MLI is an Application Programming Interface designed to address the challenges of building Machine Learning algorithms in a distributed setting based on data-centric computing. Its primary goal is to simplify the development of high-performance, scalable, distributed algorithms. Our initial results show that, relative to existing systems, this interface can be used to build distributed implementations of a wide variety of common Machine Learning algorithms with minimal complexity and highly competitive performance and scalability.
MLI REF is an API on top of MLBase (and Spark) to ease the development of various distributed machine learning algorithms (e.g., SGD).
MLI: An API for Distributed Machine Learning
2013 IEEE 13th International Conference on Data Mining
2013 IEEE 13th International Conference on Data Mining
Computer Science Mathematics