Reliably Learning the ReLU in Polynomial Time

30 November 2016

Papers citing "Reliably Learning the ReLU in Polynomial Time"

34 / 34 papers shown

Title
Importance Sampling for Nonlinear Models Prakash Palanivelu Rajmohan Fred Roosta 7 0 0 18 May 2025
Efficiently Learning One-Hidden-Layer ReLU Networks via Schur Polynomials Ilias Diakonikolas D. Kane 32 4 0 24 Jul 2023
A faster and simpler algorithm for learning shallow networks Sitan Chen Shyam Narayanan 41 7 0 24 Jul 2023
Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy Amit Daniely Nathan Srebro Gal Vardi 33 4 0 15 Feb 2023
Near-Optimal Cryptographic Hardness of Agnostically Learning Halfspaces and ReLU Regression under Gaussian Marginals Ilias Diakonikolas D. Kane Lisheng Ren 19 26 0 13 Feb 2023
Transformers Learn Shortcuts to Automata Bingbin Liu Jordan T. Ash Surbhi Goel A. Krishnamurthy Cyril Zhang OffRL LRM 48 156 0 19 Oct 2022
Loss Minimization through the Lens of Outcome Indistinguishability Parikshit Gopalan Lunjia Hu Michael P. Kim Omer Reingold Udi Wieder UQCV 38 31 0 16 Oct 2022
Neural Networks can Learn Representations with Gradient Descent Alexandru Damian Jason D. Lee Mahdi Soltanolkotabi SSL MLT 25 114 0 30 Jun 2022
$Training Fully Connected Neural Networks is $\exists\mathbb{R}$-Complete$ Training Fully Connected Neural Networks is $\exists\mathbb{R}$ -Complete Daniel Bertschinger Christoph Hertrich Paul Jungeblut Tillmann Miltzow Simon Weber OffRL 61 30 0 04 Apr 2022
Hardness of Noise-Free Learning for Two-Hidden-Layer Neural Networks Sitan Chen Aravind Gollakota Adam R. Klivans Raghu Meka 27 30 0 10 Feb 2022
Neural networks with linear threshold activations: structure and algorithms Sammy Khalife Hongyu Cheng A. Basu 42 14 0 15 Nov 2021
Exponentially Many Local Minima in Quantum Neural Networks Xuchen You Xiaodi Wu 72 52 0 06 Oct 2021
ReLU Regression with Massart Noise Ilias Diakonikolas Jongho Park Christos Tzamos 56 11 0 10 Sep 2021
Small Covers for Near-Zero Sets of Polynomials and Learning Latent Variable Models Ilias Diakonikolas D. Kane 21 32 0 14 Dec 2020
Learning Graph Neural Networks with Approximate Gradient Descent Qunwei Li Shaofeng Zou Leon Wenliang Zhong GNN 32 1 0 07 Dec 2020
Learning Deep ReLU Networks Is Fixed-Parameter Tractable Sitan Chen Adam R. Klivans Raghu Meka 22 36 0 28 Sep 2020
From Boltzmann Machines to Neural Networks and Back Again Surbhi Goel Adam R. Klivans Frederic Koehler 19 5 0 25 Jul 2020
Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs under Gaussian Marginals Ilias Diakonikolas D. Kane Nikos Zarifis 21 66 0 29 Jun 2020
Approximation Schemes for ReLU Regression Ilias Diakonikolas Surbhi Goel Sushrut Karmalkar Adam R. Klivans Mahdi Soltanolkotabi 18 51 0 26 May 2020
Neural Networks are Convex Regularizers: Exact Polynomial-time Convex Optimization Formulations for Two-layer Networks Mert Pilanci Tolga Ergen 26 116 0 24 Feb 2020
Convex Relaxations of Convolutional Neural Nets Burak Bartan Mert Pilanci 20 5 0 31 Dec 2018
Deep Frank-Wolfe For Neural Network Optimization Leonard Berrada Andrew Zisserman M. P. Kumar ODL 21 40 0 19 Nov 2018
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 32 765 0 12 Nov 2018
Learning Two-layer Neural Networks with Symmetric Inputs Rong Ge Rohith Kuditipudi Zhize Li Xiang Wang OOD MLT 36 57 0 16 Oct 2018
Learning One-hidden-layer ReLU Networks via Gradient Descent Xiao Zhang Yaodong Yu Lingxiao Wang Quanquan Gu MLT 30 134 0 20 Jun 2018
How Many Samples are Needed to Estimate a Convolutional or Recurrent Neural Network? S. Du Yining Wang Xiyu Zhai Sivaraman Balakrishnan Ruslan Salakhutdinov Aarti Singh SSL 21 57 0 21 May 2018
Improved Learning of One-hidden-layer Convolutional Neural Networks with Overlaps S. Du Surbhi Goel MLT 30 17 0 20 May 2018
Gradient Descent for One-Hidden-Layer Neural Networks: Polynomial Convergence and SQ Lower Bounds Santosh Vempala John Wilmes MLT 13 50 0 07 May 2018
Learning One Convolutional Layer with Overlapping Patches Surbhi Goel Adam R. Klivans Raghu Meka MLT 21 80 0 07 Feb 2018
Theoretical insights into the optimization landscape of over-parameterized shallow neural networks Mahdi Soltanolkotabi Adel Javanmard J. Lee 36 415 0 16 Jul 2017
Recovery Guarantees for One-hidden-layer Neural Networks Kai Zhong Zhao Song Prateek Jain Peter L. Bartlett Inderjit S. Dhillon MLT 34 336 0 10 Jun 2017
Learning ReLUs via Gradient Descent Mahdi Soltanolkotabi MLT 26 181 0 10 May 2017
Convergence Results for Neural Networks via Electrodynamics Rina Panigrahy Sushant Sachdeva Qiuyi Zhang MLT MDE 29 22 0 01 Feb 2017
Understanding Deep Neural Networks with Rectified Linear Units R. Arora A. Basu Poorya Mianjy Anirbit Mukherjee PINN 41 634 0 04 Nov 2016