In this paper, we propose a fast and optimal solution for block motion estimation based on an adaptive multilevel successive elimination algorithm. This algorithm is accomplished b...
Motivated by experience gained during the validation of a recent Approximate Mean Value Analysis (AMVA) model of modern shared memory architectures, this paper re-examines the &qu...
Tuning SVM hyperparameters is an important step in achieving a high-performance learning machine. It is usually done by minimizing an estimate of generalization error based on the...
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...
The ratio of the largest eigenvalue divided by the trace of a p×p random Wishart matrix with n degrees of freedom and identity covariance matrix plays an important role in variou...