https://github.com/ljk628/ML-Systems

papers on scalable and efficient machine learning systems
https://github.com/ljk628/ML-Systems

convolutional-neural-networks deep-learning distributed-computing machine-learning optimization

Last synced: about 2 months ago
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papers on scalable and efficient machine learning systems

• Host: GitHub
• URL: https://github.com/ljk628/ML-Systems
• Owner: ljk628
• Created: 2015-09-09T02:50:26.000Z (about 9 years ago)
• Default Branch: master
• Last Pushed: 2018-09-28T06:49:56.000Z (almost 6 years ago)
• Last Synced: 2024-04-22T00:53:44.267Z (5 months ago)
• Topics: convolutional-neural-networks, deep-learning, distributed-computing, machine-learning, optimization
• Homepage:
• Size: 85.9 KB
• Stars: 188
• Watchers: 19
• Forks: 42
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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• awesome-machine-learning-resources - **[List - Systems?style=social) (Table of Contents)

README

        
# Fast and Scalable Machine Learning: Algorithms and Systems

This is a collection of papers about recent progress in machine learning and systems, including distributed machine learning, deep learning and etc.

## Contents

1. Deep Learning

	- [Convolutional Neural Networks](dl_cnn.md)  

		- [ImageNet Models](dl_cnn.md#imagenet-models)  

		- [Architecture Design](dl_cnn.md#architecture-design)  

		- [Activation Functions](dl_cnn.md#activation-functions)  

		- [Visualization](dl_cnn.md#visualization)  

		- [Fast Convolution](dl_cnn.md#fast-convolution)  

		- [Low-Rank Filter Approximation](dl_cnn.md#low-rank-filter-approximation)

		- [Low Precision](dl_cnn.md#low-precision)  

		- [Parameter Pruning](dl_cnn.md#parameter-pruning)  

		- [Transfer Learning](dl_cnn.md#transfer-learning)  

		- [Theory](dl_cnn.md#theory)  

		- [3D Data](dl_cnn.md#3d-data)  

		- [Hardware](dl_cnn.md#hardware)  

	- [Optimization for Deep Learning](dl_opt.md)  

		- [Generalization](dl_opt.md#generalization)  

		- [Loss Surface](dl_opt.md#loss-surface)  

		- [Batch Size](dl_opt.md#batch-size)  

		- [General](dl_opt.md#general)  

		- [Adaptive Gradient Methods](dl_opt.md#adaptive-gradient-methods)  

		- [Distributed Optimization](dl_opt.md#distributed-optimization)  

		- [Initialization](dl_opt.md#initialization)  

		- [Low Precision](dl_opt.md#low-precision)  

		- [Normalization](dl_opt.md#normalization)  

		- [Regularization](dl_opt.md#regularization)  

		- [Meta Learning](dl_opt.md#meta-learning)  

	- [Deep Learning Systems](dl_sys.md) 	

		- [General Frameworks](dl_sys.md#general-frameworks)  

		- [Specific System](dl_sys.md#specific-system)  

		- [Parallelization](dl_sys.md#parallelization)  

2. Distributed Machine Learning

	- [Distributed Optimization](dist_ml.md#distributed-optimization)

	- [Distributed ML Systems](dist_ml.md#distributed-ml-systems)

3. Other Topics

	- [Matrix Factorization](matrix_fact.md)

	- [Graph Computation](graph.md)