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Neural Network Optimization

3648 directly classified papers

Papers per year

Papers

ClcNet: Improving the Efficiency of Convolutional Neural Network Using Channel Local Convolutions CVPR 2018
Image Correction via Deep Reciprocating HDR Transformation CVPR 2018
Improving Neural Language Models with Weight Norm Initialization and Regularization EMNLP 2018
Chinese NER Using Lattice LSTM ACL 2018
LSTMs Exploit Linguistic Attributes of Data ACL 2018
Adafactor: Adaptive Learning Rates with Sublinear Memory Cost ICML 2018
Training DNNs with Hybrid Block Floating Point NIPS 2018
Automatic DNN Node Pruning Using Mixture Distribution-based Group Regularization INTERSPEECH 2018
Stochastic Shake-Shake Regularization for Affective Learning from Speech INTERSPEECH 2018
Combining Natural Gradient with Hessian Free Methods for Sequence Training INTERSPEECH 2018
Training Recurrent Neural Network through Moment Matching for NLP Applications INTERSPEECH 2018
DNN Driven Speaker Independent Audio-Visual Mask Estimation for Speech Separation INTERSPEECH 2018
Interpretable Textual Neuron Representations for NLP EMNLP 2018
Towards Two-Dimensional Sequence to Sequence Model in Neural Machine Translation EMNLP 2018
Independently Recurrent Neural Network (IndRNN): Building a Longer and Deeper RNN CVPR 2018
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices CVPR 2018
Optimizing Filter Size in Convolutional Neural Networks for Facial Action Unit Recognition CVPR 2018
Long Short-Term Memory as a Dynamically Computed Element-wise Weighted Sum ACL 2018
Robust and Scalable Differentiable Neural Computer for Question Answering ACL 2018
Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis NIPS 2018
A Bridging Framework for Model Optimization and Deep Propagation NIPS 2018
Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search NIPS 2018
Implicit Bias of Gradient Descent on Linear Convolutional Networks NIPS 2018
Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced NIPS 2018
Step Size Matters in Deep Learning NIPS 2018