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Learning Representations for Weakly Supervised Natural Language Processing Tasks
Natural Language word
2015/9/14
Finding the right representations for words is critical for building accurate NLP systems when
domain-specific labeled data for the task is scarce. This article investigates novel techniques fo...
How to Solve Classification and Regression Problems on High-Dimensional Data with a Supervised Extension of Slow Feature Analysis
Slow feature analysis feature extraction classifi cation regression pattern recognition training graphs nonlinear dimensionality reduction supervised learning high-dimensional data implicitly supervised image analysis
2015/7/10
Supervised learning from high-dimensional data, e.g., multimedia data, is a challenging task. We propose an extension of slow feature analysis (SFA) for supervised dimensionality reduction called grap...
Automating Crowd-supervised Learning for Spoken Language Systems
Automating Crowd-supervised Learning Spoken Language Systems
2014/11/27
Spoken language systems often rely on static speech recognizers. When the underlying models are improved on-the-fly,training is usually performed using unsupervised methods. In this work, we explore a...
Supervised Fuzzy Mixture of Local Feature Models
Adaptive Fuzzy Mixture Supervised Clustering Local Feature Model PCA ICA Phase Transition Fuzzy Parametric Clustering Real-Coded Genetic Algorithm
2013/1/28
This paper addresses an important issue in model combination, that is, model locality. Since usually a global linear model is unable to reflect nonlinearity and to characterize local features, especia...
清华大学模式识别基础课件 Summary on Supervised Pattern Recognition Methods
模式识别基础 课件 Supervised Pattern Recognition Methods
2009/5/4
清华大学模式识别基础课件 Summary on Supervised Pattern Recognition Methods。
A Supervised Text-Independent Speaker Recognition Approach
Text-independent speaker recognition mel cepstral analysis speech feature vector
2010/2/2
We provide a supervised speech-independent voice
recognition technique in this paper. In the feature extraction stage
we propose a mel-cepstral based approach. Our feature vector
classification met...