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Neural Network Optimization

3648 directly classified papers

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Papers

Improving Optimization for Models With Continuous Symmetry Breaking ICML 2018
Stronger Generalization Bounds for Deep Nets via a Compression Approach ICML 2018
Learning to Converse with Noisy Data: Generation with Calibration IJCAI 2018
Improving Deep Neural Network Sparsity through Decorrelation Regularization IJCAI 2018
Accelerated Stochastic Power Iteration AISTATS 2018
FLAG n’ FLARE: Fast Linearly-Coupled Adaptive Gradient Methods AISTATS 2018
Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization AISTATS 2018
Accelerated Stochastic Mirror Descent: From Continuous-time Dynamics to Discrete-time Algorithms AISTATS 2018
Adaptive balancing of gradient and update computation times using global geometry and approximate subproblems AISTATS 2018
Convergence diagnostics for stochastic gradient descent with constant learning rate AISTATS 2018
A Unified Analysis of Stochastic Momentum Methods for Deep Learning IJCAI 2018
Automatic Differentiation in Machine Learning: a Survey JMLR 2018
Deep Noise Tracking Network: A Hybrid Signal Processing/Deep Learning Approach to Speech Enhancement INTERSPEECH 2018
Memory Time Span in LSTMs for Multi-Speaker Source Separation INTERSPEECH 2018
Role of Regularization in the Prediction of Valence from Speech INTERSPEECH 2018
Towards Robust Neural Machine Translation ACL 2018
Improved Asynchronous Parallel Optimization Analysis for Stochastic Incremental Methods JMLR 2018
The Implicit Bias of Gradient Descent on Separable Data JMLR 2018
Gradient Descent Learns Linear Dynamical Systems JMLR 2018
Reproducing and Regularizing the SCRN Model COLING 2018
Adaptive Weighting for Neural Machine Translation COLING 2018
Learning with Noise-Contrastive Estimation: Easing training by learning to scale COLING 2018
A Full End-to-End Semantic Role Labeler, Syntactic-agnostic Over Syntactic-aware? COLING 2018
Data-driven Onboard Scheduling for an Autonomous Observation Satellite IJCAI 2018
On the Convergence Properties of a K-step Averaging Stochastic Gradient Descent Algorithm for Nonconvex Optimization IJCAI 2018