We consider the problem of large-scale retrieval evaluation, and we propose a statistical method for evaluating retrieval systems using incomplete judgments. Unlike existing techn...
Many recent works that study the performance of multi-input multi-output (MIMO) systems in practice assume a Kronecker model where the variances of the channel entries, upon decom...
Vasanthan Raghavan, Jayesh H. Kotecha, Akbar M. Sa...
Abstract--We consider the adaptive detection of a signal of interest embedded in colored noise, when the environment is nonhomogeneous, i.e., when the training samples used for ada...
The emerging theory of compressed sensing (CS) provides a universal signal detection approach for sparse signals at sub-Nyquist sampling rates. A small number of random projection...
Abstract. Most of the work in machine learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...