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 …
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 …
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 …
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 …
Background: Parkinson disease (PD) is reported to be among the most prevalent
neurodegenerative diseases globally, presenting ongoing challenges and increasing …
neurodegenerative diseases globally, presenting ongoing challenges and increasing …
Efficient traversal of decision tree ensembles with FPGAs
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 …
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 …
outputs. Specifically, in confidential inference, Alice has the parameters of the machine …
A flexible hls hoeffding tree implementation for runtime learning on fpga
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 …
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 …
máquina. Embora existam diversas implementações paralelas em FPGA, não há estudos …
Hardware acceleration of decision tree learning algorithm
Decision Tree Classification variants are among the most popular machine learning
algorithms and have been applied in various fields with success. Their versatility and …
algorithms and have been applied in various fields with success. Their versatility and …
Artificial intelligence for materials damage diagnostics and prognostics
The reliable detection and evaluation of damage in materials represents a major
engineering concern to prevent component failure in a variety of applications. Defects …
engineering concern to prevent component failure in a variety of applications. Defects …