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ICML
2010
IEEE
15 years 4 months ago
Deep networks for robust visual recognition
Deep Belief Networks (DBNs) are hierarchical generative models which have been used successfully to model high dimensional visual data. However, they are not robust to common vari...
Yichuan Tang, Chris Eliasmith
110
Voted
JAIR
2006
108views more  JAIR 2006»
15 years 3 months ago
Preference-based Search using Example-Critiquing with Suggestions
We consider interactive tools that help users search for their most preferred item in a large collection of options. In particular, we examine example-critiquing, a technique for ...
Paolo Viappiani, Boi Faltings, Pearl Pu
JCSS
2007
116views more  JCSS 2007»
15 years 3 months ago
The most probable annotation problem in HMMs and its application to bioinformatics
Hidden Markov models (HMMs) are often used for biological sequence annotation. Each sequence feature is represented by a collection of states with the same label. In annotating a ...
Brona Brejová, Daniel G. Brown 0001, Tom&aa...
ICDAR
2009
IEEE
15 years 1 months ago
HMM-Based Online Recognition of Handwritten Chemical Symbols
In this paper, we present an online handwritten recognition method for Chemical Symbols, a widely used symbol in education and academic interactions. This method is based on Hidde...
Yang Zhang, Guangshun Shi, Jufeng Yang
CORR
2010
Springer
136views Education» more  CORR 2010»
15 years 23 days ago
The Highest Expected Reward Decoding for HMMs with Application to Recombination Detection
Abstract. Hidden Markov models are traditionally decoded by the Viterbi algorithm which finds the highest probability state path in the model. In recent years, several limitations ...
Michal Nánási, Tomás Vinar, B...