ML @ CMU

NOVEMBER 7, 2024

For the Risk Modeling component, we designed a novel interpretable deep learning tabular model extending TabNet. To validate the proposed system, we simulate different scenarios in which the RELand system could be deployed in mine clearance operations using real data from Colombia. Validation results in Colombia.

Clustering 154

Clustering Cross Validation Machine Learning Machine Learning 154

Heartbeat

JUNE 14, 2023

Label Smoothing Equation [5] In their 2019 paper “ When does label smoothing help? ”, Hinton et al. [5] logits of the final layer), which helps reduce overconfidence and subsequently reduces the network’s ECE. ” Advances in neural information processing systems 32 (2019). [6] Measuring Calibration in Deep Learning.

Deep Learning 59

Deep Learning Deep Learning Support Vector Machines Machine Learning 59

Mlearning.ai

APRIL 11, 2023

Use the cross validation technique to provide a more accurate estimate of the generalization error. Conclusion This work gives a brief overview of the double descent phenomenon, a novel concept discovered in 2019 [3]. Increase the size of training data. Hope this was helpful and enhanced your curiosity ?.

Cross Validation 52

Cross Validation Machine Learning Machine Learning Deep Learning 52

AWS Machine Learning Blog

FEBRUARY 10, 2023

Quantitative evaluation We utilize 2018–2020 season data for model training and validation, and 2021 season data for model evaluation. We perform a five-fold cross-validation to select the best model during training, and perform hyperparameter optimization to select the best settings on multiple model architecture and training parameters.

ML 96

ML ML Machine Learning Machine Learning 96

Mlearning.ai

FEBRUARY 2, 2023

In this article, I show how a Convolutional Neural Network can be used to predict a person's age based on the person's ECG Attia et al 2019 [1], showed that a person's age could be predicted from an ECG using convolutional neural networks (CNN). et al 2019 [2]. years on the test set. Ismail Fawaz et al., Singstad, B.-J.

Cross Validation 52

Cross Validation Deep Learning Deep Learning Artificial Intelligence 52