Boosting Graph Embedding on a Single GPU

1 code implementation • 19 Oct 2021 • Amro Alabsi Aljundi, Taha Atahan Akyildiz, Kamer Kaya

GOSH employs a novel graph coarsening algorithm to enhance the impact of updates and minimize the work for embedding.

Graph Embedding Link Prediction +1

Streaming Hypergraph Partitioning Algorithms on Limited Memory Environments

no code implementations • 9 Mar 2021 • Fatih Taşyaran, Berkay Demireller, Kamer Kaya, Bora Uçar

For many of today's data-centric applications, this data is streaming; new items arrive continuously, and the data grows with time.

Edge-computing hypergraph partitioning Data Structures and Algorithms Distributed, Parallel, and Cluster Computing 68W27, 68P05 E.1

Understanding Coarsening for Embedding Large-Scale Graphs

1 code implementation • 10 Sep 2020 • Taha Atahan Akyildiz, Amro Alabsi Aljundi, Kamer Kaya

Many approaches have been proposed in the literature to improve the performance of graph embedding, e. g., using distributed algorithms, accelerators, and pre-processing techniques.

Anomaly Detection Graph Embedding +2

HAMSI: A Parallel Incremental Optimization Algorithm Using Quadratic Approximations for Solving Partially Separable Problems

no code implementations • 5 Sep 2015 • Kamer Kaya, Figen Öztoprak, Ş. İlker Birbil, A. Taylan Cemgil, Umut Şimşekli, Nurdan Kuru, Hazal Koptagel, M. Kaan Öztürk

We propose HAMSI (Hessian Approximated Multiple Subsets Iteration), which is a provably convergent, second order incremental algorithm for solving large-scale partially separable optimization problems.