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154views
12 years 11 months ago
Preference elicitation and inverse reinforcement learning
We state the problem of inverse reinforcement learning in terms of preference elicitation, resulting in a principled (Bayesian) statistical formulation. This generalises previous w...
Constantin Rothkopf, Christos Dimitrakakis
NAACL
2007
13 years 10 months ago
A Systematic Exploration of the Feature Space for Relation Extraction
Relation extraction is the task of finding semantic relations between entities from text. The state-of-the-art methods for relation extraction are mostly based on statistical lea...
Jing Jiang, ChengXiang Zhai
ICDM
2008
IEEE
92views Data Mining» more  ICDM 2008»
14 years 3 months ago
A Shrinkage Approach for Modeling Non-stationary Relational Autocorrelation
Recent research has shown that collective classification in relational data often exhibit significant performance gains over conventional approaches that classify instances indi...
Pelin Angin, Jennifer Neville
ICDM
2005
IEEE
137views Data Mining» more  ICDM 2005»
14 years 2 months ago
Leveraging Relational Autocorrelation with Latent Group Models
The presence of autocorrelation provides a strong motivation for using relational learning and inference techniques. Autocorrelation is a statistical dependence between the values...
Jennifer Neville, David Jensen
CCS
2009
ACM
14 years 3 months ago
Learning your identity and disease from research papers: information leaks in genome wide association study
Genome-wide association studies (GWAS) aim at discovering the association between genetic variations, particularly single-nucleotide polymorphism (SNP), and common diseases, which...
Rui Wang, Yong Fuga Li, XiaoFeng Wang, Haixu Tang,...