COLT Ilias Diakonikolas, Daniel M. Kane, Lisheng Ren
2025	J	`jnl`	Faster Algorithms for Agnostically Learning Disjunctions and their Implications. CoRR Ilias Diakonikolas, Daniel M. Kane, Lisheng Ren
2025	A*	`conf`	Implicit High-Order Moment Tensor Estimation and Learning Latent Variable Models. FOCS Ilias Diakonikolas, Daniel M. Kane
2025	J	`jnl`	Information-Computation Tradeoffs for Noiseless Linear Regression with Oblivious Contamination. CoRR Ilias Diakonikolas, Chao Gao, Daniel M. Kane, John Lafferty, Ankit Pensia
2025	A*	`conf`	Learning Intersections of Two Margin Halfspaces under Factorizable Distributions. COLT Ilias Diakonikolas, Mingchen Ma, Lisheng Ren, Christos Tzamos
2025	J	`jnl`	Learning Intersections of Two Margin Halfspaces under Factorizable Distributions. CoRR Ilias Diakonikolas, Mingchen Ma, Lisheng Ren, Christos Tzamos
2025	J	`jnl`	Linear Regression under Missing or Corrupted Coordinates. CoRR Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Jasper C. H. Lee, Thanasis Pittas
2025	A*	`conf`	On Fine-Grained Distinct Element Estimation. ICML Ilias Diakonikolas, Daniel Kane, Jasper C. H. Lee, Thanasis Pittas, David P. Woodruff, Samson Zhou
2025	J	`jnl`	On Fine-Grained Distinct Element Estimation. CoRR Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee, Thanasis Pittas, David P. Woodruff, Samson Zhou
2025	A*	`conf`	On Learning Parallel Pancakes with Mostly Uniform Weights. ICML Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Jasper C. H. Lee, Thanasis Pittas
2025	J	`jnl`	On Learning Parallel Pancakes with Mostly Uniform Weights. CoRR Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Jasper C. H. Lee, Thanasis Pittas
2025	A*	`conf`	Online Linear Classification with Massart Noise. ICML Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2025	A*	`conf`	PTF Testing Lower Bounds for Non-Gaussian Component Analysis. FOCS Ilias Diakonikolas, Daniel M. Kane, Sihan Liu, Thanasis Pittas
2025	J	`jnl`	PTF Testing Lower Bounds for Non-Gaussian Component Analysis. CoRR Ilias Diakonikolas, Daniel M. Kane, Sihan Liu, Thanasis Pittas
2025	J	`jnl`	Replicable Distribution Testing. CoRR Ilias Diakonikolas, Jingyi Gao, Daniel M. Kane, Sihan Liu, Christopher Ye
2025	A*	`conf`	Robust Learning of Multi-index Models via Iterative Subspace Approximation. FOCS Ilias Diakonikolas, Giannis Iakovidis, Daniel M. Kane, Nikos Zarifis
2025	J	`jnl`	Robust Learning of Multi-index Models via Iterative Subspace Approximation. CoRR Ilias Diakonikolas, Giannis Iakovidis, Daniel M. Kane, Nikos Zarifis
2025	A*	`conf`	Robustly Learning Monotone Generalized Linear Models via Data Augmentation. COLT Nikos Zarifis, Puqian Wang, Ilias Diakonikolas, Jelena Diakonikolas
2025	J	`jnl`	Robustly Learning Monotone Generalized Linear Models via Data Augmentation. CoRR Nikos Zarifis, Puqian Wang, Ilias Diakonikolas, Jelena Diakonikolas
2025	J	`jnl`	Robustly Learning Monotone Single-Index Models. CoRR Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas
2025	A*	`conf`	SoS Certifiability of Subgaussian Distributions and Its Algorithmic Applications. STOC Ilias Diakonikolas, Samuel B. Hopkins, Ankit Pensia, Stefan Tiegel
2025	A*	`conf`	SoS Certificates for Sparse Singular Values and Their Applications: Robust Statistics, Subspace Distortion, and More. STOC Ilias Diakonikolas, Samuel B. Hopkins, Ankit Pensia, Stefan Tiegel
2025	A*	`conf`	Statistical Query Hardness of Multiclass Linear Classification with Random Classification Noise. ICML Ilias Diakonikolas, Mingchen Ma, Lisheng Ren, Christos Tzamos
2025	J	`jnl`	Statistical Query Hardness of Multiclass Linear Classification with Random Classification Noise. CoRR Ilias Diakonikolas, Mingchen Ma, Lisheng Ren, Christos Tzamos
2024	A*	`conf`	A Near-optimal Algorithm for Learning Margin Halfspaces with Massart Noise. NeurIPS Ilias Diakonikolas, Nikos Zarifis
2024	A*	`conf`	Active Learning of General Halfspaces: Label Queries vs Membership Queries. NeurIPS Ilias Diakonikolas, Daniel M. Kane, Mingchen Ma
2024	A*	`conf`	Agnostically Learning Multi-Index Models with Queries. FOCS Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2024	J	`jnl`	Efficient Testable Learning of General Halfspaces with Adversarial Label Noise. CoRR Ilias Diakonikolas, Daniel M. Kane, Sihan Liu, Nikos Zarifis
2024	A*	`conf`	Efficiently Learning One-Hidden-Layer ReLU Networks via SchurPolynomials. COLT Ilias Diakonikolas, Daniel M. Kane
2024	A*	`conf`	Fast Co-Training under Weak Dependence via Stream-Based Active Learning. ICML Ilias Diakonikolas, Mingchen Ma, Lisheng Ren, Christos Tzamos
2024	J	`jnl`	First Order Stochastic Optimization with Oblivious Noise. CoRR Ilias Diakonikolas, Sushrut Karmalkar, Jongho Park, Christos Tzamos
2024	A*	`conf`	How Does Unlabeled Data Provably Help Out-of-Distribution Detection? ICLR Xuefeng Du, Zhen Fang, Ilias Diakonikolas, Yixuan Li
2024	J	`jnl`	How Does Unlabeled Data Provably Help Out-of-Distribution Detection? CoRR Xuefeng Du, Zhen Fang, Ilias Diakonikolas, Yixuan Li
2024	J	`jnl`	Implicit High-Order Moment Tensor Estimation and Learning Latent Variable Models. CoRR Ilias Diakonikolas, Daniel M. Kane
2024	A*	`conf`	Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise. NeurIPS Shuyao Li, Sushrut Karmalkar, Ilias Diakonikolas, Jelena Diakonikolas
2024	J	`jnl`	Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise. CoRR Shuyao Li, Sushrut Karmalkar, Ilias Diakonikolas, Jelena Diakonikolas
2024	J	`jnl`	Online Learning of Halfspaces with Massart Noise. CoRR Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2024	A*	`conf`	Online Robust Mean Estimation. SODA Daniel M. Kane, Ilias Diakonikolas, Hanshen Xiao, Sihan Liu
2024	A*	`conf`	Reliable Learning of Halfspaces under Gaussian Marginals. NeurIPS Ilias Diakonikolas, Lisheng Ren, Nikos Zarifis
2024	J	`jnl`	Reliable Learning of Halfspaces under Gaussian Marginals. CoRR Ilias Diakonikolas, Lisheng Ren, Nikos Zarifis
2024	J	`jnl`	Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing. CoRR Shuyao Li, Yu Cheng, Ilias Diakonikolas, Jelena Diakonikolas, Rong Ge, Stephen J. Wright
2024	A*	`conf`	Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination. ICML Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas
2024	J	`jnl`	Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination. CoRR Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas
2024	A*	`conf`	Robustly Learning Single-Index Models via Alignment Sharpness. ICML Nikos Zarifis, Puqian Wang, Ilias Diakonikolas, Jelena Diakonikolas
2024	J	`jnl`	Robustly Learning Single-Index Models via Alignment Sharpness. CoRR Nikos Zarifis, Puqian Wang, Ilias Diakonikolas, Jelena Diakonikolas
2024	J	`jnl`	SQ Lower Bounds for Non-Gaussian Component Analysis with Weaker Assumptions. CoRR Ilias Diakonikolas, Daniel Kane, Lisheng Ren, Yuxin Sun
2024	A*	`conf`	Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models. NeurIPS Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas
2024	J	`jnl`	Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models. CoRR Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas
2024	J	`jnl`	SoS Certifiability of Subgaussian Distributions and its Algorithmic Applications. CoRR Ilias Diakonikolas, Samuel B. Hopkins, Ankit Pensia, Stefan Tiegel
2024	J	`jnl`	SoS Certificates for Sparse Singular Values and Their Applications: Robust Statistics, Subspace Distortion, and More. CoRR Ilias Diakonikolas, Samuel B. Hopkins, Ankit Pensia, Stefan Tiegel
2024	A*	`conf`	Statistical Query Lower Bounds for Learning Truncated Gaussians. COLT Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis
2024	J	`jnl`	Statistical Query Lower Bounds for Learning Truncated Gaussians. CoRR Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis
2024	A*	`conf`	Sum-of-Squares Lower Bounds for Non-Gaussian Component Analysis. FOCS Ilias Diakonikolas, Sushrut Karmalkar, Shuo Pang, Aaron Potechin
2024	J	`jnl`	Sum-of-squares lower bounds for Non-Gaussian Component Analysis. CoRR Ilias Diakonikolas, Sushrut Karmalkar, Shuo Pang, Aaron Potechin
2024	A*	`conf`	Super Non-singular Decompositions of Polynomials and Their Application to Robustly Learning Low-Degree PTFs. STOC Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Sihan Liu, Nikos Zarifis
2024	J	`jnl`	Super Non-singular Decompositions of Polynomials and their Application to Robustly Learning Low-degree PTFs. CoRR Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Sihan Liu, Nikos Zarifis
2024	A*	`conf`	Testable Learning of General Halfspaces with Adversarial Label Noise. COLT Ilias Diakonikolas, Daniel M. Kane, Sihan Liu, Nikos Zarifis
2024	A*	`conf`	Testing Closeness of Multivariate Distributions via Ramsey Theory. STOC Ilias Diakonikolas, Daniel M. Kane, Sihan Liu
2023	A*	`conf`	A Nearly Tight Bound for Fitting an Ellipsoid to Gaussian Random Points. COLT Daniel Kane, Ilias Diakonikolas
2023	A*	`conf`	A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm. NeurIPS Ilias Diakonikolas, Daniel Kane, Jasper C. H. Lee, Ankit Pensia, Thanasis Pittas
2023	J	`jnl`	A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm. CoRR Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee, Ankit Pensia, Thanasis Pittas
2023	A*	`conf`	A Strongly Polynomial Algorithm for Approximate Forster Transforms and Its Application to Halfspace Learning. STOC Ilias Diakonikolas, Christos Tzamos, Daniel M. Kane
2023	J	`jnl`	Agnostically Learning Multi-index Models with Queries. CoRR Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2023	J	`jnl`	Clustering Mixtures of Bounded Covariance Distributions Under Optimal Separation. CoRR Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee, Thanasis Pittas
2023	A*	`conf`	Distribution-Independent Regression for Generalized Linear Models with Oblivious Corruptions. COLT Ilias Diakonikolas, Sushrut Karmalkar, Jongho Park, Christos Tzamos
2023	J	`jnl`	Distribution-Independent Regression for Generalized Linear Models with Oblivious Corruptions. CoRR Ilias Diakonikolas, Sushrut Karmalkar, Jongho Park, Christos Tzamos
2023	A*	`conf`	Efficient Testable Learning of Halfspaces with Adversarial Label Noise. NeurIPS Ilias Diakonikolas, Daniel Kane, Vasilis Kontonis, Sihan Liu, Nikos Zarifis
2023	J	`jnl`	Efficient Testable Learning of Halfspaces with Adversarial Label Noise. CoRR Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Sihan Liu, Nikos Zarifis
2023	J	`jnl`	Efficiently Learning One-Hidden-Layer ReLU Networks via Schur Polynomials. CoRR Ilias Diakonikolas, Daniel M. Kane
2023	A*	`conf`	First Order Stochastic Optimization with Oblivious Noise. NeurIPS Ilias Diakonikolas, Sushrut Karmalkar, Jongho Park, Christos Tzamos
2023	—	`conf`	Gaussian Mean Testing Made Simple. SOSA Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia
2023	A*	`conf`	Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise. COLT Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis
2023	J	`jnl`	Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise. CoRR Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis
2023	A*	`conf`	Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression. NeurIPS Ilias Diakonikolas, Daniel Kane, Ankit Pensia, Thanasis Pittas
2023	J	`jnl`	Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression. CoRR Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, Thanasis Pittas
2023	A*	`conf`	Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise. NeurIPS Ilias Diakonikolas, Jelena Diakonikolas, Daniel Kane, Puqian Wang, Nikos Zarifis
2023	J	`jnl`	Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise. CoRR Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane, Puqian Wang, Nikos Zarifis
2023	A*	`conf`	Near-Optimal Cryptographic Hardness of Agnostically Learning Halfspaces and ReLU Regression under Gaussian Marginals. ICML Ilias Diakonikolas, Daniel Kane, Lisheng Ren
2023	J	`jnl`	Near-Optimal Cryptographic Hardness of Agnostically Learning Halfspaces and ReLU Regression under Gaussian Marginals. CoRR Ilias Diakonikolas, Daniel M. Kane, Lisheng Ren
2023	A*	`conf`	Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA. ICML Ilias Diakonikolas, Daniel Kane, Ankit Pensia, Thanasis Pittas
2023	J	`jnl`	Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA. CoRR Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, Thanasis Pittas
2023	J	`jnl`	Online Robust Mean Estimation. CoRR Daniel M. Kane, Ilias Diakonikolas, Hanshen Xiao, Sihan Liu
2023	A*	`conf`	Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing. NeurIPS Shuyao Li, Yu Cheng, Ilias Diakonikolas, Jelena Diakonikolas, Rong Ge, Stephen J. Wright
2023	A*	`conf`	Robustly Learning a Single Neuron via Sharpness. ICML Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas
2023	J	`jnl`	Robustly Learning a Single Neuron via Sharpness. CoRR Puqian Wang, Nikos Zarifis, Ilias Diakonikolas, Jelena Diakonikolas
2023	J	`jnl`	SQ Lower Bounds for Learning Bounded Covariance GMMs. CoRR Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis
2023	A*	`conf`	SQ Lower Bounds for Learning Mixtures of Linear Classifiers. NeurIPS Ilias Diakonikolas, Daniel Kane, Yuxin Sun
2023	J	`jnl`	SQ Lower Bounds for Learning Mixtures of Linear Classifiers. CoRR Ilias Diakonikolas, Daniel M. Kane, Yuxin Sun
2023	A*	`conf`	SQ Lower Bounds for Learning Mixtures of Separated and Bounded Covariance Gaussians. COLT Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis
2023	A*	`conf`	SQ Lower Bounds for Non-Gaussian Component Analysis with Weaker Assumptions. NeurIPS Ilias Diakonikolas, Daniel Kane, Lisheng Ren, Yuxin Sun
2023	A*	`conf`	Self-Directed Linear Classification. COLT Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2023	J	`jnl`	Self-Directed Linear Classification. CoRR Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2023	A*	`conf`	Statistical and Computational Limits for Tensor-on-Tensor Association Detection. COLT Ilias Diakonikolas, Daniel M. Kane, Yuetian Luo, Anru Zhang
2023	J	`jnl`	Testing Closeness of Multivariate Distributions via Ramsey Theory. CoRR Ilias Diakonikolas, Daniel M. Kane, Sihan Liu
2022	J	`jnl`	A Nearly Tight Bound for Fitting an Ellipsoid to Gaussian Random Points. CoRR Daniel M. Kane, Ilias Diakonikolas
2022	J	`jnl`	A Strongly Polynomial Algorithm for Approximate Forster Transforms and its Application to Halfspace Learning. CoRR Ilias Diakonikolas, Christos Tzamos, Daniel M. Kane
2022	J	`jnl`	A Strongly Polynomial Algorithm for Approximate Forster Transforms and its Application to Halfspace Learning. Electron. Colloquium Comput. Complex. Ilias Diakonikolas, Christos Tzamos, Daniel Kane
2022	A*	`conf`	Clustering mixture models in almost-linear time via list-decodable mean estimation. STOC Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
2022	A*	`conf`	Cryptographic Hardness of Learning Halfspaces with Massart Noise. NeurIPS Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi, Lisheng Ren
2022	J	`jnl`	Cryptographic Hardness of Learning Halfspaces with Massart Noise. CoRR Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi, Lisheng Ren
2022	A	`conf`	Efficient Approximation Algorithms for the Inverse Semivalue Problem. AAMAS Ilias Diakonikolas, Chrystalla Pavlou, John Peebles, Alistair Stewart
2022	J	`jnl`	Gaussian Mean Testing Made Simple. CoRR Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia
2022	A	`conf`	Hardness of Learning a Single Neuron with Adversarial Label Noise. AISTATS Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi, Lisheng Ren
2022	A*	`conf`	Learning General Halfspaces with Adversarial Label Noise via Online Gradient Descent. ICML Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2022	A*	`conf`	Learning a Single Neuron with Adversarial Label Noise via Gradient Descent. COLT Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2022	J	`jnl`	Learning a Single Neuron with Adversarial Label Noise via Gradient Descent. CoRR Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2022	A*	`conf`	Learning general halfspaces with general Massart noise under the Gaussian distribution. STOC Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2022	A*	`conf`	List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering. NeurIPS Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas
2022	J	`jnl`	List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering. CoRR Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas
2022	J	`jnl`	Near-Optimal Bounds for Testing Histogram Distributions. CoRR Clément L. Canonne, Ilias Diakonikolas, Daniel M. Kane, Sihan Liu
2022	A*	`conf`	Near-Optimal Statistical Query Hardness of Learning Halfspaces with Massart Noise. COLT Ilias Diakonikolas, Daniel Kane
2022	A*	`conf`	Nearly-Tight Bounds for Testing Histogram Distributions. NeurIPS Clément L. Canonne, Ilias Diakonikolas, Daniel Kane, Sihan Liu
2022	A*	`conf`	Non-Gaussian Component Analysis via Lattice Basis Reduction. COLT Ilias Diakonikolas, Daniel Kane
2022	J	`jnl`	On the Complexity of Optimal Lottery Pricing and Randomized Mechanisms for a Unit-Demand Buyer. SIAM J. Comput. Xi Chen, Ilias Diakonikolas, Anthi Orfanou, Dimitris Paparas, Xiaorui Sun, Mihalis Yannakakis
2022	A*	`conf`	Optimal SQ Lower Bounds for Robustly Learning Discrete Product Distributions and Ising Models. COLT Ilias Diakonikolas, Daniel M. Kane, Yuxin Sun
2022	J	`jnl`	Optimal SQ Lower Bounds for Robustly Learning Discrete Product Distributions and Ising Models. CoRR Ilias Diakonikolas, Daniel M. Kane, Yuxin Sun
2022	A*	`conf`	Outlier-Robust Sparse Estimation via Non-Convex Optimization. NeurIPS Yu Cheng, Ilias Diakonikolas, Rong Ge, Shivam Gupta, Daniel Kane, Mahdi Soltanolkotabi
2022	A*	`conf`	Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions. NeurIPS Ilias Diakonikolas, Daniel Kane, Jasper C. H. Lee, Ankit Pensia
2022	J	`jnl`	Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions. CoRR Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee, Ankit Pensia
2022	A*	`conf`	Robust Sparse Mean Estimation via Sum of Squares. COLT Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas
2022	J	`jnl`	Robust Sparse Mean Estimation via Sum of Squares. CoRR Ilias Diakonikolas, Daniel M. Kane, Sushrut Karmalkar, Ankit Pensia, Thanasis Pittas
2022	A*	`conf`	Robustly learning mixtures of STOC Ainesh Bakshi, Ilias Diakonikolas, He Jia, Daniel M. Kane, Pravesh K. Kothari, Santosh S. Vempala
2022	A*	`conf`	SQ Lower Bounds for Learning Single Neurons with Massart Noise. NeurIPS Ilias Diakonikolas, Daniel Kane, Lisheng Ren, Yuxin Sun
2022	J	`jnl`	SQ Lower Bounds for Learning Single Neurons with Massart Noise. CoRR Ilias Diakonikolas, Daniel M. Kane, Lisheng Ren, Yuxin Sun
2022	A*	`conf`	Streaming Algorithms for High-Dimensional Robust Statistics. ICML Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, Thanasis Pittas
2022	J	`jnl`	Streaming Algorithms for High-Dimensional Robust Statistics. CoRR Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, Thanasis Pittas
2021	A*	`conf`	Agnostic Proper Learning of Halfspaces under Gaussian Marginals. COLT Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2021	J	`jnl`	Agnostic Proper Learning of Halfspaces under Gaussian Marginals. CoRR Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2021	A*	`conf`	Boosting in the Presence of Massart Noise. COLT Ilias Diakonikolas, Russell Impagliazzo, Daniel M. Kane, Rex Lei, Jessica Sorrell, Christos Tzamos
2021	J	`jnl`	Boosting in the Presence of Massart Noise. CoRR Ilias Diakonikolas, Russell Impagliazzo, Daniel Kane, Rex Lei, Jessica Sorrell, Christos Tzamos
2021	J	`jnl`	Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean Estimation. CoRR Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
2021	A*	`conf`	Efficiently learning halfspaces with Tsybakov noise. STOC Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2021	A*	`conf`	Forster Decomposition and Learning Halfspaces with Noise. NeurIPS Ilias Diakonikolas, Daniel Kane, Christos Tzamos
2021	J	`jnl`	Forster Decomposition and Learning Halfspaces with Noise. CoRR Ilias Diakonikolas, Daniel M. Kane, Christos Tzamos
2021	A*	`conf`	Learning Online Algorithms with Distributional Advice. ICML Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Ali Vakilian, Nikos Zarifis
2021	A*	`conf`	List-Decodable Mean Estimation in Nearly-PCA Time. NeurIPS Ilias Diakonikolas, Daniel Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
2021	J	`jnl`	Non-Gaussian Component Analysis via Lattice Basis Reduction. CoRR Ilias Diakonikolas, Daniel M. Kane
2021	A*	`conf`	Optimal testing of discrete distributions with high probability. STOC Ilias Diakonikolas, Themis Gouleakis, Daniel M. Kane, John Peebles, Eric Price
2021	A*	`conf`	Outlier-Robust Learning of Ising Models Under Dobrushin's Condition. COLT Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart, Yuxin Sun
2021	J	`jnl`	Outlier-Robust Learning of Ising Models Under Dobrushin's Condition. CoRR Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart, Yuxin Sun
2021	J	`jnl`	Outlier-Robust Sparse Estimation via Non-Convex Optimization. CoRR Yu Cheng, Ilias Diakonikolas, Daniel M. Kane, Rong Ge, Shivam Gupta, Mahdi Soltanolkotabi
2021	A*	`conf`	Rapid Approximate Aggregation with Distribution-Sensitive Interval Guarantees. ICDE Stephen Macke, Maryam Aliakbarpour, Ilias Diakonikolas, Aditya G. Parameswaran, Ronitt Rubinfeld
2021	A*	`conf`	ReLU Regression with Massart Noise. NeurIPS Ilias Diakonikolas, Jongho Park, Christos Tzamos
2021	J	`jnl`	ReLU Regression with Massart Noise. CoRR Ilias Diakonikolas, Jongho Park, Christos Tzamos
2021	J	`jnl`	Robustness meets algorithms. Commun. ACM Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart
2021	A*	`conf`	Statistical Query Lower Bounds for List-Decodable Linear Regression. NeurIPS Ilias Diakonikolas, Daniel Kane, Ankit Pensia, Thanasis Pittas, Alistair Stewart
2021	J	`jnl`	Statistical Query Lower Bounds for List-Decodable Linear Regression. CoRR Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia, Thanasis Pittas, Alistair Stewart
2021	A*	`conf`	The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals in the SQ Model. COLT Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis
2021	J	`jnl`	The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals. CoRR Ilias Diakonikolas, Daniel M. Kane, Thanasis Pittas, Nikos Zarifis
2021	A*	`conf`	The Sample Complexity of Robust Covariance Testing. COLT Ilias Diakonikolas, Daniel M. Kane
2021	J	`jnl`	Threshold Phenomena in Learning Halfspaces with Massart Noise. CoRR Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2020	J	`jnl`	A Polynomial Time Algorithm for Learning Halfspaces with Tsybakov Noise. CoRR Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2020	A*	`conf`	Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks. COLT Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Nikos Zarifis
2020	J	`jnl`	Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks. CoRR Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Nikos Zarifis
2020	A*	`conf`	Approximation Schemes for ReLU Regression. COLT Ilias Diakonikolas, Surbhi Goel, Sushrut Karmalkar, Adam R. Klivans, Mahdi Soltanolkotabi
2020	J	`jnl`	Approximation Schemes for ReLU Regression. CoRR Ilias Diakonikolas, Surbhi Goel, Sushrut Karmalkar, Adam R. Klivans, Mahdi Soltanolkotabi
2020	J	`jnl`	Efficient Algorithms for Multidimensional Segmented Regression. CoRR Ilias Diakonikolas, Jerry Li, Anastasia Voloshinov
2020	A*	`conf`	Efficiently Learning Adversarially Robust Halfspaces with Noise. ICML Omar Montasser, Surbhi Goel, Ilias Diakonikolas, Nathan Srebro
2020	J	`jnl`	Efficiently Learning Adversarially Robust Halfspaces with Noise. CoRR Omar Montasser, Surbhi Goel, Ilias Diakonikolas, Nathan Srebro
2020	J	`jnl`	Hardness of Learning Halfspaces with Massart Noise. CoRR Ilias Diakonikolas, Daniel M. Kane
2020	J	`jnl`	High-Dimensional Robust Mean Estimation via Gradient Descent. CoRR Yu Cheng, Ilias Diakonikolas, Rong Ge, Mahdi Soltanolkotabi
2020	A*	`conf`	High-dimensional Robust Mean Estimation via Gradient Descent. ICML Yu Cheng, Ilias Diakonikolas, Rong Ge, Mahdi Soltanolkotabi
2020	A*	`conf`	Learning Halfspaces with Massart Noise Under Structured Distributions. COLT Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2020	J	`jnl`	Learning Halfspaces with Massart Noise Under Structured Distributions. CoRR Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2020	J	`jnl`	Learning Halfspaces with Tsybakov Noise. CoRR Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2020	J	`jnl`	List-Decodable Mean Estimation in Nearly-PCA Time. CoRR Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
2020	A*	`conf`	List-Decodable Mean Estimation via Iterative Multi-Filtering. NeurIPS Ilias Diakonikolas, Daniel Kane, Daniel Kongsgaard
2020	J	`jnl`	List-Decodable Mean Estimation via Iterative Multi-Filtering. CoRR Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard
2020	J	`jnl`	Near-Optimal Disjoint-Path Facility Location Through Set Cover by Pairs. Oper. Res. David S. Johnson, Lee Breslau, Ilias Diakonikolas, Nick Duffield, Yu Gu, MohammadTaghi Hajiaghayi, Howard J. Karloff, Mauricio G. C. Resende, Subhabrata Sen
2020	A*	`conf`	Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs under Gaussian Marginals. NeurIPS Ilias Diakonikolas, Daniel Kane, Nikos Zarifis
2020	J	`jnl`	Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs under Gaussian Marginals. CoRR Ilias Diakonikolas, Daniel M. Kane, Nikos Zarifis
2020	A*	`conf`	Non-Convex SGD Learns Halfspaces with Adversarial Label Noise. NeurIPS Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2020	J	`jnl`	Non-Convex SGD Learns Halfspaces with Adversarial Label Noise. CoRR Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
2020	J	`jnl`	Optimal Testing of Discrete Distributions with High Probability. CoRR Ilias Diakonikolas, Themis Gouleakis, Daniel M. Kane, John Peebles, Eric Price
2020	J	`jnl`	Optimal Testing of Discrete Distributions with High Probability. Electron. Colloquium Comput. Complex. Ilias Diakonikolas, Themis Gouleakis, Daniel Kane, John Peebles, Eric Price
2020	A*	`conf`	Outlier Robust Mean Estimation with Subgaussian Rates via Stability. NeurIPS Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia
2020	J	`jnl`	Outlier Robust Mean Estimation with Subgaussian Rates via Stability. CoRR Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia
2020	A*	`conf`	Outlier-Robust Clustering of Gaussians and Other Non-Spherical Mixtures. FOCS Ainesh Bakshi, Ilias Diakonikolas, Samuel B. Hopkins, Daniel Kane, Sushrut Karmalkar, Pravesh K. Kothari
2020	J	`jnl`	Rapid Approximate Aggregation with Distribution-Sensitive Interval Guarantees. CoRR Stephen Macke, Maryam Aliakbarpour, Ilias Diakonikolas, Aditya G. Parameswaran, Ronitt Rubinfeld
2020	—	`ch.`	Robust High-Dimensional Statistics. Beyond the Worst-Case Analysis of Algorithms Ilias Diakonikolas, Daniel M. Kane
2020	J	`jnl`	Robustly Learning Mixtures of k Arbitrary Gaussians. CoRR Ainesh Bakshi, Ilias Diakonikolas, He Jia, Daniel M. Kane, Pravesh K. Kothari, Santosh S. Vempala
2020	J	`jnl`	Robustly Learning any Clusterable Mixture of Gaussians. CoRR Ilias Diakonikolas, Samuel B. Hopkins, Daniel Kane, Sushrut Karmalkar
2020	A*	`conf`	Small Covers for Near-Zero Sets of Polynomials and Learning Latent Variable Models. FOCS Ilias Diakonikolas, Daniel M. Kane
2020	J	`jnl`	Small Covers for Near-Zero Sets of Polynomials and Learning Latent Variable Models. CoRR Ilias Diakonikolas, Daniel M. Kane
2020	J	`jnl`	Testing Bayesian Networks. IEEE Trans. Inf. Theory Clément L. Canonne, Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2020	A*	`conf`	The Complexity of Adversarially Robust Proper Learning of Halfspaces with Agnostic Noise. NeurIPS Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi
2020	J	`jnl`	The Complexity of Adversarially Robust Proper Learning of Halfspaces with Agnostic Noise. CoRR Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi
2020	J	`jnl`	The Sample Complexity of Robust Covariance Testing. CoRR Ilias Diakonikolas, Daniel M. Kane
2019	A*	`conf`	A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families. NeurIPS Brian Axelrod, Ilias Diakonikolas, Alistair Stewart, Anastasios Sidiropoulos, Gregory Valiant
2019	J	`jnl`	A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families. CoRR Brian Axelrod, Ilias Diakonikolas, Anastasios Sidiropoulos, Alistair Stewart, Gregory Valiant
2019	J	`jnl`	Collision-Based Testers are Optimal for Uniformity and Closeness. Chic. J. Theor. Comput. Sci. Ilias Diakonikolas, Themis Gouleakis, John Peebles, Eric Price
2019	A*	`conf`	Communication and Memory Efficient Testing of Discrete Distributions. COLT Ilias Diakonikolas, Themis Gouleakis, Daniel M. Kane, Sankeerth Rao
2019	J	`jnl`	Communication and Memory Efficient Testing of Discrete Distributions. CoRR Ilias Diakonikolas, Themis Gouleakis, Daniel M. Kane, Sankeerth Rao
2019	A*	`conf`	Degree-푑 chow parameters robustly determine degree-푑 PTFs (and algorithmic applications). STOC Ilias Diakonikolas, Daniel M. Kane
2019	A*	`conf`	Distribution-Independent PAC Learning of Halfspaces with Massart Noise. NeurIPS Ilias Diakonikolas, Themis Gouleakis, Christos Tzamos
2019	J	`jnl`	Distribution-Independent PAC Learning of Halfspaces with Massart Noise. CoRR Ilias Diakonikolas, Themis Gouleakis, Christos Tzamos
2019	A*	`conf`	Efficient Algorithms and Lower Bounds for Robust Linear Regression. SODA Ilias Diakonikolas, Weihao Kong, Alistair Stewart
2019	A*	`conf`	Equipping Experts/Bandits with Long-term Memory. NeurIPS Kai Zheng, Haipeng Luo, Ilias Diakonikolas, Liwei Wang
2019	J	`jnl`	Equipping Experts/Bandits with Long-term Memory. CoRR Kai Zheng, Haipeng Luo, Ilias Diakonikolas, Liwei Wang
2019	A*	`conf`	Faster Algorithms for High-Dimensional Robust Covariance Estimation. COLT Yu Cheng, Ilias Diakonikolas, Rong Ge, David P. Woodruff
2019	J	`jnl`	Faster Algorithms for High-Dimensional Robust Covariance Estimation. CoRR Yu Cheng, Ilias Diakonikolas, Rong Ge, David P. Woodruff
2019	A*	`conf`	High-Dimensional Robust Mean Estimation in Nearly-Linear Time. SODA Yu Cheng, Ilias Diakonikolas, Rong Ge
2019	A*	`conf`	Nearly Tight Bounds for Robust Proper Learning of Halfspaces with a Margin. NeurIPS Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi
2019	J	`jnl`	Nearly Tight Bounds for Robust Proper Learning of Halfspaces with a Margin. CoRR Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi
2019	A*	`conf`	On the Complexity of the Inverse Semivalue Problem for Weighted Voting Games. AAAI Ilias Diakonikolas, Chrystalla Pavlou
2019	A*	`conf`	Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering. NeurIPS Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Eric Price, Alistair Stewart
2019	J	`jnl`	Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering. CoRR Ilias Diakonikolas, Sushrut Karmalkar, Daniel Kane, Eric Price, Alistair Stewart
2019	A*	`conf`	Private Testing of Distributions via Sample Permutations. NeurIPS Maryam Aliakbarpour, Ilias Diakonikolas, Daniel Kane, Ronitt Rubinfeld
2019	J	`jnl`	Recent Advances in Algorithmic High-Dimensional Robust Statistics. CoRR Ilias Diakonikolas, Daniel M. Kane
2019	J	`jnl`	Robust Estimators in High-Dimensions Without the Computational Intractability. SIAM J. Comput. Ilias Diakonikolas, Gautam Kamath, Daniel Kane, Jerry Li, Ankur Moitra, Alistair Stewart
2019	A*	`conf`	Sever: A Robust Meta-Algorithm for Stochastic Optimization. ICML Ilias Diakonikolas, Gautam Kamath, Daniel Kane, Jerry Li, Jacob Steinhardt, Alistair Stewart
2019	A*	`conf`	Testing Identity of Multidimensional Histograms. COLT Ilias Diakonikolas, Daniel M. Kane, John Peebles
2018	J	`jnl`	A Polynomial Time Algorithm for Maximum Likelihood Estimation of Multivariate Log-concave Densities. CoRR Ilias Diakonikolas, Anastasios Sidiropoulos, Alistair Stewart
2018	J	`jnl`	Degree-$d$ Chow Parameters Robustly Determine Degree-$d$ PTFs (and Algorithmic Applications). Electron. Colloquium Comput. Complex. Ilias Diakonikolas, Daniel Kane
2018	J	`jnl`	Degree-d Chow Parameters Robustly Determine Degree-d PTFs (and Algorithmic Applications). CoRR Ilias Diakonikolas, Daniel M. Kane
2018	A*	`conf`	Differentially Private Identity and Equivalence Testing of Discrete Distributions. ICML Maryam Aliakbarpour, Ilias Diakonikolas, Ronitt Rubinfeld
2018	J	`jnl`	Efficient Algorithms and Lower Bounds for Robust Linear Regression. CoRR Ilias Diakonikolas, Weihao Kong, Alistair Stewart
2018	A*	`conf`	Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms. COLT Ilias Diakonikolas, Jerry Li, Ludwig Schmidt
2018	J	`jnl`	Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms. CoRR Ilias Diakonikolas, Jerry Li, Ludwig Schmidt
2018	J	`jnl`	High-Dimensional Robust Mean Estimation in Nearly-Linear Time. CoRR Yu Cheng, Ilias Diakonikolas, Rong Ge
2018	A*	`conf`	Learning geometric concepts with nasty noise. STOC Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2018	A*	`conf`	List-decodable robust mean estimation and learning mixtures of spherical gaussians. STOC Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2018	A*	`conf`	Near-Optimal Sample Complexity Bounds for Maximum Likelihood Estimation of Multivariate Log-concave Densities. COLT Timothy Carpenter, Ilias Diakonikolas, Anastasios Sidiropoulos, Alistair Stewart
2018	J	`jnl`	Near-Optimal Sample Complexity Bounds for Maximum Likelihood Estimation of Multivariate Log-concave Densities. CoRR Timothy Carpenter, Ilias Diakonikolas, Anastasios Sidiropoulos, Alistair Stewart
2018	J	`jnl`	On the Complexity of the Inverse Semivalue Problem for Weighted Voting Games. CoRR Ilias Diakonikolas, Chrystalla Pavlou
2018	A*	`ed.`	Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2018, Los Angeles, CA, USA, June 25-29, 2018 STOC Ilias Diakonikolas, David Kempe, Monika Henzinger
2018	A*	`conf`	Robust Learning of Fixed-Structure Bayesian Networks. NeurIPS Yu Cheng, Ilias Diakonikolas, Daniel Kane, Alistair Stewart
2018	A*	`conf`	Robustly Learning a Gaussian: Getting Optimal Error, Efficiently. SODA Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart
2018	A*	`conf`	Sample-Optimal Identity Testing with High Probability. ICALP Ilias Diakonikolas, Themis Gouleakis, John Peebles, Eric Price
2018	J	`jnl`	Sever: A Robust Meta-Algorithm for Stochastic Optimization. CoRR Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Jacob Steinhardt, Alistair Stewart
2018	A*	`conf`	Sharp Bounds for Generalized Uniformity Testing. NeurIPS Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2018	Misc	`conf`	Testing Conditional Independence of Discrete Distributions. ITA Clément L. Canonne, Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2018	J	`jnl`	Testing Identity of Multidimensional Histograms. CoRR Ilias Diakonikolas, Daniel M. Kane, John Peebles
2018	J	`jnl`	Testing Shape Restrictions of Discrete Distributions. Theory Comput. Syst. Clément L. Canonne, Ilias Diakonikolas, Themis Gouleakis, Ronitt Rubinfeld
2018	A*	`conf`	Testing conditional independence of discrete distributions. STOC Clément L. Canonne, Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2018	A*	`conf`	Testing for Families of Distributions via the Fourier Transform. NeurIPS Alistair Stewart, Ilias Diakonikolas, Clément L. Canonne
2018	J	`jnl`	The complexity of optimal multidimensional pricing for a unit-demand buyer. Games Econ. Behav. Xi Chen, Ilias Diakonikolas, Dimitris Paparas, Xiaorui Sun, Mihalis Yannakakis
2017	A*	`conf`	Being Robust (in High Dimensions) Can Be Practical. ICML Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart
2017	J	`jnl`	Being Robust (in High Dimensions) Can Be Practical. CoRR Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart
2017	—	`conf`	Communication-Efficient Distributed Learning of Discrete Distributions. NIPS Ilias Diakonikolas, Elena Grigorescu, Jerry Li, Abhiram Natarajan, Krzysztof Onak, Ludwig Schmidt
2017	J	`jnl`	Differentially Private Identity and Closeness Testing of Discrete Distributions. CoRR Maryam Aliakbarpour, Ilias Diakonikolas, Ronitt Rubinfeld
2017	J	`jnl`	Fourier-Based Testing for Families of Distributions. CoRR Clément L. Canonne, Ilias Diakonikolas, Alistair Stewart
2017	J	`jnl`	Fourier-Based Testing for Families of Distributions. Electron. Colloquium Comput. Complex. Clément L. Canonne, Ilias Diakonikolas, Alistair Stewart
2017	J	`jnl`	Learning Geometric Concepts with Nasty Noise. CoRR Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2017	A*	`conf`	Learning Multivariate Log-concave Distributions. COLT Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2017	J	`jnl`	List-Decodable Robust Mean Estimation and Learning Mixtures of Spherical Gaussians. CoRR Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2017	A*	`conf`	Near-Optimal Closeness Testing of Discrete Histogram Distributions. ICALP Ilias Diakonikolas, Daniel M. Kane, Vladimir Nikishkin
2017	J	`jnl`	Near-Optimal Closeness Testing of Discrete Histogram Distributions. CoRR Ilias Diakonikolas, Daniel M. Kane, Vladimir Nikishkin
2017	A*	`conf`	Playing Anonymous Games using Simple Strategies. SODA Yu Cheng, Ilias Diakonikolas, Alistair Stewart
2017	J	`jnl`	Robustly Learning a Gaussian: Getting Optimal Error, Efficiently. CoRR Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart
2017	A*	`conf`	Sample-Optimal Density Estimation in Nearly-Linear Time. SODA Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt
2017	J	`jnl`	Sample-Optimal Identity Testing with High Probability. CoRR Ilias Diakonikolas, Themis Gouleakis, John Peebles, Eric Price
2017	J	`jnl`	Sample-Optimal Identity Testing with High Probability. Electron. Colloquium Comput. Complex. Ilias Diakonikolas, Themis Gouleakis, John Peebles, Eric Price
2017	J	`jnl`	Sharp Bounds for Generalized Uniformity Testing. CoRR Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2017	J	`jnl`	Sharp Bounds for Generalized Uniformity Testing. Electron. Colloquium Comput. Complex. Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2017	A*	`conf`	Statistical Query Lower Bounds for Robust Estimation of High-Dimensional Gaussians and Gaussian Mixtures. FOCS Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2017	A*	`conf`	Testing Bayesian Networks. COLT Clément L. Canonne, Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2017	J	`jnl`	Testing Conditional Independence of Discrete Distributions. CoRR Clément L. Canonne, Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2017	J	`jnl`	The Inverse Shapley value problem. Games Econ. Behav. Anindya De, Ilias Diakonikolas, Rocco A. Servedio
2016	A*	`conf`	A New Approach for Testing Properties of Discrete Distributions. FOCS Ilias Diakonikolas, Daniel M. Kane
2016	J	`jnl`	A New Approach for Testing Properties of Discrete Distributions. CoRR Ilias Diakonikolas, Daniel M. Kane
2016	J	`jnl`	A New Approach for Testing Properties of Discrete Distributions. Electron. Colloquium Comput. Complex. Ilias Diakonikolas, Daniel M. Kane
2016	J	`jnl`	A Robust Khintchine Inequality, and Algorithms for Computing Optimal Constants in Fourier Analysis and High-Dimensional Geometry. SIAM J. Discret. Math. Anindya De, Ilias Diakonikolas, Rocco A. Servedio
2016	J	`jnl`	Collision-based Testers are Optimal for Uniformity and Closeness. CoRR Ilias Diakonikolas, Themis Gouleakis, John Peebles, Eric Price
2016	J	`jnl`	Collision-based Testers are Optimal for Uniformity and Closeness. Electron. Colloquium Comput. Complex. Ilias Diakonikolas, Themis Gouleakis, John Peebles, Eric Price
2016	J	`jnl`	Efficient Robust Proper Learning of Log-concave Distributions. CoRR Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2016	A*	`conf`	Fast Algorithms for Segmented Regression. ICML Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt
2016	J	`jnl`	Fast Algorithms for Segmented Regression. CoRR Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt
2016	J	`jnl`	How Good is the Chord Algorithm? SIAM J. Comput. Constantinos Daskalakis, Ilias Diakonikolas, Mihalis Yannakakis
2016	J	`jnl`	Learning Multivariate Log-concave Distributions. CoRR Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2016	—	`ch.`	Learning Structured Distributions. Handbook of Big Data Ilias Diakonikolas
2016	J	`jnl`	Near-Optimal Disjoint-Path Facility Location Through Set Cover by Pairs. CoRR David S. Johnson, Lee Breslau, Ilias Diakonikolas, Nick G. Duffield, Yu Gu, MohammadTaghi Hajiaghayi, Howard J. Karloff, Mauricio G. C. Resende, Subhabrata Sen
2016	A*	`conf`	Optimal Learning via the Fourier Transform for Sums of Independent Integer Random Variables. COLT Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2016	J	`jnl`	Playing Anonymous Games using Simple Strategies. CoRR Yu Cheng, Ilias Diakonikolas, Alistair Stewart
2016	A*	`conf`	Properly Learning Poisson Binomial Distributions in Almost Polynomial Time. COLT Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2016	A*	`conf`	Robust Estimators in High Dimensions without the Computational Intractability. FOCS Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart
2016	J	`jnl`	Robust Estimators in High Dimensions without the Computational Intractability. CoRR Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Zheng Li, Ankur Moitra, Alistair Stewart
2016	J	`jnl`	Robust Learning of Fixed-Structure Bayesian Networks. CoRR Yu Cheng, Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2016	J	`jnl`	Statistical Query Lower Bounds for Robust Estimation of High-dimensional Gaussians and Gaussian Mixtures. CoRR Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2016	J	`jnl`	Statistical Query Lower Bounds for Robust Estimation of High-dimensional Gaussians and Gaussian Mixtures. Electron. Colloquium Comput. Complex. Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2016	J	`jnl`	Testing Bayesian Networks. CoRR Clément L. Canonne, Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2016	A	`conf`	Testing Shape Restrictions of Discrete Distributions. STACS Clément L. Canonne, Ilias Diakonikolas, Themis Gouleakis, Ronitt Rubinfeld
2016	A*	`conf`	The fourier transform of poisson multinomial distributions and its algorithmic applications. STOC Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2015	—	`conf`	Differentially Private Learning of Structured Discrete Distributions. NIPS Ilias Diakonikolas, Moritz Hardt, Ludwig Schmidt
2015	A*	`conf`	Fast and Near-Optimal Algorithms for Approximating Distributions by Histograms. PODS Jayadev Acharya, Ilias Diakonikolas, Chinmay Hegde, Jerry Zheng Li, Ludwig Schmidt
2015	J	`jnl`	Learning Poisson Binomial Distributions. Algorithmica Constantinos Daskalakis, Ilias Diakonikolas, Rocco A. Servedio
2015	A*	`conf`	Learning from satisfying assignments. SODA Anindya De, Ilias Diakonikolas, Rocco A. Servedio
2015	J	`jnl`	Nearly Optimal Learning and Sparse Covers for Sums of Independent Integer Random Variables. CoRR Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2015	J	`jnl`	Noise Stable Halfspaces are Close to Very Small Juntas. Chic. J. Theor. Comput. Sci. Ilias Diakonikolas, Ragesh Jaiswal, Rocco A. Servedio, Li-Yang Tan, Andrew Wan
2015	A*	`conf`	On the Complexity of Optimal Lottery Pricing and Randomized Mechanisms. FOCS Xi Chen, Ilias Diakonikolas, Anthi Orfanou, Dimitris Paparas, Xiaorui Sun, Mihalis Yannakakis
2015	A*	`conf`	Optimal Algorithms and Lower Bounds for Testing Closeness of Structured Distributions. FOCS Ilias Diakonikolas, Daniel M. Kane, Vladimir Nikishkin
2015	J	`jnl`	Optimal Algorithms and Lower Bounds for Testing Closeness of Structured Distributions. CoRR Ilias Diakonikolas, Daniel M. Kane, Vladimir Nikishkin
2015	J	`jnl`	Properly Learning Poisson Binomial Distributions in Almost Polynomial Time. CoRR Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2015	J	`jnl`	Sample-Optimal Density Estimation in Nearly-Linear Time. CoRR Jayadev Acharya, Ilias Diakonikolas, Jerry Zheng Li, Ludwig Schmidt
2015	A*	`conf`	Testing Identity of Structured Distributions. SODA Ilias Diakonikolas, Daniel M. Kane, Vladimir Nikishkin
2015	J	`jnl`	Testing Shape Restrictions of Discrete Distributions. CoRR Clément L. Canonne, Ilias Diakonikolas, Themis Gouleakis, Ronitt Rubinfeld
2015	J	`jnl`	The Fourier Transform of Poisson Multinomial Distributions and its Algorithmic Applications. CoRR Ilias Diakonikolas, Daniel M. Kane, Alistair Stewart
2014	A*	`conf`	A Polynomial-time Approximation Scheme for Fault-tolerant Distributed Storage. SODA Constantinos Daskalakis, Anindya De, Ilias Diakonikolas, Ankur Moitra, Rocco A. Servedio
2014	J	`jnl`	A Regularity Lemma and Low-Weight Approximators for Low-Degree Polynomial Threshold Functions. Theory Comput. Ilias Diakonikolas, Rocco A. Servedio, Li-Yang Tan, Andrew Wan
2014	J	`jnl`	Average Sensitivity and Noise Sensitivity of Polynomial Threshold Functions. SIAM J. Comput. Ilias Diakonikolas, Prasad Raghavendra, Rocco A. Servedio, Li-Yang Tan
2014	A	`conf`	Deterministic Approximate Counting for Juntas of Degree-2 Polynomial Threshold Functions. CCC Anindya De, Ilias Diakonikolas, Rocco A. Servedio
2014	A*	`conf`	Efficient density estimation via piecewise polynomial approximation. STOC Siu On Chan, Ilias Diakonikolas, Rocco A. Servedio, Xiaorui Sun
2014	J	`jnl`	Learning Theory Comput. Constantinos Daskalakis, Ilias Diakonikolas, Rocco A. Servedio
2014	—	`conf`	Near-Optimal Density Estimation in Near-Linear Time Using Variable-Width Histograms. NIPS Siu On Chan, Ilias Diakonikolas, Rocco A. Servedio, Xiaorui Sun
2014	J	`jnl`	Near-Optimal Density Estimation in Near-Linear Time Using Variable-Width Histograms. CoRR Siu On Chan, Ilias Diakonikolas, Rocco A. Servedio, Xiaorui Sun
2014	J	`jnl`	Nearly Optimal Solutions for the Chow Parameters Problem and Low-Weight Approximation of Halfspaces. J. ACM Anindya De, Ilias Diakonikolas, Vitaly Feldman, Rocco A. Servedio
2014	A*	`conf`	Optimal Algorithms for Testing Closeness of Discrete Distributions. SODA Siu On Chan, Ilias Diakonikolas, Paul Valiant, Gregory Valiant
2014	J	`jnl`	Testing Identity of Structured Distributions. CoRR Ilias Diakonikolas, Daniel M. Kane, Vladimir Nikishkin
2014	A*	`conf`	The Complexity of Optimal Multidimensional Pricing. SODA Xi Chen, Ilias Diakonikolas, Dimitris Paparas, Xiaorui Sun, Mihalis Yannakakis
2013	J	`jnl`	A Polynomial-time Approximation Scheme for Fault-tolerant Distributed Storage. CoRR Constantinos Daskalakis, Anindya De, Ilias Diakonikolas, Ankur Moitra, Rocco A. Servedio
2013	—	`conf`	A Robust Khintchine Inequality, and Algorithms for Computing Optimal Constants in Fourier Analysis and High-Dimensional Geometry. ICALP (1) Anindya De, Ilias Diakonikolas, Rocco A. Servedio
2013	J	`jnl`	Deterministic Approximate Counting for Degree-$2$ Polynomial Threshold Functions. CoRR Anindya De, Ilias Diakonikolas, Rocco A. Servedio
2013	J	`jnl`	Deterministic Approximate Counting for Degree-2 Polynomial Threshold Functions. Electron. Colloquium Comput. Complex. Anindya De, Ilias Diakonikolas, Rocco A. Servedio
2013	J	`jnl`	Deterministic Approximate Counting for Juntas of Degree-$2$ Polynomial Threshold Functions. CoRR Anindya De, Ilias Diakonikolas, Rocco A. Servedio
2013	J	`jnl`	Deterministic Approximate Counting for Juntas of Degree-2 Polynomial Threshold Functions. Electron. Colloquium Comput. Complex. Anindya De, Ilias Diakonikolas, Rocco A. Servedio
2013	J	`jnl`	Efficient Density Estimation via Piecewise Polynomial Approximation CoRR Siu On Chan, Ilias Diakonikolas, Rocco A. Servedio, Xiaorui Sun
2013	J	`jnl`	How good is the Chord algorithm? CoRR Constantinos Daskalakis, Ilias Diakonikolas, Mihalis Yannakakis
2013	J	`jnl`	Improved Approximation of Linear Threshold Functions. Comput. Complex. Ilias Diakonikolas, Rocco A. Servedio
2013	A*	`conf`	Learning Sums of Independent Integer Random Variables. FOCS Constantinos Daskalakis, Ilias Diakonikolas, Ryan O'Donnell, Rocco A. Servedio, Li-Yang Tan
2013	A*	`conf`	Learning mixtures of structured distributions over discrete domains. SODA Siu On Chan, Ilias Diakonikolas, Rocco A. Servedio, Xiaorui Sun
2013	J	`jnl`	Optimal Algorithms for Testing Closeness of Discrete Distributions. CoRR Siu On Chan, Ilias Diakonikolas, Gregory Valiant, Paul Valiant
2013	A*	`conf`	Testing SODA Constantinos Daskalakis, Ilias Diakonikolas, Rocco A. Servedio, Gregory Valiant, Paul Valiant
2013	J	`jnl`	The Complexity of Optimal Multidimensional Pricing. CoRR Xi Chen, Ilias Diakonikolas, Dimitris Paparas, Xiaorui Sun, Mihalis Yannakakis
2012	J	`jnl`	A robust Khintchine inequality, and algorithms for computing optimal constants in Fourier analysis and high-dimensional geometry. CoRR Anindya De, Ilias Diakonikolas, Rocco A. Servedio
2012	—	`conf`	Efficiency-Revenue Trade-Offs in Auctions. ICALP (2) Ilias Diakonikolas, Christos H. Papadimitriou, George Pierrakos, Yaron Singer
2012	J	`jnl`	Efficiency-Revenue Trade-offs in Auctions CoRR Ilias Diakonikolas, Christos H. Papadimitriou, George Pierrakos, Yaron Singer
2012	J	`jnl`	Inverse Problems in Approximate Uniform Generation. Electron. Colloquium Comput. Complex. Anindya De, Ilias Diakonikolas, Rocco A. Servedio
2012	J	`jnl`	Inverse problems in approximate uniform generation CoRR Anindya De, Ilias Diakonikolas, Rocco A. Servedio
2012	A*	`conf`	Learning SODA Constantinos Daskalakis, Ilias Diakonikolas, Rocco A. Servedio
2012	J	`jnl`	Learning mixtures of structured distributions over discrete domains CoRR Siu On Chan, Ilias Diakonikolas, Rocco A. Servedio, Xiaorui Sun
2012	A*	`conf`	Learning poisson binomial distributions. STOC Constantinos Daskalakis, Ilias Diakonikolas, Rocco A. Servedio
2012	J	`jnl`	Nearly optimal solutions for the Chow Parameters Problem and low-weight approximation of halfspaces CoRR Anindya De, Ilias Diakonikolas, Vitaly Feldman, Rocco A. Servedio
2012	J	`jnl`	Nearly optimal solutions for the Chow Parameters Problem and low-weight approximation of halfspaces. Electron. Colloquium Comput. Complex. Anindya De, Ilias Diakonikolas, Vitaly Feldman, Rocco A. Servedio
2012	A*	`conf`	Nearly optimal solutions for the chow parameters problem and low-weight approximation of halfspaces. STOC Anindya De, Ilias Diakonikolas, Vitaly Feldman, Rocco A. Servedio
2012	J	`jnl`	On the Distribution of the Fourier Spectrum of Halfspaces CoRR Ilias Diakonikolas, Ragesh Jaiswal, Rocco A. Servedio, Li-Yang Tan, Andrew Wan
2012	J	`jnl`	The Inverse Shapley Value Problem CoRR Anindya De, Ilias Diakonikolas, Rocco A. Servedio
2012	—	`conf`	The Inverse Shapley Value Problem. ICALP (1) Anindya De, Ilias Diakonikolas, Rocco A. Servedio
2012	J	`jnl`	The Inverse Shapley Value Problem. Electron. Colloquium Comput. Complex. Anindya De, Ilias Diakonikolas, Rocco A. Servedio
2011	—	`—`	Approximation of Multiobjective Optimization Problems. Ilias Diakonikolas
2011	A	`conf`	Disjoint-Path Facility Location: Theory and Practice. ALENEX Lee Breslau, Ilias Diakonikolas, Nick G. Duffield, Yu Gu, Mohammad Taghi Hajiaghayi, David S. Johnson, Howard J. Karloff, Mauricio G. C. Resende, Subhabrata Sen
2011	J	`jnl`	Efficiently Testing Sparse Algorithmica Ilias Diakonikolas, Homin K. Lee, Kevin Matulef, Rocco A. Servedio, Andrew Wan
2011	A*	`conf`	Hardness Results for Agnostically Learning Low-Degree Polynomial Threshold Functions. SODA Ilias Diakonikolas, Ryan O'Donnell, Rocco A. Servedio, Yi Wu
2011	J	`jnl`	Learning $k$-Modal Distributions via Testing CoRR Constantinos Daskalakis, Ilias Diakonikolas, Rocco A. Servedio
2011	J	`jnl`	Learning Poisson Binomial Distributions CoRR Constantinos Daskalakis, Ilias Diakonikolas, Rocco A. Servedio
2011	J	`jnl`	Learning transformed product distributions CoRR Constantinos Daskalakis, Ilias Diakonikolas, Rocco A. Servedio
2011	A*	`conf`	Supervised design space exploration by compositional approximation of Pareto sets. DAC Hung-Yi Liu, Ilias Diakonikolas, Michele Petracca, Luca P. Carloni
2011	J	`jnl`	Testing $k$-Modal Distributions: Optimal Algorithms via Reductions CoRR Constantinos Daskalakis, Ilias Diakonikolas, Rocco A. Servedio, Gregory Valiant, Paul Valiant
2010	A	`conf`	A Regularity Lemma, and Low-Weight Approximators, for Low-Degree Polynomial Threshold Functions. CCC Ilias Diakonikolas, Rocco A. Servedio, Li-Yang Tan, Andrew Wan
2010	A*	`conf`	Bounded Independence Fools Degree-2 Threshold Functions. FOCS Ilias Diakonikolas, Daniel M. Kane, Jelani Nelson
2010	J	`jnl`	Bounded Independence Fools Halfspaces. SIAM J. Comput. Ilias Diakonikolas, Parikshit Gopalan, Ragesh Jaiswal, Rocco A. Servedio, Emanuele Viola
2010	A*	`conf`	Bounding the average sensitivity and noise sensitivity of polynomial threshold functions. STOC Ilias Diakonikolas, Prahladh Harsha, Adam R. Klivans, Raghu Meka, Prasad Raghavendra, Rocco A. Servedio, Li-Yang Tan
2010	J	`jnl`	Hardness Results for Agnostically Learning Low-Degree Polynomial Threshold Functions CoRR Ilias Diakonikolas, Ryan O'Donnell, Rocco A. Servedio, Yi Wu
2010	A*	`conf`	How Good is the Chord Algorithm?. SODA Constantinos Daskalakis, Ilias Diakonikolas, Mihalis Yannakakis
2009	J	`jnl`	A regularity lemma, and low-weight approximators, for low-degree polynomial threshold functions CoRR Ilias Diakonikolas, Rocco A. Servedio, Li-Yang Tan, Andrew Wan
2009	J	`jnl`	Average sensitivity and noise sensitivity of polynomial threshold functions CoRR Ilias Diakonikolas, Prasad Raghavendra, Rocco A. Servedio, Li-Yang Tan
2009	J	`jnl`	Bounded Independence Fools Degree-2 Threshold Functions CoRR Ilias Diakonikolas, Daniel M. Kane, Jelani Nelson
2009	J	`jnl`	Bounded Independence Fools Degree-2 Threshold Functions. Electron. Colloquium Comput. Complex. Ilias Diakonikolas, Daniel M. Kane, Jelani Nelson
2009	J	`jnl`	Bounded Independence Fools Halfspaces CoRR Ilias Diakonikolas, Parikshit Gopalan, Ragesh Jaiswal, Rocco A. Servedio, Emanuele Viola
2009	A*	`conf`	Bounded Independence Fools Halfspaces. FOCS Ilias Diakonikolas, Parikshit Gopalan, Ragesh Jaiswal, Rocco A. Servedio, Emanuele Viola
2009	J	`jnl`	Bounded Independence Fools Halfspaces. Electron. Colloquium Comput. Complex. Ilias Diakonikolas, Parikshit Gopalan, Ragesh Jaiswal, Rocco A. Servedio, Emanuele Viola
2009	J	`jnl`	Improved Approximation of Linear Threshold Functions CoRR Ilias Diakonikolas, Rocco A. Servedio
2009	A	`conf`	Improved Approximation of Linear Threshold Functions. CCC Ilias Diakonikolas, Rocco A. Servedio
2009	J	`jnl`	Small Approximate Pareto Sets for Biobjective Shortest Paths and Other Problems. SIAM J. Comput. Ilias Diakonikolas, Mihalis Yannakakis
2008	J	`jnl`	Efficiently Testing Sparse GF(2) Polynomials CoRR Ilias Diakonikolas, Homin K. Lee, Kevin Matulef, Rocco A. Servedio, Andrew Wan
2008	—	`conf`	Efficiently Testing Sparse GF(2) Polynomials. ICALP (1) Ilias Diakonikolas, Homin K. Lee, Kevin Matulef, Rocco A. Servedio, Andrew Wan
2008	J	`jnl`	Small Approximate Pareto Sets for Bi-objective Shortest Paths and Other Problems CoRR Ilias Diakonikolas, Mihalis Yannakakis
2008	A*	`conf`	Succinct approximate convex pareto curves. SODA Ilias Diakonikolas, Mihalis Yannakakis
2007	—	`conf`	Small Approximate Pareto Sets for Bi-objective Shortest Paths and Other Problems. APPROX-RANDOM Ilias Diakonikolas, Mihalis Yannakakis
2007	A*	`conf`	Testing for Concise Representations. FOCS Ilias Diakonikolas, Homin K. Lee, Kevin Matulef, Krzysztof Onak, Ronitt Rubinfeld, Rocco A. Servedio, Andrew Wan
2007	J	`jnl`	Testing for Concise Representations. Electron. Colloquium Comput. Complex. Ilias Diakonikolas, Homin K. Lee, Kevin Matulef, Krzysztof Onak, Ronitt Rubinfeld, Rocco A. Servedio, Andrew Wan