Insup Lee

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University of Pennsylvania

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Are all outliers alike? On Understanding the Diversity of Outliers for Detecting OODs

Deep neural networks (DNNs) are known to produce incorrect predictions w...
03/23/2021 ∙ by Ramneet Kaur, et al. ∙ 0 ∙ share

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Confidence Calibration with Bounded Error Using Transformations

As machine learning techniques become widely adopted in new domains, esp...
02/25/2021 ∙ by Sooyong Jang, et al. ∙ 0 ∙ share

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Improving Classifier Confidence using Lossy Label-Invariant Transformations

Providing reliable model uncertainty estimates is imperative to enabling...
11/09/2020 ∙ by Sooyong Jang, et al. ∙ 0 ∙ share

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PAC Confidence Predictions for Deep Neural Network Classifiers

A key challenge for deploying deep neural networks (DNNs) in safety crit...
11/02/2020 ∙ by Sangdon Park, et al. ∙ 0 ∙ share

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Class-Weighted Evaluation Metrics for Imbalanced Data Classification

Class distribution skews in imbalanced datasets may lead to models with ...
10/12/2020 ∙ by Akhilesh Gupta, et al. ∙ 23 ∙ share

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Optimal Virtual Cluster-based Multiprocessor Scheduling

Scheduling of constrained deadline sporadic task systems on multiprocess...
04/06/2020 ∙ by Arvind Easwaran, et al. ∙ 0 ∙ share

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Calibrated Prediction with Covariate Shift via Unsupervised Domain Adaptation

Reliable uncertainty estimates are an important tool for helping autonom...
02/29/2020 ∙ by Sangdon Park, et al. ∙ 9 ∙ share

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VisionGuard: Runtime Detection of Adversarial Inputs to Perception Systems

Deep neural network (DNN) models have proven to be vulnerable to adversa...
02/23/2020 ∙ by Yiannis Kantaros, et al. ∙ 6 ∙ share

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PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction

We propose an algorithm combining calibrated prediction and generalizati...
12/31/2019 ∙ by Sangdon Park, et al. ∙ 15 ∙ share

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Case Study: Verifying the Safety of an Autonomous Racing Car with a Neural Network Controller

This paper describes a verification case study on an autonomous racing c...
10/24/2019 ∙ by Radoslav Ivanov, et al. ∙ 0 ∙ share

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Reinforcement Learning for Temporal Logic Control Synthesis with Probabilistic Satisfaction Guarantees

Reinforcement Learning (RL) has emerged as an efficient method of choice...
09/11/2019 ∙ by Mohammadhosein Hasanbeig, et al. ∙ 8 ∙ share

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Self-Driving Vehicle Verification Towards a Benchmark

Industrial cyber-physical systems are hybrid systems with strict safety ...
06/20/2018 ∙ by Nima Roohi, et al. ∙ 0 ∙ share

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Injected and Delivered: Fabricating Implicit Control over Actuation Systems by Spoofing Inertial Sensors

Inertial sensors provide crucial feedback for control systems to determi...
06/20/2018 ∙ by Yazhou Tu, et al. ∙ 0 ∙ share

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Resilient Linear Classification: An Approach to Deal with Attacks on Training Data

Data-driven techniques are used in cyber-physical systems (CPS) for cont...
08/10/2017 ∙ by Sangdon Park, et al. ∙ 0 ∙ share

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