Tuning compiler optimizations for rapidly evolving hardware makes porting and extending an optimizing compiler for each new platform extremely challenging. Iterative optimization i...
Grigori Fursin, Yuriy Kashnikov, Abdul Wahid Memon...
Platt’s probabilistic outputs for Support Vector Machines (Platt, 2000) has been popular for applications that require posterior class probabilities. In this note, we propose an ...
The growing complexity of modern processors has made the development of highly efficient code increasingly difficult. Manually developing highly efficient code is usually expen...
Abstract—MapReduce is emerging as a generic parallel programming paradigm for large clusters of machines. This trend combined with the growing need to run machine learning (ML) a...
Amol Ghoting, Rajasekar Krishnamurthy, Edwin P. D....
The results of a machine learning from user behavior can be thought of as a program, and like all programs, it may need to be debugged. Providing ways for the user to debug it mat...