22 citations · 32 across the 4 of their papers we have counts for
4 papers
On the Robustness of Randomized Ensembles to Adversarial Perturbations
Hassan Dbouk, Naresh R. Shanbhag
Randomized ensemble classifiers (RECs), where one classifier is randomly selected during inference, have emerged as an attractive alternative to traditional ensembling methods for…
Energy-efficient Machine Learning in Silicon: A Communications-inspired Approach
Naresh R. Shanbhag
This position paper advocates a communications-inspired approach to the design of machine learning systems on energy-constrained embedded `always-on' platforms. The communications-…
A 481pJ/decision 3.4M decision/s Multifunctional Deep In-memory Inference Processor using Standard 6T SRAM Array
Mingu Kang, Sujan Gonugondla, Ameya Patil +1
This paper describes a multi-functional deep in-memory processor for inference applications. Deep in-memory processing is achieved by embedding pitch-matched low-SNR analog process…
Error-Resilient Machine Learning in Near Threshold Voltage via Classifier Ensemble
Sai Zhang, Naresh Shanbhag
In this paper, we present the design of error-resilient machine learning architectures by employing a distributed machine learning framework referred to as classifier ensemble (CE)…