Uncertainty accompanies our life processes and covers almost all fields of scientific studies.
Two general categories of uncertainty, namely, aleatory uncertainty and epistemic …

We present two new neighbor query algorithms, including range query (RNN) and nearest
neighbor (NN) query, based on revised kd tree by using two techniques. The first technique …

Machine learning (ML) applications have been thriving recently, largely attributed to the
increasing availability of data. However, inconsistency and incomplete information are …

We study the convex-hull problem in a probabilistic setting, motivated by the need to handle
data uncertainty inherent in many applications, including sensor databases, location-based …

In this study, we discover that the data skewness problem imposes adverse impacts on
MapReduce-based parallel kNN-join operations running clusters. We propose a data …

Solving geometric optimization problems over uncertain data has become increasingly
important in many applications and has attracted a lot of attentions in recent years. In this …

In Voronoi-based nearest neighbor search, the Voronoi cell of every point p in a database
can be used to check whether p is the closest to some query point q. We extend the notion of …

Problems on uncertain data have attracted significant attention due to the imprecise nature
of many measurement data. In this paper, we consider the k-center problem on one …

Local feature matching is a part of many large vision tasks. Local feature matching usually
consists of three parts: feature detection, description, and matching. The matching task …

Let P be a set of n uncertain points in R d, where each point pi∈ P is associated with a real
value vi and exists with probability α i∈(0, 1] independently of the other points. We present …