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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...
MICRO
2009
IEEE
113views Hardware» more  MICRO 2009»
16 years 1 months ago
Portable compiler optimisation across embedded programs and microarchitectures using machine learning
Building an optimising compiler is a difficult and time consuming task which must be repeated for each generation of a microprocessor. As the underlying microarchitecture changes...
Christophe Dubach, Timothy M. Jones, Edwin V. Boni...
CIKM
2009
Springer
16 years 1 months ago
A machine learning approach for improved BM25 retrieval
Despite the widespread use of BM25, there have been few studies examining its effectiveness on a document description over single and multiple field combinations. We determine t...
Krysta Marie Svore, Christopher J. C. Burges
COMPSAC
2007
IEEE
16 years 25 days ago
Learning Parameterized State Machine Model for Integration Testing
Although many of the software engineering activities can now be model-supported, the model is often missing in software development. We are interested in retrieving statemachine m...
Muzammil Shahbaz, Keqin Li 0002, Roland Groz