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  • S. Akaho
  • 2004
We propose a method for extracting a low dimensional structure from a set of parameters of probability distributions. By an information geometrical interpretation, we show that there exist two kinds of possible flat structures for fitting (e-PCA and m-PCA). We derive alternating procedures to find the low dimensional structures. Each alternating procedure(More)
This paper describes an experiment where dialogue-based learning is applied to map acquisition of a mobile Oce-Conversant robot. The system learns the map of environment through simple dialogue with human teachers. A formal probabilistic model is introduced as a representation of map. The importance and the eectiveness of proper segmentation of(More)
We introduce a novel approach to analysis of human browsing behavior in electronic spaces, and present an efficient recommender system that helps users increase browsing efficiency by providing suggestions on potentially desired targets of their interactions. Analysis of knowledge worker browsing behavior on a large corporate intranet revealed that users(More)
Learning from cluster examples is a composite task of two common classification tasks: learning from examples and clustering. Learning from cluster examples involves an attempt to acquire a rule that can be used to partition an unseen object set from a given example set. Having an established method for a task is useful in situations where, though an(More)
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