Neural Network Optimization

Go Wide, Then Narrow: Efficient Training of Deep Thin Networks ICML 2020 Group-Wise Dynamic Dropout Based on Latent Semantic Variations AAAI 2020 How Good is SGD with Random Shuffling? COLT 2020 HyperSTAR: Task-Aware Hyperparameters for Deep Networks CVPR 2020 Information-Theoretic Local Minima Characterization and Regularization ICML 2020 Interpolation Technique to Speed Up Gradients Propagation in Neural ODEs NeurIPS 2020 Is the Skip Connection Provable to Reform the Neural Network Loss Landscape? IJCAI 2020 L2-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks CVPR 2020 Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks ICML 2020 Learning Dynamic Routing for Semantic Segmentation CVPR 2020 Learning Over-Parametrized Two-Layer Neural Networks beyond NTK COLT 2020 Learning to Optimize Non-Rigid Tracking CVPR 2020 Lipschitz Constrained Parameter Initialization for Deep Transformers ACL 2020 Local Regularizer Improves Generalization AAAI 2020 Maximum-and-Concatenation Networks ICML 2020 MemNAS: Memory-Efficient Neural Architecture Search With Grow-Trim Learning CVPR 2020 MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation CVPR 2020 MTL-NAS: Task-Agnostic Neural Architecture Search Towards General-Purpose Multi-Task Learning CVPR 2020 Network Adjustment: Channel Search Guided by FLOPs Utilization Ratio CVPR 2020 Network as Regularization for Training Deep Neural Networks: Framework, Model and Performance AAAI 2020 Neural Architecture Generator Optimization NeurIPS 2020 Neural Architecture Search for Keyword Spotting Interspeech 2020 Neural Architecture Search in A Proxy Validation Loss Landscape ICML 2020 Neural Architecture Search on Acoustic Scene Classification Interspeech 2020 Neural Architecture Search Using Deep Neural Networks and Monte Carlo Tree Search AAAI 2020