INFORMATION THEORETIC CLUSTERING FOR UNSUPERVISED DOMAIN-ADAPTATION
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We propose a simple information-theoretic clustering approach based on maximizing the mutual information I(\sfx,y) between the unknown cluster labels y and the training patterns \sfx with respect to parameters of specifically constrained encoding dis ...
Audio segmentation, in general, is the task of segmenting a continuous audio stream in terms of acoustically homogenous regions, where the rule of homogeneity depends on the task. This thesis aims at developing and investigating efficient, robust and unsup ...
Audio segmentation, in general, is the task of segmenting a continuous audio stream in terms of acoustically homogenous regions, where the rule of homogeneity depends on the task. This thesis aims at developing and investigating efficient, robust and unsup ...
Audio segmentation, in general, is the task of segmenting a continuous audio stream in terms of acoustically homogenous regions, where the rule of homogeneity depends on the task. This thesis aims at developing and investigating efficient, robust and unsup ...
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This work presents document clustering experiments performed over noisy texts (i.e. text that have been extracted through an automatic process like speech or character recognition). The effect of recognition errors on different clustering techniques is mea ...
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We try to analyze a generic model for 2-tier distributed systems, exploring the possibility of optimal cluster sizes from an information management perspective, such that the overall cost for updating and searching information may be minimized by adopting ...
This paper presents clustering experiments performed over noisy texts (i.e. texts that have been extracted through an automatic process like character or speech recognition). The effect of recognition errors is investigated by comparing clustering results ...