conftrace_

weight initialization

50 papers

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Co-occurring keywords

neural network optimization (1293) neural network (6616) model compression (3302) deep neural network (1803) neural network training (309) activation function (133) transfer learning (5449) model initialization (32) convolutional neural network (4226) signal propagation (20)

Papers

Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not? ICML 2021
Learning where to learn: Gradient sparsity in meta and continual learning NIPS 2021
Fast Certified Robust Training with Short Warmup NIPS 2021
Learning with Retrospection AAAI 2021
Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? NIPS 2021
Improving Transformer Optimization Through Better Initialization ICML 2020
What's Hidden in a Randomly Weighted Neural Network? CVPR 2020
Cooperative Initialization based Deep Neural Network Training WACV 2020
Beyond Signal Propagation: Is Feature Diversity Necessary in Deep Neural Network Initialization? ICML 2020
Train-by-Reconnect: Decoupling Locations of Weights from Their Values NIPS 2020
On the Impact of the Activation function on Deep Neural Networks Training ICML 2019
Unsupervised Pretraining for Neural Machine Translation Using Elastic Weight Consolidation ACL 2019
Initialization of ReLUs for Dynamical Isometry NIPS 2019
Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask NIPS 2019
MetaInit: Initializing learning by learning to initialize NIPS 2019
Learning Steerable Filters for Rotation Equivariant CNNs CVPR 2018
Multi-Task Learning of Speech Recognition and Speech Synthesis Parameters for Ultrasound-based Silent Speech Interfaces INTERSPEECH 2018
Invariance of Weight Distributions in Rectified MLPs ICML 2018
How to Start Training: The Effect of Initialization and Architecture NIPS 2018
Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice NIPS 2017
Initializing Convolutional Filters with Semantic Features for Text Classification EMNLP 2017
Bank of Weight Filters for Deep CNNs ACML 2016
Pre-training of Recurrent Neural Networks via Linear Autoencoders NIPS 2014
Learning by Stretching Deep Networks ICML 2014
Understanding the difficulty of training deep feedforward neural networks AISTATS 2010