Shrinkage-based exponential language models, such as the recently introduced Model M, have provided significant gains over a range of tasks [1]. Training such models requires a l...
Abhinav Sethy, Stanley F. Chen, Bhuvana Ramabhadra...
Mobile adaptive networks consist of a collection of nodes with learning and motion abilities that interact with each other locally in order to solve distributed processing and dis...
In this paper, we propose a distributed learning strategy in wireless sensor networks. Taking advantage of recent developments on kernel-based machine learning, we consider a new ...
In this work we present a parallel algorithm for the solution of a least squares problem with structured matrices. This problem arises in many applications mainly related to digit...
Pedro Alonso, Antonio M. Vidal, Alexey L. Lastovet...
This paper proposes a Bayesian algorithm to estimate the parameters of a smooth transition regression model. With in this model, time series are divided into segments and a linear...