Nanosecond machine learning event classification with boosted decision trees in FPGA for high energy physics

TM Hong, BT Carlson, BR Eubanks… - Journal of …, 2021 - iopscience.iop.org
We present a novel implementation of classification using the machine learning/artificial
intelligence method called boosted decision trees (BDT) on field programmable gate arrays …

Advances in spam detection for email spam, web spam, social network spam, and review spam: ML-based and nature-inspired-based techniques

AA Akinyelu - Journal of Computer Security, 2021 - content.iospress.com
Despite the great advances in spam detection, spam remains a major problem that has
affected the global economy enormously. Spam attacks are popularly perpetrated through …

[HTML][HTML] Big data decision tree for continuous-valued attributes based on unbalanced cut points

S Ma, J Zhai - Journal of Big Data, 2023 - Springer
The decision tree is a widely used decision support model, which can quickly mine effective
decision rules based on the dataset. The decision tree induction algorithm for continuous …

[HTML][HTML] Integrated Approach Using Intuitionistic Fuzzy Multicriteria Decision-Making to Support Classifier Selection for Technology Adoption in Patients with Parkinson …

M Ortiz-Barrios, I Cleland, M Donnelly… - JMIR Rehabilitation …, 2024 - rehab.jmir.org
Background: Parkinson disease (PD) is reported to be among the most prevalent
neurodegenerative diseases globally, presenting ongoing challenges and increasing …

Efficient traversal of decision tree ensembles with FPGAs

R Molina, F Loor, V Gil-Costa, FM Nardini… - Journal of Parallel and …, 2021 - Elsevier
Abstract System-on-Chip (SoC) based Field Programmable Gate Arrays (FPGAs) provide a
hardware acceleration technology that can be rapidly deployed and tuned, thus providing a …

Confidential inference in decision trees: FPGA design and implementation

RR Karn, IAM Elfadel - … on Very Large Scale Integration (VLSI …, 2022 - ieeexplore.ieee.org
In confidential computing, algorithms operate on encrypted inputs to produce encrypted
outputs. Specifically, in confidential inference, Alice has the parameters of the machine …

A flexible hls hoeffding tree implementation for runtime learning on fpga

LM Sousa, N Paulino, JC Ferreira… - 2022 IEEE 21st …, 2022 - ieeexplore.ieee.org
Decision trees are often preferred when implementing Machine Learning in embedded
systems for their simplicity and scalability. Hoeffding Trees are a type of Decision Trees that …

Implementações eficientes de random forest em fpga de baixo custo para internet das coisas e computação de borda

A Silva, O Silva, I Moreira… - … de Alto Desempenho …, 2024 - proceedings-sol.sbc.org.br
Random Forest é uma abordagem robusta e amplamente utilizada em aprendizado de
máquina. Embora existam diversas implementações paralelas em FPGA, não há estudos …

Hardware acceleration of decision tree learning algorithm

A Zoulkarni, C Kachris, D Soudris - 2020 9th International …, 2020 - ieeexplore.ieee.org
Decision Tree Classification variants are among the most popular machine learning
algorithms and have been applied in various fields with success. Their versatility and …

Artificial intelligence for materials damage diagnostics and prognostics

S Malik, A Kontsos - Artificial Intelligence in Manufacturing, 2024 - Elsevier
The reliable detection and evaluation of damage in materials represents a major
engineering concern to prevent component failure in a variety of applications. Defects …