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EMNLP
2010
13 years 6 months ago
Efficient Graph-Based Semi-Supervised Learning of Structured Tagging Models
We describe a new scalable algorithm for semi-supervised training of conditional random fields (CRF) and its application to partof-speech (POS) tagging. The algorithm uses a simil...
Amarnag Subramanya, Slav Petrov, Fernando Pereira
ICML
2010
IEEE
13 years 9 months ago
Learning Markov Logic Networks Using Structural Motifs
Markov logic networks (MLNs) use firstorder formulas to define features of Markov networks. Current MLN structure learners can only learn short clauses (4-5 literals) due to extre...
Stanley Kok, Pedro Domingos
NIPS
2007
13 years 9 months ago
A Randomized Algorithm for Large Scale Support Vector Learning
This paper investigates the application of randomized algorithms for large scale SVM learning. The key contribution of the paper is to show that, by using ideas random projections...
Krishnan Kumar, Chiru Bhattacharyya, Ramesh Hariha...
SIGCSE
1997
ACM
121views Education» more  SIGCSE 1997»
14 years 18 days ago
Application-based modules using apprentice learning for CS 2
A typical Data Structures (CS 2) course covers a wide variety of topics: elementary algorithm analysis; data structures including dynamic structures, trees, tables, graphs, etc.; ...
Owen L. Astrachan, Robert F. Smith, James T. Wilke...
SIGCSE
1996
ACM
163views Education» more  SIGCSE 1996»
14 years 17 days ago
Database theory in practice: learning from cooperative group projects
lhis paper describes the use of cooperative group learning concepts in support of an undergraduate database mrtnagement course that emphasizes the theoretical and practical aspect...
Suzanne W. Dietrich, Susan Darling Urban