This paper presents a system for protecting the privacy of specific individuals in video recordings. We address the following two problems: automatic people identification with limited labeled data, and human body obscuring with preserved structure and motion information. In order to address the first problem, we propose a new discriminative learning algorithm to improve people identification a...

This paper describes a simple method to achieve logical constraints on words for topic models based on a recently developed topic modeling framework with Dirichlet forest priors (LDA-DF). Logical constraints mean logical expressions of pairwise constraints, Must-links and Cannot-Links, used in the literature of constrained clustering. Our method can not only cover the original constraints of th...

Non-negative Matrix Factorisation (NMF) has been extensively used in machine learning and data analytics applications. Most existing variations of NMF only consider how each row/column vector of factorised matrices should be shaped, and ignore the relationship among pairwise rows or columns. In many cases, such pairwise relationship enables better factorisation, for example, image clustering an...

We present an improved method for clustering in the presence of very limited supervisory information, given as pairwise instance constraints. By allowing instance-level constraints to have spacelevel inductive implications, we are able to successfully incorporate constraints for a wide range of data set types. Our method greatly improves on the previously studied constrained -means algorithm, g...

As proteins evolve, amino acid positions key to protein structure or function are subject to mutational constraints. These positions can be detected by analyzing sequence families for amino acid conservation or for coevolution between pairs of positions. Coevolutionary scores are usually rank-ordered and thresholded to reveal the top pairwise scores, but they also can be treated as weighted net...

Semi-supervised or constrained graph clustering incorporates prior information in order to improve results. Pairwise constraints are often utilized guide the process. This work addresses a problem biological networks where (1) subgraph connectivity strictly required be satisfied and (2) quality is assessed with respect pairwise constraint violations. Existing methods fail fully satisfy constrai...

An essential requirement for providing secure services in wireless sensor networks is the ability to establish pairwise keys among sensors. Due to resource constraints on the sensors, the key establishment scheme should not create significant overhead. To date, several key establishment schemes have been proposed. Some of these have appropriate connectivity and resistance against key exposure, ...

The purpose of this paper is to introduce the concept of pairwise F-closedness in bitopological spaces. This space contains both of pairwise strongcompactness and pairwise S-closedness and contained in pairwise quasi H-closedness. The characteristics and relationships concerning this new class of spaces with other corresponding types are established. Moreover, several of its basic and important...

Community detection is an important tasks across a number of research fields including social science, biology, and physics. In the real world, topology information alone is often inadequate to accurately find out community structure due to its sparsity and noise. The potential useful prior information such as pairwise constraints which contain must-link and cannot-link constraints can be obtai...