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CVPR
2008
IEEE
16 years 8 months ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona
CORR
2008
Springer
107views Education» more  CORR 2008»
15 years 6 months ago
A Spectral Algorithm for Learning Hidden Markov Models
Hidden Markov Models (HMMs) are one of the most fundamental and widely used statistical tools for modeling discrete time series. In general, learning HMMs from data is computation...
Daniel Hsu, Sham M. Kakade, Tong Zhang
ETS
2006
IEEE
114views Hardware» more  ETS 2006»
15 years 6 months ago
From Research Resources to Learning Objects: Process Model and Virtualization Experiences
Typically, most research and academic institutions own and archive a great amount of objects and research related resources that have been produced, used and maintained over long ...
José Luis Sierra, Alfredo Fernández-...
179
Voted
IAT
2010
IEEE
15 years 4 months ago
A Biologically-Inspired Cognitive Agent Model Integrating Declarative Knowledge and Reinforcement Learning
Abstract--The paper proposes a biologically-inspired cognitive agent model, known as FALCON-X, based on an integration of the Adaptive Control of Thought (ACT-R) architecture and a...
Ah-Hwee Tan, Gee Wah Ng
ICDAR
2009
IEEE
16 years 1 months ago
Statistical Modeling and Learning for Recognition-Based Handwritten Numeral String Segmentation
This paper proposes a recognition based approach to handwritten numeral string segmentation. We consider two classes: numeral strings segmented correctly or not. The feature vecto...
Yanjie Wang, Xiabi Liu, Yunde Jia