In various applications such as data cleansing, being able to retrieve categorical or numerical attributes based on notions of approximate match (e.g., edit distance, numerical di...
Liang Jin, Nick Koudas, Chen Li, Anthony K. H. Tun...
—The strategies for mining frequent itemsets, which is the essential part of discovering association rules, have been widely studied over the last decade. In real-world datasets,...
Obtaining fast and good quality approximations to data distributions is a problem of central interest to database management. A variety of popular database applications including,...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
The paper studies the computational complexity and approximation algorithms for a new evolutionary distance between multi-chromosomal genomes introduced recently by Ferretti, Nade...
Bhaskar DasGupta, Tao Jiang, Sampath Kannan, Ming ...