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07/28/2020
Stochastic Normalized Gradient Descent with Momentum for Large Batch Training
Stochastic gradient descent (SGD) and its variants have been the dominat...
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02/26/2020
Stagewise Enlargement of Batch Size for SGD-based Learning
Existing research shows that the batch size can seriously affect the per...
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06/11/2019
ADASS: Adaptive Sample Selection for Training Acceleration
Stochastic gradient decent (SGD) and its variants, including some accele...
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06/06/2019
Clustered Reinforcement Learning
Exploration strategy design is one of the challenging problems in reinfo...
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05/30/2019
On the Convergence of Memory-Based Distributed SGD
Distributed stochastic gradient descent (DSGD) has been widely used for ...
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05/30/2019
Global Momentum Compression for Sparse Communication in Distributed SGD
With the rapid growth of data, distributed stochastic gradient descent (...
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01/10/2019
Quantized Epoch-SGD for Communication-Efficient Distributed Learning
Due to its efficiency and ease to implement, stochastic gradient descent...
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03/15/2018
Proximal SCOPE for Distributed Sparse Learning: Better Data Partition Implies Faster Convergence Rate
Distributed sparse learning with a cluster of multiple machines has attr...
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02/10/2018
Feature-Distributed SVRG for High-Dimensional Linear Classification
Linear classification has been widely used in many high-dimensional appl...
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01/30/2016
SCOPE: Scalable Composite Optimization for Learning on Spark
Many machine learning models, such as logistic regression (LR) and suppo...
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08/24/2015