50 citations · 389 across the 39 of their papers we have counts for
6 papers · 1 filter
Robot Design With Neural Networks, MILP Solvers and Active Learning
Sanjai Narain, Emily Mak, Dana Chee +6
Central to the design of many robot systems and their controllers is solving a constrained blackbox optimization problem. This paper presents CNMA, a new method of solving this pro…
TUTOR: Training Neural Networks Using Decision Rules as Model Priors
Shayan Hassantabar, Prerit Terway, Niraj K. Jha
The human brain has the ability to carry out new tasks with limited experience. It utilizes prior learning experiences to adapt the solution strategy to new domains. On the other h…
DISPATCH: Design Space Exploration of Cyber-Physical Systems
Prerit Terway, Kenza Hamidouche, Niraj K. Jha
Design of cyber-physical systems (CPSs) is a challenging task that involves searching over a large search space of various CPS configurations and possible values of components comp…
Fully Dynamic Inference with Deep Neural Networks
Wenhan Xia, Hongxu Yin, Xiaoliang Dai +1
Modern deep neural networks are powerful and widely applicable models that extract task-relevant information through multi-level abstraction. Their cross-domain success, however, i…
CovidDeep: SARS-CoV-2/COVID-19 Test Based on Wearable Medical Sensors and Efficient Neural Networks
Shayan Hassantabar, Novati Stefano, Vishweshwar Ghanakota +6
The novel coronavirus (SARS-CoV-2) has led to a pandemic. The current testing regime based on Reverse Transcription-Polymerase Chain Reaction for SARS-CoV-2 has been unable to keep…
Efficient Synthesis of Compact Deep Neural Networks
Wenhan Xia, Hongxu Yin, Niraj K. Jha
Deep neural networks (DNNs) have been deployed in myriad machine learning applications. However, advances in their accuracy are often achieved with increasingly complex and deep ne…