We consider the problem of computing all-pair correlations in a warehouse containing a large number (e.g., tens of thousands) of time-series (or, signals). The problem arises in a...
Subspace clustering has attracted great attention due to its capability of finding salient patterns in high dimensional data. Order preserving subspace clusters have been proven to...
Discovering a representative set of theme patterns from a large amount of text for interpreting their meaning has always been concerned by researches of both data mining and inform...
Yongxin Tong, Shilong Ma, Dan Yu, Yuanyuan Zhang, ...
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Abstract. A compressed full-text self-index for a text T is a data structure requiring reduced space and able of searching for patterns P in T. Furthermore, the structure can repro...