Cover Image

RFX-Fuse: Breiman and Cutler's Unified ML Engine + Native Explainable Similarity

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Kuchar, Chris
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

RFX: High-Performance Random Forests with GPU Acceleration and QLORA Compression
by: Kuchar, Chris
Published: (2025)

Breiman meets Bellman: Non-Greedy Decision Trees with MDPs
by: Kohler, Hector, et al.
Published: (2023)

Leo Breiman, the Rashomon Effect, and the Occam Dilemma
by: Rudin, Cynthia
Published: (2025)

Unified Native Spaces in Kernel Methods
by: Emery, Xavier, et al.
Published: (2025)

VectorEdits: A Dataset and Benchmark for Instruction-Based Editing of Vector Graphics
by: Kuchař, Josef, et al.
Published: (2025)

MicroFlow: An Efficient Rust-Based Inference Engine for TinyML
by: Carnelos, Matteo, et al.
Published: (2024)

AI/ML Life Cycle Management for Interoperable AI Native RAN
by: Huang, Chu-Hsiang, et al.
Published: (2025)

Attend or Perish: Benchmarking Attention in Algorithmic Reasoning
by: Spiegel, Michal, et al.
Published: (2025)

When Kernels Multiply, Clusters Unify: Fusing Embeddings with the Kronecker Product
by: Wu, Youqi, et al.
Published: (2025)

SPINEX: Similarity-based Predictions with Explainable Neighbors Exploration for Anomaly and Outlier Detection
by: Naser, MZ, et al.
Published: (2024)

SPINEX-Clustering: Similarity-based Predictions with Explainable Neighbors Exploration for Clustering Problems
by: Naser, MZ, et al.
Published: (2024)

Unifying Interpretability and Explainability for Alzheimer's Disease Progression Prediction
by: Ali, Raja Farrukh, et al.
Published: (2024)

Enhancing SHAP Explainability for Diagnostic and Prognostic ML Models in Alzheimer Disease
by: Guillén, Pablo, et al.
Published: (2026)

Can LLMs Revolutionize the Design of Explainable and Efficient TinyML Models?
by: Zeinaty, Christophe El, et al.
Published: (2025)

SPINEX_ Symbolic Regression: Similarity-based Symbolic Regression with Explainable Neighbors Exploration
by: Naser, MZ, et al.
Published: (2024)

Grad-Instructor: Universal Backpropagation with Explainable Evaluation Neural Networks for Meta-learning and AutoML
by: Ino, Ryohei
Published: (2024)

Unified Multimodal Vessel Trajectory Prediction with Explainable Navigation Intention
by: Zhang, Rui, et al.
Published: (2025)

Bayesian Calibration of Engine-out NOx Models for Engine-to-Engine Transferability
by: Zinage, Shrenik, et al.
Published: (2025)

Fed-Meta-Align: A Similarity-Aware Aggregation and Personalization Pipeline for Federated TinyML on Heterogeneous Data
by: Macharla, Hemanth, et al.
Published: (2025)

Explainability Methods for Hardware Trojan Detection: A Systematic Comparison
by: Whitten, Paul, et al.
Published: (2026)

Machine Learning Meets Transparency in Osteoporosis Risk Assessment: A Comparative Study of ML and Explainability Analysis
by: Elias, Farhana, et al.
Published: (2025)

Unifying Information-Theoretic and Pair-Counting Clustering Similarity
by: Gates, Alexander J.
Published: (2025)

Unifying Explainable Anomaly Detection and Root Cause Analysis in Dynamical Systems
by: Sun, Yue, et al.
Published: (2025)

SPINEX: Similarity-based Predictions and Explainable Neighbors Exploration for Regression and Classification Tasks in Machine Learning
by: Naser, M. Z., et al.
Published: (2023)

FlashOmni: A Unified Sparse Attention Engine for Diffusion Transformers
by: Qiao, Liang, et al.
Published: (2025)

EEGDnet: Fusing Non-Local and Local Self-Similarity for 1-D EEG Signal Denoising with 2-D Transformer
by: Yi, Peng, et al.
Published: (2021)

An Explainable Multi-Task Similarity Measure: Integrating Accumulated Local Effects and Weighted Fréchet Distance
by: Hidalgo, Pablo, et al.
Published: (2026)

LUMOS: Democratizing SciML Workflows with L0-Regularized Learning for Unified Feature and Parameter Adaptation
by: Gao, Shouwei, et al.
Published: (2026)

FuseSampleAgg: Fused Neighbor Sampling and Aggregation for Mini-batch GNNs
by: Stanković, Aleksandar
Published: (2025)

Beyond the Veil of Similarity: Quantifying Semantic Continuity in Explainable AI
by: Huang, Qi, et al.
Published: (2024)

Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems
by: Coleman, Benjamin, et al.
Published: (2023)

FairyFuse: Multiplication-Free LLM Inference on CPUs via Fused Ternary Kernels
by: Zuo, Fei, et al.
Published: (2026)

Hyperspectral Anomaly Detection Fused Unified Nonconvex Tensor Ring Factors Regularization
by: Qin, Wenjin, et al.
Published: (2025)

Pre-trained Language Models Learn Remarkably Accurate Representations of Numbers
by: Kadlčík, Marek, et al.
Published: (2025)

EngineAD: A Real-World Vehicle Engine Anomaly Detection Dataset
by: Hojjati, Hadi, et al.
Published: (2026)

The Effect of Similarity Measures on Accurate Stability Estimates for Local Surrogate Models in Text-based Explainable AI
by: Burger, Christopher, et al.
Published: (2024)

SPINEX-TimeSeries: Similarity-based Predictions with Explainable Neighbors Exploration for Time Series and Forecasting Problems
by: Naser, Ahmed Z, et al.
Published: (2024)

Who Audits the Auditor? Tamper-Proof Fraud Detection with Blockchain-Anchored Explainable ML
by: Wang, Zhaohui
Published: (2026)

Explainable Human Activity Recognition: A Unified Review of Concepts and Mechanisms
by: Kundu, Mainak, et al.
Published: (2026)

Unifying VXAI: A Systematic Review and Framework for the Evaluation of Explainable AI
by: Dembinsky, David, et al.
Published: (2025)