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KDD
2009
ACM
198views Data Mining» more  KDD 2009»
14 years 10 months ago
Heterogeneous source consensus learning via decision propagation and negotiation
Nowadays, enormous amounts of data are continuously generated not only in massive scale, but also from different, sometimes conflicting, views. Therefore, it is important to conso...
Jing Gao, Wei Fan, Yizhou Sun, Jiawei Han
KDD
2008
ACM
150views Data Mining» more  KDD 2008»
14 years 10 months ago
Hypergraph spectral learning for multi-label classification
A hypergraph is a generalization of the traditional graph in which the edges are arbitrary non-empty subsets of the vertex set. It has been applied successfully to capture highord...
Liang Sun, Shuiwang Ji, Jieping Ye
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 10 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal
ATAL
2007
Springer
14 years 3 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
HICSS
2006
IEEE
163views Biometrics» more  HICSS 2006»
14 years 3 months ago
Learning Ranking vs. Modeling Relevance
The classical (ad hoc) document retrieval problem has been traditionally approached through ranking according to heuristically developed functions (such as tf.idf or bm25) or gene...
Dmitri Roussinov, Weiguo Fan