research
∙
01/26/2023
PerfSAGE: Generalized Inference Performance Predictor for Arbitrary Deep Learning Models on Edge Devices
The ability to accurately predict deep neural network (DNN) inference pe...
share
research
∙
01/15/2022
UDC: Unified DNAS for Compressible TinyML Models
Emerging Internet-of-things (IoT) applications are driving deployment of...
research
∙
11/10/2021
AnalogNets: ML-HW Co-Design of Noise-robust TinyML Models and Always-On Analog Compute-in-Memory Accelerator
Always-on TinyML perception tasks in IoT applications require very high ...
research
∙
03/26/2021
Active multi-fidelity Bayesian online changepoint detection
Online algorithms for detecting changepoints, or abrupt shifts in the be...
research
∙
01/28/2021
Information contraction in noisy binary neural networks and its implications
Neural networks have gained importance as the machine learning models th...
research
∙
10/21/2020
MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers
Executing machine learning workloads locally on resource constrained mic...
research
∙
01/14/2020
Noisy Machines: Understanding Noisy Neural Networks and Enhancing Robustness to Analog Hardware Errors Using Distillation
The success of deep learning has brought forth a wave of interest in com...
research
∙
02/27/2019
FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer Learning
The computational demands of computer vision tasks based on state-of-the...
research
∙
12/04/2018
