With the growing interest in the use of internet of things (IoT), machine-to-machine (M2M) communications have become an important networking paradig…

We consider the Minimum Dominating Set (MDS) problem on the intersection graphs of geometric objects. Even for simple and widely-used geometric objec…

Attention is an operation that selects some largest element from some set, where the notion of largest is defined elsewhere. Applying this operation …

Given a set of $n$ points (sites) inside a rectangle $R$ and $n$ points (label locations or ports) on its boundary, a boundary labeling problem seeks…

Automated builds are integral to the Continuous Integration (CI) software development practice. In CI, developers are encouraged to integrate early a…

Software for mixed-integer linear programming can return incorrect results for a number of reasons, one being the use of inexact floating-point arith…

In this paper we propose a novel dual adversarial co-learning approach for multi-domain text classification (MDTC). The approach learns shared-privat…

Federated learning is a communication-efficient training process that alternates between local training at the edge devices and averaging the updated…

Wireless network virtualization and information-centric networking (ICN) are two promising technologies for next generation wireless networks. Althou…

Let $P$ be a set of $n$ colored points in the plane. Introduced by Hart (1968), a consistent subset of $P$, is a set $S\subseteq P$ such that for eve…

Future networks are expected to connect an enormous number of nodes wirelessly using wide-band transmission. This brings great challenges. To avoid c…

In this work, we extend and analyze the nonperturbative Maxwell-Schr\"odinger-Plasma (MASP) model. This model was proposed to describe the high order…

In cognitive radio (CR) networks, the perceived reduction of application layer quality of service (QoS), such as multimedia distortion, by secondary …

Despite the advancement of supervised image recognition algorithms, their de- pendence on the availability of labeled data and the rapid expansion of…

Artifical Neural Networks are a particular class of learning systems modeled after biological neural functions with an interesting penchant for Hebbi…

We study the problem of placing a set $T$ of broadcast towers in a simple polygon $P$ in order for any point to locate itself in the interior of $P$.…

A graph $G$ with $n$ vertices is called an outerstring graph if it has an intersection representation of a set of $n$ curves inside a disk such that …

Automatic question generation is an important problem in natural language processing. In this paper we propose a novel adaptive copying recurrent neu…

This article addresses the residential energy cost optimization problem in smart grid. To date, most of the previous research only consider a partial…

Despite the breakthroughs achieved by deep learning models in conventional supervised learning scenarios, their dependence on sufficient labeled trai…

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