Sciweavers

8970 search results - page 1379 / 1794
» Learning to Learn Causal Models
Sort
View
AIR
2004
113views more  AIR 2004»
15 years 6 months ago
Class Noise vs. Attribute Noise: A Quantitative Study
Real-world data is never perfect and can often suffer from corruptions (noise) that may impact interpretations of the data, models created from the data and decisions made based on...
Xingquan Zhu, Xindong Wu
UMUAI
2008
192views more  UMUAI 2008»
15 years 6 months ago
Automatic detection of learner's affect from conversational cues
We explored the reliability of detecting a learner's affect from conversational features extracted from interactions with AutoTutor, an intelligent tutoring system that helps...
Sidney K. D'Mello, Scotty D. Craig, Amy M. Withers...
AI
2000
Springer
15 years 6 months ago
Wrapper induction: Efficiency and expressiveness
The Internet presents numerous sources of useful information--telephone directories, product catalogs, stock quotes, event listings, etc. Recently, many systems have been built th...
Nicholas Kushmerick
SAC
2010
ACM
15 years 1 months ago
A new methodology for photometric validation in vehicles visual interactive systems
This work proposes a new methodology for automatically validating the internal lighting system of an automotive, i.e., assessing the visual quality of an instrument cluster (IC) f...
Alexandre W. C. Faria, David Menotti, Daniel S. D....
KDD
2012
ACM
247views Data Mining» more  KDD 2012»
13 years 9 months ago
Integrating meta-path selection with user-guided object clustering in heterogeneous information networks
Real-world, multiple-typed objects are often interconnected, forming heterogeneous information networks. A major challenge for link-based clustering in such networks is its potent...
Yizhou Sun, Brandon Norick, Jiawei Han, Xifeng Yan...
« Prev « First page 1379 / 1794 Last » Next »