AIMS We investigated clinical characteristics and outcomes of patients with significant valvular disease (SVD) in the Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF) trial. METHODS AND RESULTS ROCKET AF excluded patients with mitral stenosis or artificial valve prostheses....

This paper develops an efficient online algorithm based on K-SVD for learning multiple consecutive tasks. We first derive a batch multi-task learning method that builds upon the K-SVD algorithm, and then extend the batch algorithm to train models online in a lifelong learning setting. The resulting method has lower computational complexity than other current lifelong learning algorithms while m...

Truncated Singular Value Decomposition (SVD) calculates the closest rank-k approximation of a given input matrix. Selecting the appropriate rank k defines a critical model order choice in most applications of SVD. To obtain a principled cut-off criterion for the spectrum, we convert the underlying optimization problem into a noisy channel coding problem. The optimal approximation capacity of th...

—In this work we propose a new deep learning tool – deep dictionary learning. Multi-level dictionaries are learnt in a greedy fashion – one layer at a time. This requires solving a simple (shallow) dictionary learning problem; the solution to this is well known. We apply the proposed technique on some benchmark deep learning datasets. We compare our results with other deep learning tools like s...

In this paper, we propose a quantum algorithm for recommendation systems which incorporates the contextual information of users to personalized recommendation. The preference is encoded in third-order tensor dimension N can be approximated by truncated singular value decomposition (t-svd) subsample tensor. Unlike classical that reconstructs using t-svd, our obtains recommended product under cer...

= ' blind sequence detection (BSD) aigorithm based on the innovations approach is proposed and its performance in a Rayleigh fading environment is evaluated. A cornparison between the innovations and Tong's Singular Value Decomposition (SVD) [25] based blind sequence detection algorithm is also presented. Further insight is gained on how blind sequence detectors behave by examining several para...