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AAAI
1998
14 years 13 hour ago
Learning to Classify Text from Labeled and Unlabeled Documents
In many important text classification problems, acquiring class labels for training documents is costly, while gathering large quantities of unlabeled data is cheap. This paper sh...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
KDD
2006
ACM
167views Data Mining» more  KDD 2006»
14 years 11 months ago
Clustering pair-wise dissimilarity data into partially ordered sets
Ontologies represent data relationships as hierarchies of possibly overlapping classes. Ontologies are closely related to clustering hierarchies, and in this article we explore th...
Jinze Liu, Qi Zhang, Wei Wang 0010, Leonard McMill...
HIPC
2009
Springer
13 years 8 months ago
Optimizing the use of GPU memory in applications with large data sets
Abstract--With General Purpose programmable GPUs becoming more and more popular, automated tools are needed to bridge the gap between achievable performance from highly parallel ar...
Nadathur Satish, Narayanan Sundaram, Kurt Keutzer
NAACL
2001
14 years 1 days ago
Applying Co-Training Methods to Statistical Parsing
We propose a novel Co-Training method for statistical parsing. The algorithm takes as input a small corpus (9695 sentences) annotated with parse trees, a dictionary of possible le...
Anoop Sarkar
ECCV
2010
Springer
14 years 1 months ago
Learning Shape Segmentation Using Constrained Spectral Clustering and Probabilistic Label Transfer
We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...