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Statistical-Query Lower Bounds via Functional Gradients
v1v2 (latest)

Statistical-Query Lower Bounds via Functional Gradients

29 June 2020
Surbhi Goel
Aravind Gollakota
Adam R. Klivans
ArXiv (abs)PDFHTML

Papers citing "Statistical-Query Lower Bounds via Functional Gradients"

50 / 52 papers shown
Robustly Learning Monotone Single-Index Models
Robustly Learning Monotone Single-Index Models
Puqian Wang
Nikos Zarifis
Ilias Diakonikolas
Jelena Diakonikolas
128
1
0
06 Aug 2025
Learning Neural Networks with Distribution Shift: Efficiently Certifiable Guarantees
Learning Neural Networks with Distribution Shift: Efficiently Certifiable GuaranteesInternational Conference on Learning Representations (ICLR), 2025
Gautam Chandrasekaran
Adam R. Klivans
Lin Lin Lee
Konstantinos Stavropoulos
OOD
266
2
0
22 Feb 2025
Reliable Learning of Halfspaces under Gaussian MarginalsNeural Information Processing Systems (NeurIPS), 2024
Ilias Diakonikolas
Lisheng Ren
Nikos Zarifis
305
0
0
18 Nov 2024
Model Stealing for Any Low-Rank Language Model
Model Stealing for Any Low-Rank Language ModelSymposium on the Theory of Computing (STOC), 2024
Allen Liu
Ankur Moitra
267
11
0
12 Nov 2024
Learning a Single Neuron Robustly to Distributional Shifts and
  Adversarial Label Noise
Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label NoiseNeural Information Processing Systems (NeurIPS), 2024
Shuyao Li
Sushrut Karmalkar
Ilias Diakonikolas
Jelena Diakonikolas
OOD
283
4
0
11 Nov 2024
Sample and Computationally Efficient Robust Learning of Gaussian
  Single-Index Models
Sample and Computationally Efficient Robust Learning of Gaussian Single-Index ModelsNeural Information Processing Systems (NeurIPS), 2024
Puqian Wang
Nikos Zarifis
Ilias Diakonikolas
Jelena Diakonikolas
308
2
0
08 Nov 2024
Sum-of-squares lower bounds for Non-Gaussian Component Analysis
Sum-of-squares lower bounds for Non-Gaussian Component AnalysisIEEE Annual Symposium on Foundations of Computer Science (FOCS), 2024
Ilias Diakonikolas
Sushrut Karmalkar
Shuo Pang
Aaron Potechin
188
8
0
28 Oct 2024
Efficient Testable Learning of General Halfspaces with Adversarial Label
  Noise
Efficient Testable Learning of General Halfspaces with Adversarial Label Noise
Ilias Diakonikolas
Daniel M. Kane
Sihan Liu
Nikos Zarifis
200
0
0
30 Aug 2024
Learning Neural Networks with Sparse Activations
Learning Neural Networks with Sparse Activations
Pranjal Awasthi
Nishanth Dikkala
Pritish Kamath
Raghu Meka
456
7
0
26 Jun 2024
On the Computational Landscape of Replicable Learning
On the Computational Landscape of Replicable Learning
Alkis Kalavasis
Amin Karbasi
Grigoris Velegkas
Felix Y. Zhou
276
8
0
24 May 2024
SQ Lower Bounds for Non-Gaussian Component Analysis with Weaker
  Assumptions
SQ Lower Bounds for Non-Gaussian Component Analysis with Weaker AssumptionsNeural Information Processing Systems (NeurIPS), 2024
Ilias Diakonikolas
Daniel M. Kane
Lisheng Ren
Yuxin Sun
266
16
0
07 Mar 2024
Statistical Query Lower Bounds for Learning Truncated Gaussians
Statistical Query Lower Bounds for Learning Truncated Gaussians
Ilias Diakonikolas
Daniel M. Kane
Thanasis Pittas
Nikos Zarifis
246
6
0
04 Mar 2024
Replicable Learning of Large-Margin Halfspaces
Replicable Learning of Large-Margin Halfspaces
Alkis Kalavasis
Amin Karbasi
Kasper Green Larsen
Grigoris Velegkas
Felix Y. Zhou
291
14
0
21 Feb 2024
Agnostically Learning Multi-index Models with Queries
Agnostically Learning Multi-index Models with Queries
Ilias Diakonikolas
Daniel M. Kane
Vasilis Kontonis
Christos Tzamos
Nikos Zarifis
302
9
0
27 Dec 2023
Efficient Active Learning Halfspaces with Tsybakov Noise: A Non-convex
  Optimization Approach
Efficient Active Learning Halfspaces with Tsybakov Noise: A Non-convex Optimization ApproachInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Yinan Li
Chicheng Zhang
207
1
0
23 Oct 2023
Distribution-Independent Regression for Generalized Linear Models with
  Oblivious Corruptions
Distribution-Independent Regression for Generalized Linear Models with Oblivious CorruptionsAnnual Conference Computational Learning Theory (COLT), 2023
Ilias Diakonikolas
Sushrut Karmalkar
Jongho Park
Christos Tzamos
401
2
0
20 Sep 2023
SQ Lower Bounds for Learning Bounded Covariance GMMs
SQ Lower Bounds for Learning Bounded Covariance GMMs
Ilias Diakonikolas
D. Kane
Thanasis Pittas
Nikos Zarifis
270
0
0
22 Jun 2023
Agnostically Learning Single-Index Models using Omnipredictors
Agnostically Learning Single-Index Models using OmnipredictorsNeural Information Processing Systems (NeurIPS), 2023
Aravind Gollakota
Parikshit Gopalan
Adam R. Klivans
Konstantinos Stavropoulos
183
16
0
18 Jun 2023
Robustly Learning a Single Neuron via Sharpness
Robustly Learning a Single Neuron via SharpnessInternational Conference on Machine Learning (ICML), 2023
Puqian Wang
Nikos Zarifis
Ilias Diakonikolas
Jelena Diakonikolas
214
14
0
13 Jun 2023
Statistical Indistinguishability of Learning Algorithms
Statistical Indistinguishability of Learning AlgorithmsInternational Conference on Machine Learning (ICML), 2023
Alkis Kalavasis
Amin Karbasi
Shay Moran
Grigoris Velegkas
232
20
0
23 May 2023
Tester-Learners for Halfspaces: Universal Algorithms
Tester-Learners for Halfspaces: Universal AlgorithmsNeural Information Processing Systems (NeurIPS), 2023
Aravind Gollakota
Adam R. Klivans
Konstantinos Stavropoulos
Arsen Vasilyan
273
15
0
19 May 2023
Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample
  Complexity for Learning Single Index Models
Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index ModelsNeural Information Processing Systems (NeurIPS), 2023
Alexandru Damian
Eshaan Nichani
Rong Ge
Jason D. Lee
MLT
440
56
0
18 May 2023
Efficient Testable Learning of Halfspaces with Adversarial Label Noise
Efficient Testable Learning of Halfspaces with Adversarial Label NoiseNeural Information Processing Systems (NeurIPS), 2023
Ilias Diakonikolas
D. Kane
Vasilis Kontonis
Sihan Liu
Nikos Zarifis
AAML
272
20
0
09 Mar 2023
An Efficient Tester-Learner for Halfspaces
An Efficient Tester-Learner for HalfspacesInternational Conference on Learning Representations (ICLR), 2023
Aravind Gollakota
Adam R. Klivans
Konstantinos Stavropoulos
Arsen Vasilyan
216
16
0
28 Feb 2023
Computational Complexity of Learning Neural Networks: Smoothness and
  Degeneracy
Computational Complexity of Learning Neural Networks: Smoothness and DegeneracyNeural Information Processing Systems (NeurIPS), 2023
Amit Daniely
Nathan Srebro
Gal Vardi
288
9
0
15 Feb 2023
Near-Optimal Cryptographic Hardness of Agnostically Learning Halfspaces
  and ReLU Regression under Gaussian Marginals
Near-Optimal Cryptographic Hardness of Agnostically Learning Halfspaces and ReLU Regression under Gaussian MarginalsInternational Conference on Machine Learning (ICML), 2023
Ilias Diakonikolas
D. Kane
Lisheng Ren
273
38
0
13 Feb 2023
A Moment-Matching Approach to Testable Learning and a New
  Characterization of Rademacher Complexity
A Moment-Matching Approach to Testable Learning and a New Characterization of Rademacher ComplexitySymposium on the Theory of Computing (STOC), 2022
Aravind Gollakota
Adam R. Klivans
Pravesh Kothari
CoGe
195
22
0
23 Nov 2022
Learning a Single Neuron with Adversarial Label Noise via Gradient
  Descent
Learning a Single Neuron with Adversarial Label Noise via Gradient DescentAnnual Conference Computational Learning Theory (COLT), 2022
Ilias Diakonikolas
Vasilis Kontonis
Christos Tzamos
Nikos Zarifis
MLT
223
24
0
17 Jun 2022
Learning (Very) Simple Generative Models Is Hard
Learning (Very) Simple Generative Models Is HardNeural Information Processing Systems (NeurIPS), 2022
Sitan Chen
Jungshian Li
Yuanzhi Li
214
12
0
31 May 2022
Learning ReLU networks to high uniform accuracy is intractable
Learning ReLU networks to high uniform accuracy is intractableInternational Conference on Learning Representations (ICLR), 2022
Julius Berner
Philipp Grohs
F. Voigtlaender
323
5
0
26 May 2022
Testing distributional assumptions of learning algorithms
Testing distributional assumptions of learning algorithmsSymposium on the Theory of Computing (STOC), 2022
R. Rubinfeld
Arsen Vasilyan
OOD
282
27
0
14 Apr 2022
Distributional Hardness Against Preconditioned Lasso via Erasure-Robust
  Designs
Distributional Hardness Against Preconditioned Lasso via Erasure-Robust Designs
Jonathan A. Kelner
Frederic Koehler
Raghu Meka
Dhruv Rohatgi
251
2
0
05 Mar 2022
Hardness of Noise-Free Learning for Two-Hidden-Layer Neural Networks
Hardness of Noise-Free Learning for Two-Hidden-Layer Neural NetworksNeural Information Processing Systems (NeurIPS), 2022
Sitan Chen
Aravind Gollakota
Adam R. Klivans
Raghu Meka
557
34
0
10 Feb 2022
Agnostic Learnability of Halfspaces via Logistic Loss
Agnostic Learnability of Halfspaces via Logistic LossInternational Conference on Machine Learning (ICML), 2022
Ziwei Ji
Kwangjun Ahn
Pranjal Awasthi
Satyen Kale
Stefani Karp
258
3
0
31 Jan 2022
Lattice-Based Methods Surpass Sum-of-Squares in Clustering
Lattice-Based Methods Surpass Sum-of-Squares in Clustering
Ilias Zadik
M. Song
Alexander S. Wein
Joan Bruna
425
42
0
07 Dec 2021
ReLU Regression with Massart Noise
ReLU Regression with Massart NoiseNeural Information Processing Systems (NeurIPS), 2021
Ilias Diakonikolas
Jongho Park
Christos Tzamos
290
13
0
10 Sep 2021
Efficient Algorithms for Learning from Coarse Labels
Efficient Algorithms for Learning from Coarse LabelsAnnual Conference Computational Learning Theory (COLT), 2021
Eleni Psaroudaki
Alkis Kalavasis
Vasilis Kontonis
Christos Tzamos
213
19
0
22 Aug 2021
Learning General Halfspaces with General Massart Noise under the
  Gaussian Distribution
Learning General Halfspaces with General Massart Noise under the Gaussian Distribution
Ilias Diakonikolas
D. Kane
Vasilis Kontonis
Christos Tzamos
Nikos Zarifis
233
31
0
19 Aug 2021
Learning stochastic decision trees
Learning stochastic decision treesInternational Colloquium on Automata, Languages and Programming (ICALP), 2021
Guy Blanc
Jane Lange
Li-Yang Tan
164
4
0
08 May 2021
Agnostic Proper Learning of Halfspaces under Gaussian Marginals
Agnostic Proper Learning of Halfspaces under Gaussian MarginalsAnnual Conference Computational Learning Theory (COLT), 2021
Ilias Diakonikolas
D. Kane
Vasilis Kontonis
Christos Tzamos
Nikos Zarifis
244
21
0
10 Feb 2021
The Optimality of Polynomial Regression for Agnostic Learning under
  Gaussian Marginals
The Optimality of Polynomial Regression for Agnostic Learning under Gaussian MarginalsAnnual Conference Computational Learning Theory (COLT), 2021
Ilias Diakonikolas
D. Kane
Thanasis Pittas
Nikos Zarifis
180
61
0
08 Feb 2021
From Local Pseudorandom Generators to Hardness of Learning
From Local Pseudorandom Generators to Hardness of LearningAnnual Conference Computational Learning Theory (COLT), 2021
Amit Daniely
Gal Vardi
389
39
0
20 Jan 2021
On the Power of Localized Perceptron for Label-Optimal Learning of
  Halfspaces with Adversarial Noise
On the Power of Localized Perceptron for Label-Optimal Learning of Halfspaces with Adversarial NoiseInternational Conference on Machine Learning (ICML), 2020
Jie Shen
443
15
0
19 Dec 2020
Near-Optimal Statistical Query Hardness of Learning Halfspaces with
  Massart Noise
Near-Optimal Statistical Query Hardness of Learning Halfspaces with Massart NoiseAnnual Conference Computational Learning Theory (COLT), 2020
Ilias Diakonikolas
D. Kane
425
30
0
17 Dec 2020
Achieving Adversarial Robustness Requires An Active Teacher
Achieving Adversarial Robustness Requires An Active TeacherJournal of Computational Mathematics (JCM), 2020
Chao Ma
Lexing Ying
201
1
0
14 Dec 2020
On InstaHide, Phase Retrieval, and Sparse Matrix Factorization
On InstaHide, Phase Retrieval, and Sparse Matrix FactorizationInternational Conference on Learning Representations (ICLR), 2020
Sitan Chen
Xiaoxiao Li
Zhao Song
Danyang Zhuo
315
14
0
23 Nov 2020
A Polynomial Time Algorithm for Learning Halfspaces with Tsybakov Noise
A Polynomial Time Algorithm for Learning Halfspaces with Tsybakov Noise
Ilias Diakonikolas
D. Kane
Vasilis Kontonis
Christos Tzamos
Nikos Zarifis
283
22
0
04 Oct 2020
Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins
Agnostic Learning of Halfspaces with Gradient Descent via Soft MarginsInternational Conference on Machine Learning (ICML), 2020
Spencer Frei
Yuan Cao
Quanquan Gu
288
13
0
01 Oct 2020
Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and
  ReLUs under Gaussian Marginals
Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs under Gaussian Marginals
Ilias Diakonikolas
D. Kane
Nikos Zarifis
299
74
0
29 Jun 2020
Non-Convex SGD Learns Halfspaces with Adversarial Label Noise
Non-Convex SGD Learns Halfspaces with Adversarial Label NoiseNeural Information Processing Systems (NeurIPS), 2020
Ilias Diakonikolas
Vasilis Kontonis
Christos Tzamos
Nikos Zarifis
291
34
0
11 Jun 2020
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