robustness
1
6.3
- noun
- /roʊˈbʌstnəs/
- Specialized
:
robustez
- Researchers focused on enhancing the robustness of machine learning algorithms to improve their reliability in real-world applications.
- test the robustness
- robustness check
- robustness of our findings
Examples
-
An important idea for achieving robustness in machine learning is regularization.
Academic text (2017) -
Finally, we ran a series of sensitivity analyses to test the robustness of our model.
Academic text (2015) -
As a field, what are our current ideas about how to achieve robustness in AI systems?
Academic text (2017) -
Finally, as a robustness check, we also present results using the valuation-based index produced by NCREIF.
Academic text (2016) -
A scenario analysis, including productivity losses, was performed to assess the robustness of this direct-costing perspective.
Academic text (2016) -
To further test the robustness of the proposed technique, segmented bone volumes of the femur and tibia are estimated.
Academic text (2017) -
The same three misclassified samples were identified for all tests, indicating a satisfactory robustness of the fractal-SVM classifier.
Academic text (2017) -
A second important idea for achieving robustness is to optimize a risk-sensitive objective, such as the conditional value at risk (CVaR).
Academic text (2017) -
To evaluate the deployment of any AI model, we must assess its robustness against varied input data.
-
The robustness of the system was tested by introducing random noise to the inputs.
Synonyms
363
3.1
Being steady and not likely to change
How well a thing stays strong and works under stress
Antonyms
How Robust
52
4.7
52
4.8
363
3.1
- Specialized
1
6.3
- Specialized
29
4.1
17
5.2
Surface Forms
Morphology
Etymology
Robustness comes from the Latin root robur, 'oak' and 'strength', a helpful image is a machine that stays standing when a storm hits. That's why in computing and machine learning robustness means a model keeps working even when the input data is noisy or changed.