Theoretical Issues in Deep Networks: Approximation, Optimization and Generalization

25 August 2019

Papers citing "Theoretical Issues in Deep Networks: Approximation, Optimization and Generalization"

22 / 72 papers shown

Title
Post-Selections in AI and How to Avoid Them J. Weng 19 0 0 19 Jun 2021
Locality defeats the curse of dimensionality in convolutional teacher-student scenarios Alessandro Favero Francesco Cagnetta M. Wyart 32 31 0 16 Jun 2021
Tabular Data: Deep Learning is Not All You Need Ravid Shwartz-Ziv Amitai Armon LMTD 13 1,208 0 06 Jun 2021
Deep physical neural networks enabled by a backpropagation algorithm for arbitrary physical systems Logan G. Wright Tatsuhiro Onodera Martin M. Stein Tianyu Wang Darren T. Schachter Zoey Hu Peter L. McMahon PINN AI4CE 49 469 0 27 Apr 2021
Measuring and modeling the motor system with machine learning Sébastien B Hausmann Alessandro Marin Vargas Alexander Mathis Mackenzie W. Mathis 44 50 0 22 Mar 2021
An Analytic Layer-wise Deep Learning Framework with Applications to Robotics Huu-Thiet Nguyen C. Cheah Kar-Ann Toh 18 16 0 07 Feb 2021
Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training Cong Fang Hangfeng He Qi Long Weijie J. Su FAtt 132 168 0 29 Jan 2021
Unsupervised Imputation of Non-ignorably Missing Data Using Importance-Weighted Autoencoders David K. Lim N. Rashid Junier B. Oliva J. Ibrahim 26 3 0 18 Jan 2021
Data-Driven Random Access Optimization in Multi-Cell IoT Networks with NOMA Sami Khairy Prasanna Balaprakash L. Cai H. Vincent Poor 35 6 0 02 Jan 2021
Cutting-edge 3D Medical Image Segmentation Methods in 2020: Are Happy Families All Alike? Jun Ma 66 25 0 01 Jan 2021
Explicit regularization and implicit bias in deep network classifiers trained with the square loss T. Poggio Q. Liao 19 41 0 31 Dec 2020
Robustness, Privacy, and Generalization of Adversarial Training Fengxiang He Shaopeng Fu Bohan Wang Dacheng Tao 33 10 0 25 Dec 2020
Towards Coinductive Models for Natural Language Understanding. Bringing together Deep Learning and Deep Semantics Wlodek Zadrozny AI4CE 24 1 0 09 Dec 2020
Statistical Mechanics of Deep Linear Neural Networks: The Back-Propagating Kernel Renormalization Qianyi Li H. Sompolinsky 30 69 0 07 Dec 2020
Gradient-Based Empirical Risk Minimization using Local Polynomial Regression Ali Jadbabaie A. Makur Devavrat Shah 33 6 0 04 Nov 2020
Deep Learning Predicts Cardiovascular Disease Risks from Lung Cancer Screening Low Dose Computed Tomography Hanqing Chao Hongming Shan F. Homayounieh Ramandeep Singh R. Khera Hengtao Guo Timothy Su Ge Wang M. Kalra Pingkun Yan 22 73 0 16 Aug 2020
Partial local entropy and anisotropy in deep weight spaces Daniele Musso 9 3 0 17 Jul 2020
Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies Yu Huang Yue Chen 3DPC 51 83 0 10 Jun 2020
A function space analysis of finite neural networks with insights from sampling theory Raja Giryes 22 6 0 15 Apr 2020
The Unreasonable Effectiveness of Deep Learning in Artificial Intelligence T. Sejnowski 7 295 0 12 Feb 2020
Bad Global Minima Exist and SGD Can Reach Them Shengchao Liu Dimitris Papailiopoulos D. Achlioptas 13 80 0 06 Jun 2019
Bridging the Gaps Between Residual Learning, Recurrent Neural Networks and Visual Cortex Q. Liao T. Poggio 213 255 0 13 Apr 2016