We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
We present BL-WoLF, a framework for learnability in repeated zero-sum games where the cost of learning is measured by the losses the learning agent accrues (rather than the number...
Several important time series data mining problems reduce to the core task of finding approximately repeated subsequences in a longer time series. In an earlier work, we formalize...
Bill Yuan-chi Chiu, Eamonn J. Keogh, Stefano Lonar...
Many algorithms have been proposed to approximate holistic aggregates, such as quantiles and heavy hitters, over data streams. However, little work has been done to explore what t...
Graham Cormode, Theodore Johnson, Flip Korn, S. Mu...
In many decision-making applications, the skyline query is frequently used to find a set of dominating data points (called skyline points) in a multidimensional dataset. In a high-...
Chee Yong Chan, H. V. Jagadish, Kian-Lee Tan, Anth...