Neural Network Optimization

Memory Efficient Adaptive Optimization NeurIPS 2019 Meta-Curvature NeurIPS 2019 Meta-Descent for Online, Continual Prediction AAAI 2019 MetaInit: Initializing learning by learning to initialize NeurIPS 2019 MetaQuant: Learning to Quantize by Learning to Penetrate Non-differentiable Quantization NeurIPS 2019 Metatrace Actor-Critic: Online Step-Size Tuning by Meta-gradient Descent for Reinforcement Learning Control IJCAI 2019 MFAS: Multimodal Fusion Architecture Search CVPR 2019 Momentum-Based Variance Reduction in Non-Convex SGD NeurIPS 2019 Monotone Learning with Rectified Wire Networks JMLR 2019 Multinomial Distribution Learning for Effective Neural Architecture Search ICCV 2019 NAS-Bench-101: Towards Reproducible Neural Architecture Search ICML 2019 Neural Architecture Search: A Survey JMLR 2019 Neural Temporal-Difference Learning Converges to Global Optima NeurIPS 2019 Neuron birth-death dynamics accelerates gradient descent and converges asymptotically ICML 2019 Neurons Merging Layer: Towards Progressive Redundancy Reduction for Deep Supervised Hashing IJCAI 2019 New Convergence Aspects of Stochastic Gradient Algorithms JMLR 2019 Non-Autoregressive Machine Translation with Auxiliary Regularization AAAI 2019 Nonlinear Acceleration of Primal-Dual Algorithms AISTATS 2019 Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics NeurIPS 2019 Normal Approximation for Stochastic Gradient Descent via Non-Asymptotic Rates of Martingale CLT COLT 2019 Nostalgic Adam: Weighting More of the Past Gradients When Designing the Adaptive Learning Rate IJCAI 2019 Numerical Optimization to AI, and Back AAAI 2019 On Dropout and Nuclear Norm Regularization ICML 2019 One-Shot Neural Architecture Search via Self-Evaluated Template Network ICCV 2019 One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers NeurIPS 2019