ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1610.09300
  4. Cited By
Globally Optimal Training of Generalized Polynomial Neural Networks with
  Nonlinear Spectral Methods

Globally Optimal Training of Generalized Polynomial Neural Networks with Nonlinear Spectral Methods

28 October 2016
A. Gautier
Quynh N. Nguyen
Matthias Hein
ArXiv (abs)PDFHTML

Papers citing "Globally Optimal Training of Generalized Polynomial Neural Networks with Nonlinear Spectral Methods"

16 / 16 papers shown
Title
The Mechanism of Prediction Head in Non-contrastive Self-supervised
  Learning
The Mechanism of Prediction Head in Non-contrastive Self-supervised Learning
Zixin Wen
Yuanzhi Li
SSL
116
35
0
12 May 2022
On Polynomial Approximations for Privacy-Preserving and Verifiable ReLU
  Networks
On Polynomial Approximations for Privacy-Preserving and Verifiable ReLU Networks
Ramy E. Ali
Jinhyun So
A. Avestimehr
57
36
0
11 Nov 2020
When Can Neural Networks Learn Connected Decision Regions?
When Can Neural Networks Learn Connected Decision Regions?
Trung Le
Dinh Q. Phung
MLT
57
1
0
25 Jan 2019
On Connected Sublevel Sets in Deep Learning
On Connected Sublevel Sets in Deep Learning
Quynh N. Nguyen
132
102
0
22 Jan 2019
On the Benefit of Width for Neural Networks: Disappearance of Bad Basins
On the Benefit of Width for Neural Networks: Disappearance of Bad Basins
Dawei Li
Tian Ding
Ruoyu Sun
128
38
0
28 Dec 2018
Outsourcing Private Machine Learning via Lightweight Secure Arithmetic
  Computation
Outsourcing Private Machine Learning via Lightweight Secure Arithmetic Computation
S. Garg
Zahra Ghodsi
Carmit Hazay
Yuval Ishai
Antonio Marcedone
Muthuramakrishnan Venkitasubramaniam
FedML
82
2
0
04 Dec 2018
Faster CryptoNets: Leveraging Sparsity for Real-World Encrypted
  Inference
Faster CryptoNets: Leveraging Sparsity for Real-World Encrypted Inference
Edward Chou
Josh Beal
Daniel Levy
Serena Yeung
Albert Haque
Li Fei-Fei
65
199
0
25 Nov 2018
A Fully Private Pipeline for Deep Learning on Electronic Health Records
A Fully Private Pipeline for Deep Learning on Electronic Health Records
Edward Chou
Thao Nguyen
Josh Beal
Albert Haque
Li Fei-Fei
SyDaFedML
23
6
0
25 Nov 2018
On the loss landscape of a class of deep neural networks with no bad
  local valleys
On the loss landscape of a class of deep neural networks with no bad local valleys
Quynh N. Nguyen
Mahesh Chandra Mukkamala
Matthias Hein
97
87
0
27 Sep 2018
Adding One Neuron Can Eliminate All Bad Local Minima
Adding One Neuron Can Eliminate All Bad Local Minima
Shiyu Liang
Ruoyu Sun
Jason D. Lee
R. Srikant
100
90
0
22 May 2018
Understanding the Loss Surface of Neural Networks for Binary
  Classification
Understanding the Loss Surface of Neural Networks for Binary Classification
Shiyu Liang
Ruoyu Sun
Yixuan Li
R. Srikant
95
88
0
19 Feb 2018
Optimization Landscape and Expressivity of Deep CNNs
Optimization Landscape and Expressivity of Deep CNNs
Quynh N. Nguyen
Matthias Hein
101
29
0
30 Oct 2017
When is a Convolutional Filter Easy To Learn?
When is a Convolutional Filter Easy To Learn?
S. Du
Jason D. Lee
Yuandong Tian
MLT
62
130
0
18 Sep 2017
SafetyNets: Verifiable Execution of Deep Neural Networks on an Untrusted
  Cloud
SafetyNets: Verifiable Execution of Deep Neural Networks on an Untrusted Cloud
Zahra Ghodsi
Tianyu Gu
S. Garg
98
161
0
30 Jun 2017
Multi-output Polynomial Networks and Factorization Machines
Multi-output Polynomial Networks and Factorization Machines
Mathieu Blondel
Vlad Niculae
Takuma Otsuka
N. Ueda
70
13
0
22 May 2017
The loss surface of deep and wide neural networks
The loss surface of deep and wide neural networks
Quynh N. Nguyen
Matthias Hein
ODL
188
285
0
26 Apr 2017
1