Dual-execution/checkpointing based transient error tolerance techniques have been widely used in the high-end mission critical systems. These techniques, however, are not very att...
Neighbor search is a fundamental task in machine learning, especially in classification and retrieval. Efficient nearest neighbor search methods have been widely studied, with the...
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Hierarchical topic taxonomies have proliferated on the World Wide Web [5, 18], and exploiting the output space decompositions they induce in automated classification systems is an...
We investigate the idea of finding semantically related search engine queries based on their temporal correlation; in other words, we infer that two queries are related if their p...