We propose a unified manifold learning framework for semi-supervised and unsupervised dimension reduction by employing a simple but effective linear regression function to map the ...
Feiping Nie, Dong Xu, Ivor Wai-Hung Tsang, Changsh...
Abstract. This paper concerns second-order analysis for a remarkable class of variational systems in finite-dimensional and infinite-dimensional spaces, which is particularly imp...
Abstract. We study the problem of learning partitions using equivalence constraints as input. This is a binary classification problem in the product space of pairs of datapoints. ...
Monitoring global states of an application deployed over distributed nodes becomes prevalent in today's datacenters. State monitoring requires not only correct monitoring resu...
Abstract. The building behaviour of termites has previously been modelled mathematically in two dimensions. However, physical and logistic constraints were not taken into account i...