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ILP
1999
Springer
15 years 8 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
15 years 5 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
15 years 5 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
CIVR
2006
Springer
201views Image Analysis» more  CIVR 2006»
15 years 7 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
15 years 5 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...