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IJPP
2011
115views more  IJPP 2011»
14 years 10 months ago
Milepost GCC: Machine Learning Enabled Self-tuning Compiler
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...
ML
2007
ACM
130views Machine Learning» more  ML 2007»
15 years 6 months ago
A note on Platt's probabilistic outputs for support vector machines
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 ...
Hsuan-Tien Lin, Chih-Jen Lin, Ruby C. Weng
IPPS
2007
IEEE
16 years 26 days ago
Optimizing Sorting with Machine Learning Algorithms
The growing complexity of modern processors has made the development of highly efficient code increasingly difficult. Manually developing highly efficient code is usually expen...
Xiaoming Li, María Jesús Garzar&aacu...
ICDE
2011
IEEE
258views Database» more  ICDE 2011»
14 years 10 months ago
SystemML: Declarative machine learning on MapReduce
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....
IUI
2009
ACM
16 years 3 months ago
Fixing the program my computer learned: barriers for end users, challenges for the machine
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...
Todd Kulesza, Weng-Keen Wong, Simone Stumpf, Steph...