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» Learning Causal Models of Relational Domains
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NIPS
2008
13 years 8 months ago
Stochastic Relational Models for Large-scale Dyadic Data using MCMC
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
Shenghuo Zhu, Kai Yu, Yihong Gong
ACL
2010
13 years 5 months ago
Open-Domain Semantic Role Labeling by Modeling Word Spans
Most supervised language processing systems show a significant drop-off in performance when they are tested on text that comes from a domain significantly different from the domai...
Fei Huang, Alexander Yates
AAAI
2011
12 years 7 months ago
Combining Learned Discrete and Continuous Action Models
Action modeling is an important skill for agents that must perform tasks in novel domains. Previous work on action modeling has focused on learning STRIPS operators in discrete, r...
Joseph Z. Xu, John E. Laird
CVPR
2012
IEEE
11 years 9 months ago
A Unified Framework for Event Summarization and Rare Event Detection
A novel approach for event summarization and rare event detection is proposed. Unlike conventional methods that deal with event summarization and rare event detection independently...
Junseok Kwon and Kyoung Mu Lee
CRIWG
2001
13 years 8 months ago
Integration of Domain-Specific Elements into Visual Language Based Collaborative Environments
This paper presents an approach for the integration of domain related elements and operational semantics into collaborative environments based on visual languages. This integratio...
Niels Pinkwart, Heinz Ulrich Hoppe, Katrin Ga&szli...