Approximation algorithms for Kernel Methods on Multi-core CPUs and GPUs
We are exploring the opportunities of utilizing new architectures such as GPUs, multi-core processors, and distributed clusters (cloud computing) to efficiently solve research problems related to multimedia content analysis, large-scale data analysis, and machine learning techniques.
People
- Mohamed Hefeeda (Assistant Professor)
- Wael Abd-Almageed (Assistant Research Scientist at UMD)
- Fei Gao (MSc Student)
- Taher Dameh (MSc Student)
References and Links
- M. Hussein and W. Abd-Almageed, Efficient Band Approximation of Gram Matrices for Large Scale Kernel Methods on GPUs, In Proc. of the International Conference for High Performance Computing, Networking, Storage, and Analysis (SuperComputing'09), Portland, OR, November 2009.
