Recovery Guarantees for One-hidden-layer Neural Networks

10 June 2017

Inderjit S. Dhillon

Papers citing "Recovery Guarantees for One-hidden-layer Neural Networks"

50 / 223 papers shown

Title
Explicitising The Implicit Intrepretability of Deep Neural Networks Via Duality Chandrashekar Lakshminarayanan Ashutosh Kumar Singh A. Rajkumar AI4CE 26 1 0 01 Mar 2022
Self-Training: A Survey Massih-Reza Amini Vasilii Feofanov Loïc Pauletto Lies Hadjadj Emilie Devijver Yury Maximov SSL 40 102 0 24 Feb 2022
Benign Overfitting in Two-layer Convolutional Neural Networks Yuan Cao Zixiang Chen M. Belkin Quanquan Gu MLT 19 83 0 14 Feb 2022
Hardness of Noise-Free Learning for Two-Hidden-Layer Neural Networks Sitan Chen Aravind Gollakota Adam R. Klivans Raghu Meka 24 30 0 10 Feb 2022
How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis Shuai Zhang Hao Wu Sijia Liu Pin-Yu Chen Jinjun Xiong SSL MLT 41 22 0 21 Jan 2022
Low-Pass Filtering SGD for Recovering Flat Optima in the Deep Learning Optimization Landscape Devansh Bisla Jing Wang A. Choromańska 25 34 0 20 Jan 2022
On generalization bounds for deep networks based on loss surface implicit regularization Masaaki Imaizumi Johannes Schmidt-Hieber ODL 28 3 0 12 Jan 2022
Complexity from Adaptive-Symmetries Breaking: Global Minima in the Statistical Mechanics of Deep Neural Networks Shaun Li AI4CE 46 0 0 03 Jan 2022
Parameter identifiability of a deep feedforward ReLU neural network Joachim Bona-Pellissier François Bachoc François Malgouyres 41 15 0 24 Dec 2021
Risk bounds for aggregated shallow neural networks using Gaussian prior L. Tinsi A. Dalalyan BDL 20 7 0 21 Dec 2021
Efficiently Learning Any One Hidden Layer ReLU Network From Queries Sitan Chen Adam R. Klivans Raghu Meka MLAU MLT 45 8 0 08 Nov 2021
Landscape analysis of an improved power method for tensor decomposition Joe Kileel T. Klock João M. Pereira 24 10 0 29 Oct 2021
Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection Koby Bibas M. Feder Tal Hassner OODD 31 24 0 18 Oct 2021
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks Shuai Zhang Meng Wang Sijia Liu Pin-Yu Chen Jinjun Xiong UQCV MLT 31 13 0 12 Oct 2021
Exponentially Many Local Minima in Quantum Neural Networks Xuchen You Xiaodi Wu 72 51 0 06 Oct 2021
Local SGD Optimizes Overparameterized Neural Networks in Polynomial Time Yuyang Deng Mohammad Mahdi Kamani M. Mahdavi FedML 19 14 0 22 Jul 2021
Going Beyond Linear RL: Sample Efficient Neural Function Approximation Baihe Huang Kaixuan Huang Sham Kakade Jason D. Lee Qi Lei Runzhe Wang Jiaqi Yang 46 8 0 14 Jul 2021
Continual Learning in the Teacher-Student Setup: Impact of Task Similarity Sebastian Lee Sebastian Goldt Andrew M. Saxe CLL 32 73 0 09 Jul 2021
On the Cryptographic Hardness of Learning Single Periodic Neurons M. Song Ilias Zadik Joan Bruna AAML 22 27 0 20 Jun 2021
On Learnability via Gradient Method for Two-Layer ReLU Neural Networks in Teacher-Student Setting Shunta Akiyama Taiji Suzuki MLT 24 13 0 11 Jun 2021
Achieving Small Test Error in Mildly Overparameterized Neural Networks Shiyu Liang Ruoyu Sun R. Srikant 20 3 0 24 Apr 2021
Decentralized Federated Averaging Tao Sun Dongsheng Li Bao Wang FedML 54 207 0 23 Apr 2021
Spurious Local Minima Are Common for Deep Neural Networks with Piecewise Linear Activations Bo Liu 9 7 0 25 Feb 2021
A Local Convergence Theory for Mildly Over-Parameterized Two-Layer Neural Network Mo Zhou Rong Ge Chi Jin 74 45 0 04 Feb 2021
Stable Recovery of Entangled Weights: Towards Robust Identification of Deep Neural Networks from Minimal Samples Christian Fiedler M. Fornasier T. Klock Michael Rauchensteiner OOD 22 12 0 18 Jan 2021
Towards Searching Efficient and Accurate Neural Network Architectures in Binary Classification Problems Yigit Can Alparslan E. Moyer I. Isozaki Daniel Ethan Schwartz Adam Dunlop Shesh Dave Edward J. Kim MQ AI4CE 23 6 0 16 Jan 2021
Towards Understanding Learning in Neural Networks with Linear Teachers Roei Sarussi Alon Brutzkus Amir Globerson FedML MLT 57 20 0 07 Jan 2021
Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning Zeyuan Allen-Zhu Yuanzhi Li FedML 60 355 0 17 Dec 2020
Spectral Methods for Data Science: A Statistical Perspective Yuxin Chen Yuejie Chi Jianqing Fan Cong Ma 40 165 0 15 Dec 2020
Small Covers for Near-Zero Sets of Polynomials and Learning Latent Variable Models Ilias Diakonikolas D. Kane 19 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
Align, then memorise: the dynamics of learning with feedback alignment Maria Refinetti Stéphane dÁscoli Ruben Ohana Sebastian Goldt 26 36 0 24 Nov 2020
On InstaHide, Phase Retrieval, and Sparse Matrix Factorization Sitan Chen Xiaoxiao Li Zhao Song Danyang Zhuo 21 13 0 23 Nov 2020
Neural Network Training Techniques Regularize Optimization Trajectory: An Empirical Study Cheng Chen Junjie Yang Yi Zhou 13 0 0 13 Nov 2020
Algorithms and Hardness for Linear Algebra on Geometric Graphs Josh Alman T. Chu Aaron Schild Zhao Song 57 29 0 04 Nov 2020
How Does the Task Landscape Affect MAML Performance? Liam Collins Aryan Mokhtari Sanjay Shakkottai 27 3 0 27 Oct 2020
MixCon: Adjusting the Separability of Data Representations for Harder Data Recovery Xiaoxiao Li Yangsibo Huang Binghui Peng Zhao Song Keqin Li MIACV 30 1 0 22 Oct 2020
A Modular Analysis of Provable Acceleration via Polyak's Momentum: Training a Wide ReLU Network and a Deep Linear Network Jun-Kun Wang Chi-Heng Lin Jacob D. Abernethy 8 23 0 04 Oct 2020
Learning Deep ReLU Networks Is Fixed-Parameter Tractable Sitan Chen Adam R. Klivans Raghu Meka 22 36 0 28 Sep 2020
Generalized Leverage Score Sampling for Neural Networks J. Lee Ruoqi Shen Zhao Song Mengdi Wang Zheng Yu 21 42 0 21 Sep 2020
Nonparametric Learning of Two-Layer ReLU Residual Units Zhunxuan Wang Linyun He Chunchuan Lyu Shay B. Cohen MLT OffRL 33 1 0 17 Aug 2020
Learnability and Robustness of Shallow Neural Networks Learned With a Performance-Driven BP and a Variant PSO For Edge Decision-Making Hongmei He Mengyuan Chen Gang Xu Zhilong Zhu Zhenhuan Zhu 16 7 0 13 Aug 2020
From Boltzmann Machines to Neural Networks and Back Again Surbhi Goel Adam R. Klivans Frederic Koehler 19 5 0 25 Jul 2020
Learning Over-Parametrized Two-Layer ReLU Neural Networks beyond NTK Yuanzhi Li Tengyu Ma Hongyang R. Zhang MLT 20 28 0 09 Jul 2020
Understanding the Impact of Model Incoherence on Convergence of Incremental SGD with Random Reshuffle Shaocong Ma Yi Zhou 19 3 0 07 Jul 2020
The Gaussian equivalence of generative models for learning with shallow neural networks Sebastian Goldt Bruno Loureiro Galen Reeves Florent Krzakala M. Mézard Lenka Zdeborová BDL 41 100 0 25 Jun 2020
Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case Shuai Zhang Meng Wang Sijia Liu Pin-Yu Chen Jinjun Xiong MLT AI4CE 33 33 0 25 Jun 2020
Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks Ilias Diakonikolas D. Kane Vasilis Kontonis Nikos Zarifis 9 65 0 22 Jun 2020
Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent Surbhi Goel Aravind Gollakota Zhihan Jin Sushrut Karmalkar Adam R. Klivans MLT ODL 16 70 0 22 Jun 2020
Training (Overparametrized) Neural Networks in Near-Linear Time Jan van den Brand Binghui Peng Zhao Song Omri Weinstein ODL 29 82 0 20 Jun 2020