Device-to-Device (D2D) has been a potential technology to improve the sum-rate of cellular networks, especially in local communication. By reusing the resource of cellular user equipment (UE), D2D can enhance the spectrum efficiency, but at the cost of introducing extra co-channel interference. In this paper, we adopt a resource reusing mechanism in which multiple D2D pairs can share multiple r...

Media-streaming applications require smooth patterns of data transmission and also benefit from efficient resource utilization. System-wise, the underlying congestion control mechanism should achieve fairness and maintain TCP-friendliness. In this context, we optimize Additive Increase Multiplicative Decrease (AIMD) congestion control for multimedia applications, within the framework of bandwid...

Spectral clustering and path-based clustering are two recently developed clustering approaches that have delivered impressive results in a number of challenging clustering tasks. However, they are not robust enough against noise and outliers in the data. In this paper, based on M-estimation from robust statistics, we develop a robust path-based spectral clustering method by defining a robust pa...

We present a simple and scalable graph clustering method called power iteration clustering (PIC). PIC finds a very low-dimensional embedding of a dataset using truncated power iteration on a normalized pair-wise similarity matrix of the data. This embedding turns out to be an effective cluster indicator, consistently outperforming widely used spectral methods such as NCut on real datasets. PIC ...

We review the physical and cosmological consequences of two possible electromagnetic couplings to the dark sector: (i) a neutral lightest dark-matter particle (LDP) with nonzero electric and/or magnetic dipole moments and (ii) a charged next-to-lightest dark-matter particle (NLDP) which decays to a neutral LDP. For scenario (i) we find that a relatively light particle with mass between a few Me...

This paper presents a novel algorithm which generates three-dimensional face point trajectories for a given speech le with or without its text. The proposed algorithm rst employs an o -line training phase. In this phase, recorded face point trajectories along with their speech data and phonetic labels are used to generate phonetic codebooks. These codebooks consist of both acoustic and visual f...

This work focuses on the active selection of pairwise constraints for spectral clustering. We develop and analyze a technique for Active Constrained Clustering by Examining Spectral eigenvectorS (ACCESS) derived from a similarity matrix. The ACCESS method uses an analysis based on the theoretical properties of spectral decomposition to identify data items that are likely to be located on the bo...

Spectral clustering is a modern and wellknown method for performing data cluster-ing. However, it depends on the availabilityof a similarity matrix, which in many appli-cations can be non-trivial to obtain. In thispaper, we focus on the problem of perform-ing spectral clustering under a budget con-straint, where there is a limit on the numberof entries which can ...