Search Results for author:
Found 4 papers, 2 papers with code
Conformalized Survival Distributions: A Generic Post-Process to Increase Calibration
Discrimination and calibration represent two important properties of survival analysis, with the former assessing the model's ability to accurately rank subjects and the latter evaluating the alignment of predicted outcomes with actual events.
iHAS: Instance-wise Hierarchical Architecture Search for Deep Learning Recommendation Models
The searching stage identifies optimal instance-wise embedding dimensions across different field features via carefully designed Bernoulli gates with stochastic selection and regularizers.
ConKI: Contrastive Knowledge Injection for Multimodal Sentiment Analysis
Multimodal Sentiment Analysis leverages multimodal signals to detect the sentiment of a speaker.
An Effective Meaningful Way to Evaluate Survival Models
One straightforward metric to evaluate a survival prediction model is based on the Mean Absolute Error (MAE) -- the average of the absolute difference between the time predicted by the model and the true event time, over all subjects.
