Learning Two Layer Rectified Neural Networks in Polynomial Time

5 November 2018

Papers citing "Learning Two Layer Rectified Neural Networks in Polynomial Time"

47 / 47 papers shown

Title
Learning Neural Networks with Distribution Shift: Efficiently Certifiable Guarantees Gautam Chandrasekaran Adam R. Klivans Lin Lin Lee Konstantinos Stavropoulos OOD 73 1 0 22 Feb 2025
On the Hardness of Learning One Hidden Layer Neural Networks Shuchen Li Ilias Zadik Manolis Zampetakis 48 2 0 04 Oct 2024
Linear Bellman Completeness Suffices for Efficient Online Reinforcement Learning with Few Actions Noah Golowich Ankur Moitra OffRL 68 1 0 17 Jun 2024
Hardness of Learning Neural Networks under the Manifold Hypothesis B. Kiani Jason Wang Melanie Weber 77 4 0 03 Jun 2024
SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning Shuai Zhang Heshan Devaka Fernando Miao Liu K. Murugesan Songtao Lu Pin-Yu Chen Tianyi Chen Meng Wang 70 2 0 24 May 2024
Convex Relaxations of ReLU Neural Networks Approximate Global Optima in Polynomial Time Sungyoon Kim Mert Pilanci 191 4 0 06 Feb 2024
Agnostically Learning Multi-index Models with Queries Ilias Diakonikolas Daniel M. Kane Vasilis Kontonis Christos Tzamos Nikos Zarifis 63 4 0 27 Dec 2023
Polynomial-Time Solutions for ReLU Network Training: A Complexity Classification via Max-Cut and Zonotopes Yifei Wang Mert Pilanci 74 3 0 18 Nov 2023
On the Convergence and Sample Complexity Analysis of Deep Q-Networks with $ε$ -Greedy Exploration Shuai Zhang Hongkang Li Meng Wang Miao Liu Pin-Yu Chen Songtao Lu Sijia Liu K. Murugesan Subhajit Chaudhury 111 21 0 24 Oct 2023
Efficiently Learning One-Hidden-Layer ReLU Networks via Schur Polynomials Ilias Diakonikolas D. Kane 71 5 0 24 Jul 2023
A faster and simpler algorithm for learning shallow networks Sitan Chen Shyam Narayanan 75 8 0 24 Jul 2023
Most Neural Networks Are Almost Learnable Amit Daniely Nathan Srebro Gal Vardi 57 0 0 25 May 2023
$Toward $L_\infty$-recovery of Nonlinear Functions: A Polynomial Sample Complexity Bound for Gaussian Random Fields$ Toward $L_\infty$ -recovery of Nonlinear Functions: A Polynomial Sample Complexity Bound for Gaussian Random Fields Kefan Dong Tengyu Ma 88 4 0 29 Apr 2023
Learning Narrow One-Hidden-Layer ReLU Networks Sitan Chen Zehao Dou Surbhi Goel Adam R. Klivans Raghu Meka MLT 74 15 0 20 Apr 2023
Training a Two Layer ReLU Network Analytically Adrian Barbu 137 6 0 06 Apr 2023
Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy Amit Daniely Nathan Srebro Gal Vardi 96 5 0 15 Feb 2023
Bounding the Width of Neural Networks via Coupled Initialization -- A Worst Case Analysis Alexander Munteanu Simon Omlor Zhao Song David P. Woodruff 97 15 0 26 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 125 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 68 31 0 10 Feb 2022
How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis Shuai Zhang Ming Wang Sijia Liu Pin-Yu Chen Jinjun Xiong SSL MLT 109 23 0 21 Jan 2022
Efficiently Learning Any One Hidden Layer ReLU Network From Queries Sitan Chen Adam R. Klivans Raghu Meka MLAU MLT 103 8 0 08 Nov 2021
An Empirical Study on Compressed Decentralized Stochastic Gradient Algorithms with Overparameterized Models A. Rao Hoi-To Wai 26 0 0 09 Oct 2021
Efficient Algorithms for Learning Depth-2 Neural Networks with General ReLU Activations Pranjal Awasthi Alex K. Tang Aravindan Vijayaraghavan MLT 59 21 0 21 Jul 2021
Near-Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time Nadiia Chepurko K. Clarkson Praneeth Kacham David P. Woodruff 48 10 0 16 Jul 2021
Neural Optimization Kernel: Towards Robust Deep Learning Yueming Lyu Ivor Tsang 53 1 0 11 Jun 2021
The Computational Complexity of ReLU Network Training Parameterized by Data Dimensionality Vincent Froese Christoph Hertrich R. Niedermeier 67 24 0 18 May 2021
$Training Neural Networks is $\exists\mathbb R$-complete$ Training Neural Networks is $\exists\mathbb R$ -complete Mikkel Abrahamsen Linda Kleist Tillmann Miltzow 21 1 0 19 Feb 2021
From Local Pseudorandom Generators to Hardness of Learning Amit Daniely Gal Vardi 129 32 0 20 Jan 2021
Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning Zeyuan Allen-Zhu Yuanzhi Li FedML 187 376 0 17 Dec 2020
Small Covers for Near-Zero Sets of Polynomials and Learning Latent Variable Models Ilias Diakonikolas D. Kane 81 33 0 14 Dec 2020
Tight Hardness Results for Training Depth-2 ReLU Networks Surbhi Goel Adam R. Klivans Pasin Manurangsi Daniel Reichman 78 41 0 27 Nov 2020
Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra Nadiia Chepurko K. Clarkson L. Horesh Honghao Lin David P. Woodruff 60 24 0 09 Nov 2020
MixCon: Adjusting the Separability of Data Representations for Harder Data Recovery Xiaoxiao Li Yangsibo Huang Binghui Peng Zhao Song Keqin Li MIACV 69 1 0 22 Oct 2020
Learning Deep ReLU Networks Is Fixed-Parameter Tractable Sitan Chen Adam R. Klivans Raghu Meka 87 38 0 28 Sep 2020
Generalized Leverage Score Sampling for Neural Networks Jason D. Lee Ruoqi Shen Zhao Song Mengdi Wang Zheng Yu 66 43 0 21 Sep 2020
Learning Over-Parametrized Two-Layer ReLU Neural Networks beyond NTK Yuanzhi Li Tengyu Ma Hongyang R. Zhang MLT 95 27 0 09 Jul 2020
Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks Ilias Diakonikolas D. Kane Vasilis Kontonis Nikos Zarifis 76 66 0 22 Jun 2020
Training (Overparametrized) Neural Networks in Near-Linear Time Jan van den Brand Binghui Peng Zhao Song Omri Weinstein ODL 91 83 0 20 Jun 2020
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 122 151 0 20 May 2020
Learning Polynomials of Few Relevant Dimensions Sitan Chen Raghu Meka 70 40 0 28 Apr 2020
A Deep Conditioning Treatment of Neural Networks Naman Agarwal Pranjal Awasthi Satyen Kale AI4CE 115 16 0 04 Feb 2020
Convex Formulation of Overparameterized Deep Neural Networks Cong Fang Yihong Gu Weizhong Zhang Tong Zhang 80 28 0 18 Nov 2019
Quadratic Suffices for Over-parametrization via Matrix Chernoff Bound Zhao Song Xin Yang 75 91 0 09 Jun 2019
What Can ResNet Learn Efficiently, Going Beyond Kernels? Zeyuan Allen-Zhu Yuanzhi Li 416 183 0 24 May 2019
Analysis of a Two-Layer Neural Network via Displacement Convexity Adel Javanmard Marco Mondelli Andrea Montanari MLT 119 57 0 05 Jan 2019
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers Zeyuan Allen-Zhu Yuanzhi Li Yingyu Liang MLT 235 775 0 12 Nov 2018
Principled Deep Neural Network Training through Linear Programming D. Bienstock Gonzalo Muñoz Sebastian Pokutta 89 25 0 07 Oct 2018