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» Automatic Ordering of Subgoals - A Machine Learning Approach
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142
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ML
1998
ACM
139views Machine Learning» more  ML 1998»
15 years 3 months ago
The Hierarchical Hidden Markov Model: Analysis and Applications
We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our m...
Shai Fine, Yoram Singer, Naftali Tishby
ECCV
2008
Springer
16 years 5 months ago
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...
128
Voted
NN
2006
Springer
114views Neural Networks» more  NN 2006»
15 years 3 months ago
Modular learning models in forecasting natural phenomena
Modular model is a particular type of committee machine and is comprised of a set of specialized (local) models each of which is responsible for a particular region of the input s...
Dimitri P. Solomatine, Michael Baskara L. A. Siek
120
Voted
DAS
2010
Springer
15 years 5 months ago
Overlapped text segmentation using Markov random field and aggregation
Separating machine printed text and handwriting from overlapping text is a challenging problem in the document analysis field and no reliable algorithms have been developed thus f...
Xujun Peng, Srirangaraj Setlur, Venu Govindaraju, ...
123
Voted
STOC
1993
ACM
117views Algorithms» more  STOC 1993»
15 years 7 months ago
Efficient noise-tolerant learning from statistical queries
In this paper, we study the problem of learning in the presence of classification noise in the probabilistic learning model of Valiant and its variants. In order to identify the cl...
Michael J. Kearns