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AAAI
2007
13 years 9 months ago
Learning Voting Trees
Binary voting trees provide a succinct representation for a large and prominent class of voting rules. In this paper, we investigate the PAC-learnability of this class of rules. W...
Ariel D. Procaccia, Aviv Zohar, Yoni Peleg, Jeffre...
GECCO
2004
Springer
107views Optimization» more  GECCO 2004»
14 years 26 days ago
Multiple Species Weighted Voting - A Genetics-Based Machine Learning System
Multiple Species Weighted Voting (MSWV) is a genetics-based machine learning (GBML) system with relatively few parameters that combines N two-class classifiers into an N -class cla...
Alexander F. Tulai, Franz Oppacher
ECCV
2002
Springer
14 years 9 months ago
Probabilistic and Voting Approaches to Cue Integration for Figure-Ground Segmentation
This paper describes techniques for fusing the output of multiple cues to robustly and accurately segment foreground objects from the background in image sequences. Two different m...
Eric Hayman, Jan-Olof Eklundh
ICML
1999
IEEE
14 years 8 months ago
The Alternating Decision Tree Learning Algorithm
The applicationofboosting procedures to decision tree algorithmshas been shown to produce very accurate classi ers. These classiers are in the form of a majority vote over a numbe...
Yoav Freund, Llew Mason
AAAI
2010
13 years 9 months ago
Good Rationalizations of Voting Rules
The concept of distance rationalizability allows one to define new voting rules or "rationalize" existing ones via a consensus class of elections and a distance. A conse...
Edith Elkind, Piotr Faliszewski, Arkadii M. Slinko