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CVPR
2010
IEEE
15 years 11 months ago
Boundary Learning by Optimization with Topological Constraints
Recent studies have shown that machine learning can improve the accuracy of detecting object boundaries in images. In the standard approach, a boundary detector is trained by mini...
Viren Jain, Benjamin Bollmann, Bobby Kasthuri, Ken...
144
Voted
ICRA
2003
IEEE
222views Robotics» more  ICRA 2003»
15 years 8 months ago
Path planning using learned constraints and preferences
— In this paper we present a novel method for robot path planning based on learning motion patterns. A motion pattern is defined as the path that results from applying a set of ...
Gregory Dudek, Saul Simhon
138
Voted
ECML
2003
Springer
15 years 8 months ago
Pairwise Preference Learning and Ranking
We consider supervised learning of a ranking function, which is a mapping from instances to total orders over a set of labels (options). The training information consists of exampl...
Johannes Fürnkranz, Eyke Hüllermeier
INCDM
2010
Springer
159views Data Mining» more  INCDM 2010»
15 years 7 months ago
Semi-supervised Learning for False Alarm Reduction
Abstract. Intrusion Detection Systems (IDSs) which have been deployed in computer networks to detect a wide variety of attacks are suffering how to manage of a large number of tri...
Chien-Yi Chiu, Yuh-Jye Lee, Chien-Chung Chang, Wen...
134
Voted
ECML
2006
Springer
15 years 6 months ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...