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» Noise-Tolerant Instance-Based Learning Algorithms
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ROBOCUP
2007
Springer
99views Robotics» more  ROBOCUP 2007»
14 years 1 months ago
Instance-Based Action Models for Fast Action Planning
Abstract. Two main challenges of robot action planning in real domains are uncertain action effects and dynamic environments. In this paper, an instance-based action model is lear...
Mazda Ahmadi, Peter Stone
ISBI
2009
IEEE
14 years 2 months ago
Instance-Based Generative Biological Shape Modeling
Biological shape modeling is an essential task that is required for systems biology efforts to simulate complex cell behaviors. Statistical learning methods have been used to buil...
Tao Peng, Wei Wang, Gustavo K. Rohde, Robert F. Mu...
ESWS
2008
Springer
13 years 9 months ago
Instance Based Clustering of Semantic Web Resources
Abstract. The original Semantic Web vision was explicit in the need for intelligent autonomous agents that would represent users and help them navigate the Semantic Web. We argue t...
Gunnar Aastrand Grimnes, Peter Edwards, Alun D. Pr...
ALT
2002
Springer
14 years 4 months ago
Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning
We describe a new boosting algorithm that is the first such algorithm to be both smooth and adaptive. These two features make possible performance improvements for many learning ...
Dmitry Gavinsky
ISTCS
1997
Springer
13 years 11 months ago
Learning with Queries Corrupted by Classification Noise
Kearns introduced the "statistical query" (SQ) model as a general method for producing learning algorithms which are robust against classification noise. We extend this ...
Jeffrey C. Jackson, Eli Shamir, Clara Shwartzman