research
∙
08/01/2023
Learning from Hypervectors: A Survey on Hypervector Encoding
Hyperdimensional computing (HDC) is an emerging computing paradigm that ...
share
research
∙
04/11/2023
Late Breaking Results: Scalable and Efficient Hyperdimensional Computing for Network Intrusion Detection
Cybersecurity has emerged as a critical challenge for the industry. With...
research
∙
04/11/2023
DistHD: A Learner-Aware Dynamic Encoding Method for Hyperdimensional Classification
Brain-inspired hyperdimensional computing (HDC) has been recently consid...
research
∙
03/01/2023
BP-NTT: Fast and Compact in-SRAM Number Theoretic Transform with Bit-Parallel Modular Multiplication
Number Theoretic Transform (NTT) is an essential mathematical tool for c...
research
∙
08/01/2022
Efficient Personalized Learning for Wearable Health Applications using HyperDimensional Computing
Health monitoring applications increasingly rely on machine learning tec...
research
∙
07/25/2022
COSIME: FeFET based Associative Memory for In-Memory Cosine Similarity Search
In a number of machine learning models, an input query is searched acros...
research
∙
07/08/2022
Modeling and Predicting Transistor Aging under Workload Dependency using Machine Learning
The pivotal issue of reliability is one of colossal concern for circuit ...
research
∙
05/14/2022
QHD: A brain-inspired hyperdimensional reinforcement learning algorithm
Reinforcement Learning (RL) has opened up new opportunities to solve a w...
research
∙
10/01/2021
Spiking Hyperdimensional Network: Neuromorphic Models Integrated with Memory-Inspired Framework
Recently, brain-inspired computing models have shown great potential to ...
research
∙
06/22/2021
MIMHD: Accurate and Efficient Hyperdimensional Inference Using Multi-Bit In-Memory Computing
Hyperdimensional Computing (HDC) is an emerging computational framework ...
research
∙
08/10/2020
Trustworthy AI Inference Systems: An Industry Research View
In this work, we provide an industry research view for approaching the d...
research
∙
05/14/2020
Prive-HD: Privacy-Preserved Hyperdimensional Computing
The privacy of data is a major challenge in machine learning as a traine...
research
∙
11/17/2019
FPGA Energy Efficiency by Leveraging Thermal Margin
Cutting edge FPGAs are not energy efficient as conventionally presumed t...
research
∙
08/18/2019
Workload-Aware Opportunistic Energy Efficiency in Multi-FPGA Platforms
The continuous growth of big data applications with high computational a...
research
∙
02/18/2019
Adv-DWF: Defending Against Deep-Learning-Based Website Fingerprinting Attacks with Adversarial Traces
Website Fingerprinting (WF) is a type of traffic analysis attack that en...
research
∙
06/15/2018
RAPIDNN: In-Memory Deep Neural Network Acceleration Framework
Deep neural networks (DNN) have demonstrated effectiveness for various a...
research
∙
05/05/2018
Towards Predicting Efficient and Anonymous Tor Circuits
The Tor anonymity system provides online privacy for millions of users, ...
research
∙
01/07/2018