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We study the power of query access for the task of agnostic learning under the Gaussian distribution.
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Agnostically learning halfspaces
A. Kalai, A. Klivans, Y. Mansour, and R. Servedio · 2005
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On the power of membership queries in agnostic learning
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Agnostically learning decision trees
P. Gopalan, A. Kalai, and A. Klivans · 2008
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A query algorithm for agnostically learning dnf?
P. Gopalan, A. Kalai, and A. R. Klivans · 2008
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Learning geometric concepts via Gaussian surface area
A. Klivans, R. O’Donnell, and R. Servedio · 2008
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A. T. Kalai and R. Sastry · 2009
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Bounding the average sensitivity and noise sensitivity of polynomial threshold functions
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Bounded independence fools degree- 2 2 threshold functions
I. Diakonikolas, D. M. Kane, and J. Nelson · 2010
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Model reconstruction from model explanations
S. Milli, L. Schmidt, A. D. Dragan, and M. Hardt · 2019
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Learning polynomials in few relevant dimensions
S. Chen and R. Meka · 2020
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Small covers for near-zero sets of polynomials and learning latent variable models
I. Diakonikolas and D. M Kane · 2020
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Algorithms and SQ lower bounds for pac learning one-hidden-layer ReLU networks
I. Diakonikolas, D. M. Kane, V. Kontonis, and N. Zarifis · 2020
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Near-optimal SQ lower bounds for agnostically learning halfspaces and ReLUs under Gaussian marginals
I. Diakonikolas, D. M. Kane, and N. Zarifis · 2020
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Statistical-query lower bounds via functional gradients
S. Goel, A. Gollakota, and A. R. Klivans · 2020
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A regularity lemma, and low-weight approximators, for low-degree polynomial threshold functions
I. Diakonikolas, R. Servedio, L.-Y. Tan, and A. Wan · 2010
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Graph expansion and the unique games conjecture
P. Raghavendra and D. Steurer · 2010
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A random-sampling-based algorithm for learning intersections of halfspaces
S. Vempala · 2010
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Learning gradients: predictive models that infer geometry and statistical dependence
Q. Wu, J. Guinney, M. Maggioni, and S. Mukherjee · 2010
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The gaussian surface area and noise sensitivity of degree- d polynomial threshold functions
D. M. Kane · 2011
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Efficient learning of generalized linear and single index models with isotonic regression
S. M Kakade, V. Kanade, O. Shamir, and A. Kalai · 2011
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High accuracy and high fidelity extraction of neural networks
M. Jagielski, N. Carlini, D. Berthelot, A. Kurakin, and N. Papernot · 2020
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Span recovery for deep neural networks with applications to input obfuscation
R. Jayaram, D.P. Woodruff, and Q. Zhang · 2020
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Reverse-engineering deep ReLU networks
D. Rolnick and K. P. Kording · 2020
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Efficiently learning one hidden layer relu networks from queries
S. Chen, A. R. Klivans, and R. Meka · 2021
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Agnostic proper learning of halfspaces under gaussian marginals
I. Diakonikolas, D. M. Kane, V. Kontonis, C. Tzamos, and N. Zarifis · 2021
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The optimality of polynomial regression for agnostic learning under gaussian marginals in the sq model
I. Diakonikolas, D. M. Kane, T. Pittas, and N. Zarifis · 2021
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Robust testing of low dimensional functions
A. De, E. Mossel, and J. Neeman · 2021
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Learning single-index models with shallow neural networks
A. Bietti, J. Bruna, C. Sanford, and M. J. Song · 2022
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Properly learning decision trees in almost polynomial time
G. Blanc, J. Lange, M. Qiao, and L.-Y. Tan · 2022
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Learning deep relu networks is fixed-parameter tractable
S. Chen, A. R. Klivans, and R. Meka · 2022
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An exact poly-time membership-queries algorithm for extracting a three-layer relu network
A. Daniely and E. Granot · 2022
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Hardness of learning a single neuron with adversarial label noise
I. Diakonikolas, D. Kane, P. Manurangsi, and L. Ren · 2022
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Cryptographic hardness of learning halfspaces with massart noise
I. Diakonikolas, D. M. Kane, P. Manurangsi, and L. Ren · 2022
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Neural networks can learn representations with gradient descent
A. Damian, J. Lee, and M. Soltanolkotabi · 2022
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Near-optimal statistical query lower bounds for agnostically learning intersections of halfspaces with gaussian marginals
D. J. Hsu, C. Sanford, R. A. Servedio, and E. Vlatakis-Gkaragkounis · 2022
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Learning narrow one-hidden-layer relu networks
S. Chen, Z. Dou, S. Goel, A. R. Klivans, and R. Meka · 2023
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A faster and simpler algorithm for learning shallow networks
S. Chen and S. Narayanan · 2023
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Efficiently learning one-hidden-layer relu networks via schur polynomials
I. Diakonikolas and D. M. Kane · 2023
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Near-optimal cryptographic hardness of agnostically learning halfspaces and relu regression under gaussian marginals
I. Diakonikolas, D. M. Kane, and L. Ren · 2023
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Agnostically learning single-index models using omnipredictors
A. Gollakota, P. Gopalan, A. R. Klivans, and K. Stavropoulos · 2023
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Hardness of agnostically learning halfspaces from worst-case lattice problems
S. Tiegel · 2023
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