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ECML
2007
Springer
15 years 3 months ago
Learning to Classify Documents with Only a Small Positive Training Set
Many real-world classification applications fall into the class of positive and unlabeled (PU) learning problems. In many such applications, not only could the negative training ex...
Xiaoli Li, Bing Liu, See-Kiong Ng
ESA
2010
Springer
220views Algorithms» more  ESA 2010»
14 years 10 months ago
Data Structures for Storing Small Sets in the Bitprobe Model
abstract appeared in Proc. 24th Annual Symposium of Computational Geometry (SoCG), 2008, pp. 338-345. S. Shannigrahi and S. P. Pal, "Efficient Prufer-like Coding and Counting ...
Jaikumar Radhakrishnan, Smit Shah 0001, Saswata Sh...
ISCA
1993
IEEE
112views Hardware» more  ISCA 1993»
15 years 1 months ago
Working Sets, Cache Sizes, and Node Granularity Issues for Large-Scale Multiprocessors
The distribution of resources among processors, memory and caches is a crucial question faced by designers of large-scale parallel machines. If a machine is to solve problems with...
Edward Rothberg, Jaswinder Pal Singh, Anoop Gupta
ICALP
2005
Springer
15 years 3 months ago
Noisy Turing Machines
Abstract. Turing machines exposed to a small stochastic noise are considered. An exact characterisation of their (≈ Π0 2 ) computational power (as noise level tends to 0) is obt...
Eugene Asarin, Pieter Collins
88
Voted
COLING
1990
14 years 10 months ago
Word Sense Disambiguation with Very Large Neural Networks Extracted from Machine Readable Dictionaries
In this paper, we describe a means for automatically building very large neural networks (VLNNs) from definition texts in machine-readable dictionaries, and demonstrate the use of...
Jean Véronis, Nancy Ide