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ACL
2010
13 years 6 months ago
Distributional Similarity vs. PU Learning for Entity Set Expansion
Distributional similarity is a classic technique for entity set expansion, where the system is given a set of seed entities of a particular class, and is asked to expand the set u...
Xiaoli Li, Lei Zhang, Bing Liu, See-Kiong Ng
TSMC
1998
99views more  TSMC 1998»
13 years 8 months ago
Learning visually guided grasping: a test case in sensorimotor learning
Abstract—We present a general scheme for learning sensorimotor tasks which allows rapid on-line learning and generalization of the learned knowledge to unfamiliar objects. The sc...
Ishay Kamon, Tamar Flash, Shimon Edelman
HAIS
2009
Springer
14 years 10 days ago
Beyond Homemade Artificial Data Sets
One of the most important challenges in supervised learning is how to evaluate the quality of the models evolved by different machine learning techniques. Up to now, we have relied...
Núria Macià, Albert Orriols-Puig, Es...
COLT
2004
Springer
14 years 1 months ago
Regularization and Semi-supervised Learning on Large Graphs
We consider the problem of labeling a partially labeled graph. This setting may arise in a number of situations from survey sampling to information retrieval to pattern recognition...
Mikhail Belkin, Irina Matveeva, Partha Niyogi
COMCOM
1999
124views more  COMCOM 1999»
13 years 8 months ago
Minimizing the Cost of Fault Location when Testing from a Finite State Machine
If a test does not produce the expected output, the incorrect output may have been caused by an earlier state transfer failure. Ghedamsi and von Bochmann [1992] and Ghedamsi et al...
Robert M. Hierons