Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
A learning problem might have several measures of complexity (e.g., norm and dimensionality) that affect the generalization error. What is the interaction between these complexiti...
We are inevitably moving into a realm where small and inexpensive wireless devices would be seamlessly embedded in the physical world and form a wireless sensor network in order t...
Antonios Deligiannakis, Yannis Kotidis, Nick Rouss...
In this paper, we study the number of measurements required to recover a sparse signal in M with L nonzero coefficients from compressed samples in the presence of noise. We conside...
A generalized concept of interference suppression is introduced for multiuser systems with a known memoryless transmit non-linearity, such as in the downlink amplifier of a satelli...