Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
Estimating the selectivity of multidimensional range queries over real valued attributes has significant applications in data exploration and database query optimization. In this p...
Dimitrios Gunopulos, George Kollios, Vassilis J. T...
We present a points-to analysis technique suitable for environments with small time and memory budgets, such as just-in-time (JIT) compilers and interactive development environmen...
Manu Sridharan, Denis Gopan, Lexin Shan, Rastislav...
A key problem in video content analysis using dynamic graphical models is to learn a suitable model structure given some observed visual data. We propose a Completed Likelihood AI...