Search Results - Daniely, Amit

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  1. 1
    Tight products and graph expansion

    Tight products and graph expansion by Daniely, Amit, Linial, Nathan

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  2. 2
    A Vacuum Ultraviolet Photoionization Mass Spectrometry and Density Functional Calculation Study of Formic Acid–Water Clusters

    A Vacuum Ultraviolet Photoionization Mass Spectrometry and Density Functional Calculation Study of Formic Acid–Water Clusters by Daniely, Amit, Wannenmacher, Anna, Levy, Nevo, Sheffer, Omri, Joseph, Edwin, Kostko, Oleg, Ahmed, Musahid, Stein, Tamar

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  3. 3
    Inapproximability of Truthful Mechanisms via Generalizations of the Vapnik--Chervonenkis Dimension

    Inapproximability of Truthful Mechanisms via Generalizations of the Vapnik--Chervonenkis Dimension by Daniely, Amit, Schapira, Michael, Shahaf, Gal

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  4. 4
    On the Sample Complexity of Two-Layer Networks: Lipschitz vs. Element-Wise Lipschitz Activation

    On the Sample Complexity of Two-Layer Networks: Lipschitz vs. Element-Wise Lipschitz Activation by Daniely, Amit, Granot, Elad

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  5. 5
    Memorizing Gaussians with no over-parameterizaion via gradient decent on neural networks

    Memorizing Gaussians with no over-parameterizaion via gradient decent on neural networks by Daniely, Amit

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  6. 6
    An Exact Poly-Time Membership-Queries Algorithm for Extraction a three-Layer ReLU Network

    An Exact Poly-Time Membership-Queries Algorithm for Extraction a three-Layer ReLU Network by Daniely, Amit, Granot, Elad

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  7. 7
    Neural Networks Learning and Memorization with (almost) no Over-Parameterization

    Neural Networks Learning and Memorization with (almost) no Over-Parameterization by Daniely, Amit

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  8. 8
    Approximate Description Length, Covering Numbers, and VC Dimension

    Approximate Description Length, Covering Numbers, and VC Dimension by Daniely, Amit, Katzhendler, Gal

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  9. 9
    From Local Pseudorandom Generators to Hardness of Learning

    From Local Pseudorandom Generators to Hardness of Learning by Daniely, Amit, Vardi, Gal

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  10. 10
    Most ReLU Networks Suffer from \(\ell^2\) Adversarial Perturbations

    Most ReLU Networks Suffer from \(\ell^2\) Adversarial Perturbations by Daniely, Amit, Schacham, Hadas

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  11. 11
    Hardness of Learning Neural Networks with Natural Weights

    Hardness of Learning Neural Networks with Natural Weights by Daniely, Amit, Vardi, Gal

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  12. 12
    SGD Learns the Conjugate Kernel Class of the Network

    SGD Learns the Conjugate Kernel Class of the Network by Daniely, Amit

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  13. 13
    Most Neural Networks Are Almost Learnable

    Most Neural Networks Are Almost Learnable by Daniely, Amit, Srebro, Nathan, Vardi, Gal

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  14. 14
    Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy

    Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy by Daniely, Amit, Srebro, Nathan, Vardi, Gal

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  15. 15
    Learning Parities with Neural Networks

    Learning Parities with Neural Networks by Daniely, Amit, Malach, Eran

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  16. 16
    Depth Separation for Neural Networks

    Depth Separation for Neural Networks by Daniely, Amit

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  17. 17
    Locally Private Learning without Interaction Requires Separation

    Locally Private Learning without Interaction Requires Separation by Daniely, Amit, Feldman, Vitaly

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  18. 18
    Generalization Bounds for Neural Networks via Approximate Description Length

    Generalization Bounds for Neural Networks via Approximate Description Length by Daniely, Amit, Granot, Elad

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  19. 19
    Complexity Theoretic Limitations on Learning Halfspaces

    Complexity Theoretic Limitations on Learning Halfspaces by Daniely, Amit

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  20. 20
    Competitive ratio versus regret minimization: achieving the best of both worlds

    Competitive ratio versus regret minimization: achieving the best of both worlds by Daniely, Amit, Mansour, Yishay

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