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Moving destination prediction offers an important category of location-based applications and provides essential intelligence to business and governments. In existing studies, a common approach to destination prediction is to match the given query trajectory with massive recorded trajectories by...
We present and analyze a simple, two-step algorithm to approximate the optimal solution of the sparse PCA problem. In the proposed approach, we first solve an 1-penalized version of the NP-hard sparse PCA optimization problem and then we use a randomized rounding strategy to sparsify the...
All pairs similarity search (APSS) is used in many web search and data mining applications. Previous work has used techniques such as comparison filtering, inverted indexing, and parallel accumulation of partial results. However, shuffling intermediate results can incur significant communication...
With the ever increasing volume of geo-referenced datasets, there is a real need for better statistical estimation and prediction techniques for spatial analysis. Most existing approaches focus on predicting multivariate Gaussian spatial processes, but as the data may consist of non-Gaussian (or...
Matrix factorization is often used for data representation in many data mining and machine-learning problems. In particular, for a dataset without any negative entries, nonnegative matrix factorization (NMF) is often used to find a low-rank approximation by the product of two nonnegative...
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