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» Unsupervised Learning of Models for Recognition
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IJCAI
2001
14 years 11 months ago
Probabilistic Classification and Clustering in Relational Data
Supervised and unsupervised learning methods have traditionally focused on data consisting of independent instances of a single type. However, many real-world domains are best des...
Benjamin Taskar, Eran Segal, Daphne Koller
ICIP
2008
IEEE
15 years 11 months ago
A supervised nonlinear neighborhood embedding of color histogram for image indexing
Subspace learning techniques are widespread in pattern recognition research. They include PCA, ICA, LPP, etc. These techniques are generally linear and unsupervised. The problem o...
Xian-Hua Han, Yen-Wei Chen, Takeshi Sukegawa
ICASSP
2011
IEEE
14 years 1 months ago
An investigation of subspace modeling for phonetic and speaker variability in automatic speech recognition
This paper investigates the impact of subspace based techniques for acoustic modeling in automatic speech recognition (ASR). There are many well known approaches to subspace based...
Richard C. Rose, Shou-Chun Yin, Yun Tang
ICML
2005
IEEE
15 years 10 months ago
Robust one-class clustering using hybrid global and local search
Unsupervised learning methods often involve summarizing the data using a small number of parameters. In certain domains, only a small subset of the available data is relevant for ...
Gunjan Gupta, Joydeep Ghosh
DAGM
2008
Springer
14 years 11 months ago
Switching Linear Dynamic Models for Noise Robust In-Car Speech Recognition
Performance of speech recognition systems strongly degrades in the presence of background noise, like the driving noise in the interior of a car. We compare two different Kalman fi...
Björn Schuller, Martin Wöllmer, Tobias M...