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cs.LG2026
Jump Like A Squirrel: Optimized Execution Step Order for Anytime Random Forest Inference
Daniel Biebert, Christian Hakert, Kay Heider +3
Due to their efficiency and small size, decision trees and random forests are popular machine learning models used for classification on resource-constrained systems. In such syste…
cs.LG2025
WCDT: Systematic WCET Optimization for Decision Tree Implementations
Nils Hölscher, Christian Hakert, Georg von der Brüggen +3
Machine-learning models are increasingly deployed on resource-constrained embedded systems with strict timing constraints. In such scenarios, the worst-case execution time (WCET) o…
cs.LG2024
Register Your Forests: Decision Tree Ensemble Optimization by Explicit CPU Register Allocation
Daniel Biebert, Christian Hakert, Kuan-Hsun Chen +1
Bringing high-level machine learning models to efficient and well-suited machine implementations often invokes a bunch of tools, e.g.~code generators, compilers, and optimizers. Al…