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A Customizable Dynamic Scenario Modeling and Data Generation Platform for Autonomous Driving
Safely interacting with humans is a significant challenge for autonomous...
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The Quotient in Preorder Theories
Seeking the largest solution to an expression of the form A x <= B is a ...
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Generalizing Fault Detection Against Domain Shifts Using Stratification-Aware Cross-Validation
Incipient anomalies present milder symptoms compared to severe ones, and...
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Using Ensemble Classifiers to Detect Incipient Anomalies
Incipient anomalies present milder symptoms compared to severe ones, and...
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Exploiting Uncertainties from Ensemble Learners to Improve Decision-Making in Healthcare AI
Ensemble learning is widely applied in Machine Learning (ML) to improve ...
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Industrial Control via Application Containers:Maintaining determinism in IAAS
Industry 4.0 is changing fundamentally data collection, its storage and ...
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Probabilistic Dynamic Hard Real-Time Scheduling in HPC
Industry 4.0 is changing fundamentally the way data is collected, stored...
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Augmenting Monte Carlo Dropout Classification Models with Unsupervised Learning Tasks for Detecting and Diagnosing Out-of-Distribution Faults
The Monte Carlo dropout method has proved to be a scalable and easy-to-u...
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Domain Randomization and Pyramid Consistency: Simulation-to-Real Generalization without Accessing Target Domain Data
We propose to harness the potential of simulation for the semantic segme...
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Industrial Control via Application Containers: Migrating from Bare-Metal to IAAS
We explore the challenges and opportunities of shifting industrial contr...
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An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing
We present a novel unsupervised deep learning approach that utilizes the...
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A Formalization of Robustness for Deep Neural Networks
Deep neural networks have been shown to lack robustness to small input p...
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A tractable ellipsoidal approximation for voltage regulation problems
We present a machine learning approach to the solution of chance constra...
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A New Simulation Metric to Determine Safe Environments and Controllers for Systems with Unknown Dynamics
We consider the problem of extracting safe environments and controllers ...
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Detecting and Diagnosing Incipient Building Faults Using Uncertainty Information from Deep Neural Networks
Early detection of incipient faults is of vital importance to reducing m...
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A One-Class Support Vector Machine Calibration Method for Time Series Change Point Detection
It is important to identify the change point of a system's health status...
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A Metric for Linear Temporal Logic
We propose a measure and a metric on the sets of infinite traces generat...
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Counterexample-Guided Data Augmentation
We present a novel framework for augmenting data sets for machine learni...
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Time Series Learning using Monotonic Logical Properties
We propose a new paradigm for time-series learning where users implicitl...
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Context-Specific Validation of Data-Driven Models
With an increasing use of data-driven models to control robotic systems,...
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Systematic Testing of Convolutional Neural Networks for Autonomous Driving
We present a framework to systematically analyze convolutional neural ne...
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