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Neural Network Optimization

903 papers

Papers per year

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9
127
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Papers

Inter-Class Angular Loss for Convolutional Neural Networks AAAI 2019
Guided Dropout AAAI 2019
Complex Unitary Recurrent Neural Networks Using Scaled Cayley Transform AAAI 2019
HyperAdam: A Learnable Task-Adaptive Adam for Network Training AAAI 2019
Learning Dynamic Generator Model by Alternating Back-Propagation through Time AAAI 2019
Balanced Sparsity for Efficient DNN Inference on GPU AAAI 2019
RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications AAAI 2019
Capacity Control of ReLU Neural Networks by Basis-Path Norm AAAI 2019
Weighted Channel Dropout for Regularization of Deep Convolutional Neural Network AAAI 2019
Calibrated Stochastic Gradient Descent for Convolutional Neural Networks AAAI 2019
A Meta-Learning Approach for Custom Model Training AAAI 2019
Continual and Multi-Task Architecture Search ACL 2019
Regularizing Neural Networks via Stochastic Branch Layers ACML 2019
Bayesian Learning of Neural Network Architectures AISTATS 2019
Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron AISTATS 2019
Revisit Batch Normalization: New Understanding and Refinement via Composition Optimization AISTATS 2019
Neural Rejuvenation: Improving Deep Network Training by Enhancing Computational Resource Utilization CVPR 2019
On Implicit Filter Level Sparsity in Convolutional Neural Networks CVPR 2019
Searching for a Robust Neural Architecture in Four GPU Hours CVPR 2019
Understanding the Disharmony Between Dropout and Batch Normalization by Variance Shift CVPR 2019
MnasNet: Platform-Aware Neural Architecture Search for Mobile CVPR 2019
MS-TCN: Multi-Stage Temporal Convolutional Network for Action Segmentation CVPR 2019
RENAS: Reinforced Evolutionary Neural Architecture Search CVPR 2019
Centripetal SGD for Pruning Very Deep Convolutional Networks With Complicated Structure CVPR 2019
Dynamic Recursive Neural Network CVPR 2019