Sciweavers

2440 search results - page 173 / 488
» Learn .MT: A New Approach to Incremental Learning
Sort
View
FSS
2008
110views more  FSS 2008»
15 years 6 months ago
Learning valued preference structures for solving classification problems
This paper introduces a new approach to classification which combines pairwise decomposition techniques with ideas and tools from fuzzy preference modeling. More specifically, our...
Eyke Hüllermeier, Klaus Brinker
IEAAIE
2010
Springer
15 years 4 months ago
Learning User Preferences to Maximise Occupant Comfort in Office Buildings
It is desirable to ensure that the thermal comfort conditions in offices are in line with the preferences of occupants. Controlling their offices correctly therefore requires the c...
Anika Schumann, Nic Wilson, Mateo Burillo
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
2000
ACM
154views Machine Learning» more  ML 2000»
15 years 6 months ago
Lazy Learning of Bayesian Rules
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...
Zijian Zheng, Geoffrey I. Webb
ICRA
2010
IEEE
164views Robotics» more  ICRA 2010»
15 years 5 months ago
Boundary detection based on supervised learning
— Detecting the boundaries of objects is a key step in separating foreground objects from the background, which is useful for robotics and computer vision applications, such as o...
Kiho Kwak, Daniel F. Huber, Jeongsook Chae, Takeo ...