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ILP
2007
Springer
15 years 4 months ago
Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates
Statistical Relational Learning (SRL) combines the benefits of probabilistic machine learning approaches with complex, structured domains from Inductive Logic Programming (ILP). W...
Mark Goadrich, Jude W. Shavlik
JCT
1998
70views more  JCT 1998»
14 years 10 months ago
Partitions into Distinct Parts and Elliptic Curves
Let Q(N) denote the number of partitions of N into distinct parts. If ω(k) := 3k2 +k 2 , then it is well known that Q(N) + ∞X k=1 (−1)k “ Q(N − 2ω(k)) + Q(N − 2ω(−k)...
Ken Ono
ECML
2007
Springer
15 years 4 months ago
Probabilistic Explanation Based Learning
Abstract. Explanation based learning produces generalized explanations from examples. These explanations are typically built in a deductive manner and they aim to capture the essen...
Angelika Kimmig, Luc De Raedt, Hannu Toivonen
PVLDB
2010
252views more  PVLDB 2010»
14 years 5 months ago
Efficient and Effective Similarity Search over Probabilistic Data based on Earth Mover's Distance
Probabilistic data is coming as a new deluge along with the technical advances on geographical tracking, multimedia processing, sensor network and RFID. While similarity search is...
Jia Xu, Zhenjie Zhang, Anthony K. H. Tung, Ge Yu
ICDM
2005
IEEE
165views Data Mining» more  ICDM 2005»
15 years 3 months ago
A Bernoulli Relational Model for Nonlinear Embedding
The notion of relations is extremely important in mathematics. In this paper, we use relations to describe the embedding problem and propose a novel stochastic relational model fo...
Gang Wang, Hui Zhang, Zhihua Zhang, Frederick H. L...