Graph Theory and Algorithms

Artificial intelligence, and in particular machine learning, is a fast-emerging field. Research on artificial intelligence focuses mainly on image-, text- and voice-based applications, leading to breakthrough developments in self-driving cars, voice recognition algorithms and recommendation systems. In this article, w…

• İMDAT AS

This paper describes a novel solution to the rigid point pattern matching problem in Euclidean spaces of any dimension. Although we assume rigid motion, jitter is allowed. We present a noniterative, polynomial time algorithm that is guaranteed to find an optimal solution for the noiseless case. First, we model point p…

• DANTE AUGUSTO COUTO BARONE

Specialized hardware accelerators can significantly improve the performance and power efficiency of compute systems. In this paper, we focus on hardware accelerators for graph analytics applications and propose a configurable architecture template that is specifically optimized for iterative vertex-centric graph appli…

Specialized hardware accelerators can significantly improve the performance and power efficiency of compute systems. In this paper, we focus on hardware accelerators for graph analytics applications and propose a configurable architecture template that is specifically optimized for iterative vertex-centric graph appli…

Cancer causes deviations in the distribution of cells, leading to changes in biological structures that they form. Correct localization and characterization of these structures are crucial for accurate cancer diagnosis and grading. In this paper, we introduce an effective hybrid model that employs both structural and…

• ÇİĞDEM GÜNDÜZ DEMİR

Large-scale training is important to ensure high performance and accuracy of machine-learning models. At Facebook we use many different models, including computer vision, video and language models. However, in this paper we focus on the deep learning recommendation models (DLRMs), which are responsible for more than 5…

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• KAMER KAYA

In graph theory, k-core is a key metric used to identify subgraphs of high cohesion, also known as the `dense' regions of a graph. As the real world graphs such as social network graphs grow in size, the contents get richer and the topologies change dynamically, we are challenged not only to materialize k-core subgrap…

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• MÜCAHİT SOYLU

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• RESUL DAŞ

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• İBRAHİM AYKUT ERDEM