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Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization
Numerous empirical evidences have corroborated the importance of noise i...
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Regularized Attentive Capsule Network for Overlapped Relation Extraction
Distantly supervised relation extraction has been widely applied in know...
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A Benchmarking Framework for Interactive 3D Applications in the Cloud
With the growing popularity of cloud gaming and cloud virtual reality (V...
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On Computation and Generalization of Generative Adversarial Imitation Learning
Generative Adversarial Imitation Learning (GAIL) is a powerful and pract...
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Online Quantification of Input Model Uncertainty by Two-Layer Importance Sampling
Stochastic simulation has been widely used to analyze the performance of...
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Towards Understanding the Importance of Shortcut Connections in Residual Networks
Residual Network (ResNet) is undoubtedly a milestone in deep learning. R...
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Towards Understanding the Importance of Noise in Training Neural Networks
Numerous empirical evidence has corroborated that the noise plays a cruc...
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Neural Relation Extraction via Inner-Sentence Noise Reduction and Transfer Learning
Extracting relations is critical for knowledge base completion and const...
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Towards Understanding Acceleration Tradeoff between Momentum and Asynchrony in Nonconvex Stochastic Optimization
Asynchronous momentum stochastic gradient descent algorithms (Async-MSGD...
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Toward Deeper Understanding of Nonconvex Stochastic Optimization with Momentum using Diffusion Approximations
Momentum Stochastic Gradient Descent (MSGD) algorithm has been widely ap...
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Implementation of Training Convolutional Neural Networks
Deep learning refers to the shining branch of machine learning that is b...
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