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ILP
1999
Springer
15 years 1 months ago
Probabilistic Relational Models
Most real-world data is heterogeneous and richly interconnected. Examples include the Web, hypertext, bibliometric data and social networks. In contrast, most statistical learning...
Daphne Koller
ECTEL
2010
Springer
14 years 10 months ago
Orchestrating Learning Using Adaptive Educational Designs in IMS Learning Design
: IMS Learning Design (IMS LD) is an open specification to support interoperability of advanced educational designs for a wide range of technology-enhanced learning solutions and o...
Marion R. Gruber, Christian Glahn, Marcus Specht, ...
NIPS
2007
14 years 11 months ago
Gaussian Process Models for Link Analysis and Transfer Learning
In this paper we model relational random variables on the edges of a network using Gaussian processes (GPs). We describe appropriate GP priors, i.e., covariance functions, for dir...
Kai Yu, Wei Chu
81
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CIVR
2006
Springer
201views Image Analysis» more  CIVR 2006»
15 years 1 months ago
Efficient Margin-Based Rank Learning Algorithms for Information Retrieval
Learning a good ranking function plays a key role for many applications including the task of (multimedia) information retrieval. While there are a few rank learning methods availa...
Rong Yan, Alexander G. Hauptmann
AAAI
2010
14 years 11 months ago
Structure Learning for Markov Logic Networks with Many Descriptive Attributes
Many machine learning applications that involve relational databases incorporate first-order logic and probability. Markov Logic Networks (MLNs) are a prominent statistical relati...
Hassan Khosravi, Oliver Schulte, Tong Man, Xiaoyua...