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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...
This paper addresses the task of finding acronym-definition pairs in text. Most of the previous work on the topic is about systems that involve manually generated rules or regular expressions. In this...
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...
Machine learning has facilitated many recent advances in natural language processing and information extraction. Unfortunately, most machine learning methods rely on costly labeled data, which impedes...
Machine face recognition has traditionally been studied under the assumption of a carefully controlled image acquisition process. By controlling image acquisition, variation due to factors such as pos...
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...
Collective classification models attempt to improve classification performance by taking into account the class labels of related instances. However, they tend not to learn patterns of interactions be...
Most feature selection methods for object tracking assume that the labeled samples obtained in the next framesfollow the similar distribution with the samples in the previous frame. However, this assu...
In the privacy preservation of association rules, sensitivity analysis should be reported after the quantification of items in terms of their occurrence. The traditional methodologies, used for preser...
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...
In this work, we present a novel method to detect violent shots in movies. The detection process is split into two views–––the audio and video views. From the audio-view, a weakly-supervised method is...
Linear Discriminant Analysis (LDA) is a popular method for dimensionality reduction and classification. In real-world applications when there is no sufficient labeled data, LDA suffers fro...
清华大学模式识别基础课件 Summary on Supervised Pattern Recognition Methods。
Vision-based homecare system receives increasing research interest owing to its efficiency, portability and low-cost characters. This paper presents a vision-based semi-supervised homecare system to a...
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...

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