Testing for outliers with conformal p-values
Testing for outliers with conformal p-values Page 1 The Annals of Statistics 2023, Vol. 51, No.
1, 149–178 https://doi.org/10.1214/22-AOS2244 © Institute of Mathematical Statistics, 2023 …
1, 149–178 https://doi.org/10.1214/22-AOS2244 © Institute of Mathematical Statistics, 2023 …
Transcend: Detecting concept drift in malware classification models
Building machine learning models of malware behavior is widely accepted as a panacea
towards effective malware classification. A crucial requirement for building sustainable …
towards effective malware classification. A crucial requirement for building sustainable …
Estimating diagnostic uncertainty in artificial intelligence assisted pathology using conformal prediction
Unreliable predictions can occur when an artificial intelligence (AI) system is presented with
data it has not been exposed to during training. We demonstrate the use of conformal …
data it has not been exposed to during training. We demonstrate the use of conformal …
[图书][B] Algorithmic learning in a random world
Vladimir Vovk Alexander Gammerman Glenn Shafer Second Edition Page 1 Vladimir Vovk
Alexander Gammerman Glenn Shafer Algorithmic Learning in a Random World Second …
Alexander Gammerman Glenn Shafer Algorithmic Learning in a Random World Second …
Testing randomness online
V Vovk - Statistical Science, 2021 - projecteuclid.org
Testing Randomness Online Page 1 Statistical Science 2021, Vol. 36, No. 4, 595–611 https://doi.org/10.1214/20-STS817
© Institute of Mathematical Statistics, 2021 Testing Randomness Online Vladimir Vovk …
© Institute of Mathematical Statistics, 2021 Testing Randomness Online Vladimir Vovk …
[图书][B] Conformal prediction for reliable machine learning: theory, adaptations and applications
The conformal predictions framework is a recent development in machine learning that can
associate a reliable measure of confidence with a prediction in any real-world pattern …
associate a reliable measure of confidence with a prediction in any real-world pattern …
iDECODe: In-distribution equivariance for conformal out-of-distribution detection
Abstract Machine learning methods such as deep neural networks (DNNs), despite their
success across different domains, are known to often generate incorrect predictions with …
success across different domains, are known to often generate incorrect predictions with …
Towards intelligent incident management: why we need it and how we make it
The management of cloud service incidents (unplanned interruptions or outages of a
service/product) greatly affects customer satisfaction and business revenue. After years of …
service/product) greatly affects customer satisfaction and business revenue. After years of …
Real-time out-of-distribution detection in learning-enabled cyber-physical systems
F Cai, X Koutsoukos - 2020 ACM/IEEE 11th International …, 2020 - ieeexplore.ieee.org
Cyber-physical systems (CPS) greatly benefit by using machine learning components that
can handle the uncertainty and variability of the real-world. Typical components such as …
can handle the uncertainty and variability of the real-world. Typical components such as …
Quantifying uncertainty in land-use land-cover classification using conformal statistics
Land-use land-cover (LULC) change is one of the most important anthropogenic threats to
biodiversity and ecosystems integrity. As a result, the systematic generation of annual …
biodiversity and ecosystems integrity. As a result, the systematic generation of annual …