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AUSAI
2008
Springer
14 years 11 months ago
Learning Object Representations Using Sequential Patterns
This paper explores the use of alternating sequential patterns of local features and saccading actions to learn robust and compact object representations. The temporal encoding rep...
Nobuyuki Morioka
AAAI
1997
14 years 11 months ago
Worst-Case Absolute Loss Bounds for Linear Learning Algorithms
The absolute loss is the absolute difference between the desired and predicted outcome. I demonstrateworst-case upper bounds on the absolute loss for the perceptron algorithm and ...
Tom Bylander
KES
2006
Springer
14 years 9 months ago
A Divergent-Style Learning Support Tool for English Learners Using a Thesaurus Diagram
This paper proposes an English learning support tool which provides users with divergent information to find the right words and expressions. In contrast to a number of software to...
Chie Shimodaira, Hiroshi Shimodaira, Susumu Kunifu...
RIA
2006
84views more  RIA 2006»
14 years 9 months ago
Learning Recursive Automata from Positive Examples
In this theoretical paper, we compare the "classical" learning techniques used to infer regular grammars from positive examples with the ones used to infer categorial gra...
Isabelle Tellier
ICDAR
2005
IEEE
15 years 3 months ago
Learning Diagram Parts with Hidden Random Fields
Many diagrams contain compound objects composed of parts. We propose a recognition framework that learns parts in an unsupervised way, and requires training labels only for compou...
Martin Szummer