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» Learning from labeled and unlabeled data on a directed graph
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ICCV
2007
IEEE
15 years 6 months ago
Contextual Distance for Data Perception
Structural perception of data plays a fundamental role in pattern analysis and machine learning. In this paper, we develop a new structural perception of data based on local conte...
Deli Zhao, Zhouchen Lin, Xiaoou Tang
ITS
2004
Springer
130views Multimedia» more  ITS 2004»
15 years 5 months ago
Opening the Door to Non-programmers: Authoring Intelligent Tutor Behavior by Demonstration
Abstract. Intelligent tutoring systems are quite difficult and time intensive to develop. In this paper, we describe a method and set of software tools that ease the process of cog...
Kenneth R. Koedinger, Vincent Aleven, Neil T. Heff...
EMNLP
2011
13 years 11 months ago
Multi-Source Transfer of Delexicalized Dependency Parsers
We present a simple method for transferring dependency parsers from source languages with labeled training data to target languages without labeled training data. We first demons...
Ryan T. McDonald, Slav Petrov, Keith Hall
KDD
2008
ACM
193views Data Mining» more  KDD 2008»
16 years 4 days ago
A family of dissimilarity measures between nodes generalizing both the shortest-path and the commute-time distances
This work introduces a new family of link-based dissimilarity measures between nodes of a weighted directed graph. This measure, called the randomized shortest-path (RSP) dissimil...
Luh Yen, Marco Saerens, Amin Mantrach, Masashi Shi...
IJCAI
1997
15 years 1 months ago
Machine Learning Techniques to Make Computers Easier to Use
Identifying user-dependent information that can be automatically collected helps build a user model by which 1) to predict what the user wants to do next and 2) to do relevant pre...
Hiroshi Motoda, Kenichi Yoshida