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BMVC
2000
15 years 9 months ago
Quantifying Ambiguities in Inferring Vector-Based 3D Models
This paper presents a framework for directly addressing issues arising from self-occlusions and ambiguities due to the lack of depth information in vector-based representations. V...
Eng-Jon Ong, Shaogang Gong
NIPS
1998
15 years 9 months ago
Learning from Dyadic Data
Dyadic data refers to a domain with two nite sets of objects in which observations are made for dyads, i.e., pairs with one element from either set. This type of data arises natur...
Thomas Hofmann, Jan Puzicha, Michael I. Jordan
CASCON
1996
123views Education» more  CASCON 1996»
15 years 8 months ago
Views on template-based parallel programming
For almost a decade we have been working at developing and using template-based models for coarse-grained parallel computing. Our initial system, FrameWorks, was positively receiv...
Ajit Singh, Jonathan Schaeffer, Duane Szafron
NIPS
1994
15 years 8 months ago
Active Learning with Statistical Models
For many types of machine learning algorithms, one can compute the statistically optimal" way to select training data. In this paper, we review how optimal data selection tec...
David A. Cohn, Zoubin Ghahramani, Michael I. Jorda...
ACL
1989
15 years 8 months ago
Automatic Acquisition of the Lexical Semantics of Verbs from Sentence Frames
This paper presents a computational model ofverb acquisitionwhich uses what we willcallthe principle of structured overeommitment to eliminate the need for negative evidence. The ...
Mort Webster, Mitchell P. Marcus