In this paper we propose a Bayesian model for multi-task feature selection. This model is based on a generalized spike and slab sparse prior distribution that enforces the selectio...
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
Efficient one-pass computation of F0, the number of distinct elements in a data stream, is a fundamental problem arising in various contexts in databases and networking. We consid...
Minimum-entropy decoding is a universal decoding algorithm used in decoding block compression of discrete memoryless sources as well as block transmission of information across di...
A monotone distribution P over a (partially) ordered domain assigns higher probability to y than to x if y x in the order. We study several natural problems concerning testing pr...