Sciweavers

940 search results - page 7 / 188
» Learning Word Representations from Relational Graphs
Sort
View
IJCAI
2007
14 years 11 months ago
Change of Representation for Statistical Relational Learning
Statistical relational learning (SRL) algorithms learn statistical models from relational data, such as that stored in a relational database. We previously introduced view learnin...
Jesse Davis, Irene M. Ong, Jan Struyf, Elizabeth S...
98
Voted
WEBI
2010
Springer
14 years 7 months ago
Relations Expansion: Extracting Relationship Instances from the Web
In this paper, we propose a Relation Expansion framework, which uses a few seed sentences marked up with two entities to expand a set of sentences containing target relations. Duri...
Haibo Li, Yutaka Matsuo, Mitsuru Ishizuka
76
Voted
HYBRID
1998
Springer
15 years 1 months ago
Large Patterns Make Great Symbols: An Example of Learning from Example
We look at distributed representation of structure with variable binding, that is natural for neural nets and allows traditional symbolic representation and processing. The repres...
Pentti Kanerva
81
Voted
MLDM
2005
Springer
15 years 3 months ago
Low-Level Cursive Word Representation Based on Geometric Decomposition
Abstract. An efficient low-level word image representation plays a crucial role in general cursive word recognition. This paper proposes a novel representation scheme, where a word...
Jian-xiong Dong, Adam Krzyzak, Ching Y. Suen, Domi...
83
Voted
ILP
2003
Springer
15 years 2 months ago
Graph Kernels and Gaussian Processes for Relational Reinforcement Learning
RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
Thomas Gärtner, Kurt Driessens, Jan Ramon