Feature selection, as a data preprocessing strategy, has been proven to be effective and
efficient in preparing data (especially high-dimensional data) for various data-mining and …

Wireless local area networks (WLANs) have become a promising choice for indoor
positioning as the only existing and established infrastructure, to localize the mobile and …

Abstract Multi-task learning (MTL), which optimizes multiple related learning tasks at the
same time, has been widely used in various applications, including natural language …

Recent studies on brain imaging analysis witnessed the core roles of machine learning
techniques in computer-assisted intervention for brain disease diagnosis. Of various …

We use convex relaxation techniques to provide a sequence of regularized low-rank
solutions for large-scale matrix completion problems. Using the nuclear norm as a …

Many machine learning and pattern classification methods have been applied to the
diagnosis of Alzheimer's disease (AD) and its prodromal stage, ie, mild cognitive impairment …

The fusion of complementary information contained in multi-modality data [eg, magnetic
resonance imaging (MRI), positron emission tomography (PET), and genetic data] has …

Spoofing with photograph or video is one of the most common manner to circumvent a face
recognition system. In this paper, we present a real-time and non-intrusive method to …

Non-convex sparsity-inducing penalties have recently received considerable attentions in
sparse learning. Recent theoretical investigations have demonstrated their superiority over …

Goal: Cataracts are a clouding of the lens and the leading cause of blindness worldwide.
Assessing the presence and severity of cataracts is essential for diagnosis and progression …