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2007.07213
Cited By

Plateau Phenomenon in Gradient Descent Training of ReLU networks:
Explanation, Quantification and Avoidance

Plateau Phenomenon in Gradient Descent Training of ReLU networks: Explanation, Quantification and Avoidance

SIAM Journal on Scientific Computing (SIAM J. Sci. Comput.), 2020

14 July 2020

ArXiv (abs)PDF HTML

Papers citing "Plateau Phenomenon in Gradient Descent Training of ReLU networks: Explanation, Quantification and Avoidance"

5 / 5 papers shown

Is the Frequency Principle always valid?

Is the Frequency Principle always valid?

92

0

0

24 Aug 2025

Multi-Band Variable-Lag Granger Causality: A Unified Framework for Causal Time Series Inference across Frequencies

Multi-Band Variable-Lag Granger Causality: A Unified Framework for Causal Time Series Inference across Frequencies

Chakattrai Sookkongwaree

Tattep Lakmuang

Chainarong Amornbunchornvej

101

0

0

01 Aug 2025

Parallel Trust-Region Approaches in Neural Network Training: Beyond
Traditional Methods

Parallel Trust-Region Approaches in Neural Network Training: Beyond Traditional Methods

Samuel A. Cruz Alegría

Alena Kopanicáková

210

2

0

21 Dec 2023

On the Omnipresence of Spurious Local Minima in Certain Neural Network
Training Problems

On the Omnipresence of Spurious Local Minima in Certain Neural Network Training ProblemsConstructive approximation (Constr. Approx.), 2022

Julia Kowalczyk

303

9

0

23 Feb 2022

Deep Kronecker neural networks: A general framework for neural networks
with adaptive activation functions

Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions

Ameya Dilip Jagtap

Kenji Kawaguchi

George Karniadakis

264

157

0

20 May 2021