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SDM
2012
SIAM
237views Data Mining» more  SDM 2012»
11 years 10 months ago
A Distributed Kernel Summation Framework for General-Dimension Machine Learning
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray
ICML
1998
IEEE
14 years 8 months ago
RL-TOPS: An Architecture for Modularity and Re-Use in Reinforcement Learning
This paper introduces the RL-TOPs architecture for robot learning, a hybrid system combining teleo-reactive planning and reinforcement learning techniques. The aim of this system ...
Malcolm R. K. Ryan, Mark D. Pendrith
ICML
2006
IEEE
14 years 8 months ago
Nonstationary kernel combination
The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...
SDL
2007
152views Hardware» more  SDL 2007»
13 years 9 months ago
TTCN-3 Quality Engineering: Using Learning Techniques to Evaluate Metric Sets
Software metrics are an essential means to assess software quality. For the assessment of software quality, typically sets of complementing metrics are used since individual metric...
Edith Werner, Jens Grabowski, Helmut Neukirchen, N...
ACTAC
2006
126views more  ACTAC 2006»
13 years 7 months ago
Named Entity Recognition for Hungarian Using Various Machine Learning Algorithms
In this paper we introduce a statistical Named Entity recognizer (NER) system for the Hungarian language. We examined three methods for identifying and disambiguating proper nouns...
Richárd Farkas, György Szarvas, Andr&a...