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Tutorial: Safe and Reliable Machine Learning

Tutorial: Safe and Reliable Machine Learning

15 April 2019
S. Saria
Adarsh Subbaswamy
    FaML
ArXivPDFHTML

Papers citing "Tutorial: Safe and Reliable Machine Learning"

8 / 8 papers shown
Title
Towards Robust Training Datasets for Machine Learning with Ontologies: A
  Case Study for Emergency Road Vehicle Detection
Towards Robust Training Datasets for Machine Learning with Ontologies: A Case Study for Emergency Road Vehicle Detection
Lynn Vonderhaar
Timothy Elvira
T. Procko
Omar Ochoa
24
0
0
21 Jun 2024
Echocardiogram Foundation Model -- Application 1: Estimating Ejection
  Fraction
Echocardiogram Foundation Model -- Application 1: Estimating Ejection Fraction
Adil Dahlan
C. Zakka
Abhinav Kumar
Laura Tang
R. Shad
R. Fong
W. Hiesinger
22
2
0
21 Nov 2023
Deployment of Image Analysis Algorithms under Prevalence Shifts
Deployment of Image Analysis Algorithms under Prevalence Shifts
Patrick Godau
P. Kalinowski
E. Christodoulou
Annika Reinke
M. Tizabi
Luciana Ferrer
Paul Jäger
Lena Maier-Hein
34
9
0
22 Mar 2023
Bayesian logistic regression for online recalibration and revision of
  risk prediction models with performance guarantees
Bayesian logistic regression for online recalibration and revision of risk prediction models with performance guarantees
Jean Feng
Alexej Gossmann
B. Sahiner
R. Pirracchio
OOD
13
5
0
13 Oct 2021
Detecting and Mitigating Test-time Failure Risks via Model-agnostic
  Uncertainty Learning
Detecting and Mitigating Test-time Failure Risks via Model-agnostic Uncertainty Learning
Preethi Lahoti
Krishna P. Gummadi
G. Weikum
26
3
0
09 Sep 2021
Quality Assurance Challenges for Machine Learning Software Applications
  During Software Development Life Cycle Phases
Quality Assurance Challenges for Machine Learning Software Applications During Software Development Life Cycle Phases
Md. Abdullah Al Alamin
Gias Uddin
18
11
0
03 May 2021
"The Human Body is a Black Box": Supporting Clinical Decision-Making
  with Deep Learning
"The Human Body is a Black Box": Supporting Clinical Decision-Making with Deep Learning
M. Sendak
M. C. Elish
M. Gao
Joseph D. Futoma
W. Ratliff
M. Nichols
A. Bedoya
S. Balu
Cara O'Brien
HAI
16
166
0
19 Nov 2019
Can You Trust This Prediction? Auditing Pointwise Reliability After
  Learning
Can You Trust This Prediction? Auditing Pointwise Reliability After Learning
Peter F. Schulam
S. Saria
OOD
11
103
0
02 Jan 2019
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