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Optimization

1638 directly classified papers

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Papers

A Dual Approach to Verify and Train Deep Networks IJCAI 2019
Meta-Learning With Differentiable Convex Optimization CVPR 2019
Beyond Gradient Descent for Regularized Segmentation Losses CVPR 2019
Min-Max Statistical Alignment for Transfer Learning CVPR 2019
Robustness via Curvature Regularization, and Vice Versa CVPR 2019
Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidth CVPR 2019
HAQ: Hardware-Aware Automated Quantization With Mixed Precision CVPR 2019
DeepView: View Synthesis With Learned Gradient Descent CVPR 2019
TIGS: An Inference Algorithm for Text Infilling with Gradient Search ACL 2019
Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search ICML 2019
Stochastic Gradient Push for Distributed Deep Learning ICML 2019
A Margin-based Loss with Synthetic Negative Samples for Continuous-output Machine Translation EMNLP 2019
Making Asynchronous Stochastic Gradient Descent Work for Transformers EMNLP 2019
Gradient Descent Finds Global Minima of Deep Neural Networks ICML 2019
Band-limited Training and Inference for Convolutional Neural Networks ICML 2019
Trading Redundancy for Communication: Speeding up Distributed SGD for Non-convex Optimization ICML 2019
Improving Deep Transformer with Depth-Scaled Initialization and Merged Attention EMNLP 2019
Speculative Beam Search for Simultaneous Translation EMNLP 2019
Improved Differentiable Architecture Search for Language Modeling and Named Entity Recognition EMNLP 2019
Combining Global Sparse Gradients with Local Gradients in Distributed Neural Network Training EMNLP 2019
AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks AAAI 2019
MPD-AL: An Efficient Membrane Potential Driven Aggregate-Label Learning Algorithm for Spiking Neurons AAAI 2019
Comparing Sample-Wise Learnability across Deep Neural Network Models AAAI 2019
RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications AAAI 2019
Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning AAAI 2019