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09/16/2023
Some Algebraic Aspects of Assume-Guarantee Reasoning
We present the algebra of assume-guarantee (AG) contracts. We define con...
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07/28/2023
Beating Backdoor Attack at Its Own Game
Deep neural networks (DNNs) are vulnerable to backdoor attack, which doe...
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05/27/2023
Context-Aided Variable Elimination for Requirement Engineering
Deriving system-level specifications from component specifications usual...
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03/31/2023
Pacti: Scaling Assume-Guarantee Reasoning for System Analysis and Design
Contract-based design is a method to facilitate modular system design. W...
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02/27/2023
A Grammar for the Representation of Unmanned Aerial Vehicles with 3D Topologies
We propose a context-sensitive grammar for the systematic exploration of...
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11/21/2022
Contract-Based Specification Refinement and Repair for Mission Planning
We address the problem of modeling, refining, and repairing formal speci...
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12/01/2021
Querying Labelled Data with Scenario Programs for Sim-to-Real Validation
Simulation-based testing of autonomous vehicles (AVs) has become an esse...
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10/28/2021
Class-wise Thresholding for Detecting Out-of-Distribution Data
We consider the problem of detecting OoD(Out-of-Distribution) input data...
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09/25/2021
Multi-source Few-shot Domain Adaptation
Multi-source Domain Adaptation (MDA) aims to transfer predictive models ...
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09/14/2021
Conditional Synthetic Data Generation for Robust Machine Learning Applications with Limited Pandemic Data
Background: At the onset of a pandemic, such as COVID-19, data with prop...
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07/03/2021
Scene-aware Learning Network for Radar Object Detection
Object detection is essential to safe autonomous or assisted driving. Pr...
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05/26/2021
Hypercontracts
Contracts (or interface) theories have been proposed to formally support...
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04/12/2021
A Hierarchical State-Machine-Based Framework for Platoon Manoeuvre Descriptions
This paper introduces the SEAD framework that simplifies the process of ...
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11/30/2020
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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09/23/2020
The Quotient in Preorder Theories
Seeking the largest solution to an expression of the form A x <= B is a ...
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08/20/2020
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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08/20/2020
Using Ensemble Classifiers to Detect Incipient Anomalies
Incipient anomalies present milder symptoms compared to severe ones, and...
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07/12/2020
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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05/05/2020
Industrial Control via Application Containers:Maintaining determinism in IAAS
Industry 4.0 is changing fundamentally data collection, its storage and ...
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12/05/2019
Probabilistic Dynamic Hard Real-Time Scheduling in HPC
Industry 4.0 is changing fundamentally the way data is collected, stored...
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09/10/2019
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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09/02/2019
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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08/13/2019
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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07/26/2019
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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03/24/2019
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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03/09/2019
A tractable ellipsoidal approximation for voltage regulation problems
We present a machine learning approach to the solution of chance constra...
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02/27/2019
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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02/18/2019
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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02/18/2019
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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11/30/2018
A Metric for Linear Temporal Logic
We propose a measure and a metric on the sets of infinite traces generat...
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05/17/2018
Counterexample-Guided Data Augmentation
We present a novel framework for augmenting data sets for machine learni...
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02/24/2018
Time Series Learning using Monotonic Logical Properties
We propose a new paradigm for time-series learning where users implicitl...
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02/14/2018
Context-Specific Validation of Data-Driven Models
With an increasing use of data-driven models to control robotic systems,...
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08/10/2017
