[HTML][HTML] Survey on mining signal temporal logic specifications
Formal specifications play an essential role in the life-cycle of modern systems, both at the
time of their design and during their operation. Despite their importance, formal …
time of their design and during their operation. Despite their importance, formal …
The voice of COVID-19: Breath and cough recording classification with temporal decision trees and random forests
Symbolic learning is the logic-based approach to machine learning, and its mission is to
provide algorithms and methodologies to extract logical information from data and express it …
provide algorithms and methodologies to extract logical information from data and express it …
Learning linear temporal properties
We present two novel algorithms for learning formulas in Linear Temporal Logic (LTL) from
examples. The first learning algorithm reduces the learning task to a series of satisfiability …
examples. The first learning algorithm reduces the learning task to a series of satisfiability …
Frequency-temporal-logic-based bearing fault diagnosis and fault interpretation using Bayesian optimization with Bayesian neural networks
Rolling element bearings are widely used components in modern rotary machines, and
accurate diagnosis and interpretation for faults of bearings are significant for equipment …
accurate diagnosis and interpretation for faults of bearings are significant for equipment …
Earthquake multi-classification detection based velocity and displacement data filtering using machine learning algorithms
MA Murti, R Junior, AN Ahmed, A Elshafie - Scientific reports, 2022 - nature.com
Earthquake is one of the natural disasters that have a big impact on society. Currently, there
are many studies on earthquake detection. However, the vibrations that were detected by …
are many studies on earthquake detection. However, the vibrations that were detected by …
[HTML][HTML] Transfer of temporal logic formulas in reinforcement learning
Transferring high-level knowledge from a source task to a target task is an effective way to
expedite reinforcement learning (RL). For example, propositional logic and first-order logic …
expedite reinforcement learning (RL). For example, propositional logic and first-order logic …
Offline and online learning of signal temporal logic formulae using decision trees
G Bombara, C Belta - ACM Transactions on Cyber-Physical Systems, 2021 - dl.acm.org
In this article, we focus on inferring high-level descriptions of a system from its execution
traces. Specifically, we consider a classification problem where system behaviors are …
traces. Specifically, we consider a classification problem where system behaviors are …
Scalable anytime algorithms for learning fragments of linear temporal logic
Linear temporal logic (LTL) is a specification language for finite sequences (called traces)
widely used in program verification, motion planning in robotics, process mining, and many …
widely used in program verification, motion planning in robotics, process mining, and many …
TeLEx: learning signal temporal logic from positive examples using tightness metric
We propose a novel passive learning approach, TeLex, to infer signal temporal logic (STL)
formulas that characterize the behavior of a dynamical system using only observed signal …
formulas that characterize the behavior of a dynamical system using only observed signal …
Interpretable classification of time-series data using efficient enumerative techniques
S Mohammadinejad, JV Deshmukh… - Proceedings of the 23rd …, 2020 - dl.acm.org
Cyber-physical system applications such as autonomous vehicles, wearable devices, and
avionic systems generate a large volume of time-series data. Designers often look for tools …
avionic systems generate a large volume of time-series data. Designers often look for tools …