Neural Network Optimization

Controlling Neural Level Sets NeurIPS 2019 Control Regularization for Reduced Variance Reinforcement Learning ICML 2019 Convergence of Adversarial Training in Overparametrized Neural Networks NeurIPS 2019 Convergence of Gradient Descent on Separable Data AISTATS 2019 Critical Learning Periods in Deep Networks ICLR 2019 Cubic Regularization with Momentum for Nonconvex Optimization UAI 2019 Customizable Architecture Search for Semantic Segmentation CVPR 2019 DARTS: Differentiable Architecture Search ICLR 2019 Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation NeurIPS 2019 DATA: Differentiable ArchiTecture Approximation NeurIPS 2019 Data-Driven Neuron Allocation for Scale Aggregation Networks CVPR 2019 DBDNet: Learning Bi-directional Dynamics for Early Action Prediction IJCAI 2019 Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask NeurIPS 2019 Deep Cascade Multi-Task Learning for Slot Filling in Online Shopping Assistant AAAI 2019 Deep Equilibrium Models NeurIPS 2019 Deep Frank-Wolfe For Neural Network Optimization ICLR 2019 Deep Learning without Weight Transport NeurIPS 2019 Deeply-Supervised Knowledge Synergy CVPR 2019 Deep Neural Networks with Multi-Branch Architectures Are Intrinsically Less Non-Convex AISTATS 2019 DeepOBS: A Deep Learning Optimizer Benchmark Suite ICLR 2019 Deep Reinforcement Learning via Past-Success Directed Exploration AAAI 2019 Deep RNN Framework for Visual Sequential Applications CVPR 2019 Demystifying Dropout ICML 2019 Diagnosing Bottlenecks in Deep Q-learning Algorithms ICML 2019 Differentiable Dynamic Normalization for Learning Deep Representation ICML 2019