Abhinav Vishnu
Biography
I am a Principal Member of Technical Staff at AMD Research.
My research intrests are in designing scalable, fault tolerant and energy efficient Machine Learning and Data Mining (MLDM) algorithms. A few examples include Deep Learning algorithms (with Keras, TensorFlow and Caffe), Support Vector Machines (SVM), Frequent Pattern Mining (FP-Growth) and several others such as K-Nearest Neighbors (k-NN), k-means using MPI and PGAS models, such as Global Arrays. The MLDM research is integrated in Machine Learning Toolkit for Extreme Scale (MaTEx). I am also interested in applications of Machine Learning including fault, performance modeling and domain sciences.
My research intrests are in designing scalable, fault tolerant and energy efficient Machine Learning and Data Mining (MLDM) algorithms. A few examples include Deep Learning algorithms (with Keras, TensorFlow and Caffe), Support Vector Machines (SVM), Frequent Pattern Mining (FP-Growth) and several others such as K-Nearest Neighbors (k-NN), k-means using MPI and PGAS models, such as Global Arrays. The MLDM research is integrated in Machine Learning Toolkit for Extreme Scale (MaTEx). I am also interested in applications of Machine Learning including fault, performance modeling and domain sciences.
Presentations
Workshop
Online Only
Machine Learning and Artificial Intelligence
W