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MULABS: Multi-Task Learning with Attention-Based Scoring for Click-Through Rate Prediction on Sparse Data in Healthcare Real-World Scenarios.
Tu Tu
Jing Zhang
Yue Wang
Hui Jin
Megan Weihong He
Published in:
BIBM (2022)
Keyphrases
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sparse data
multi task learning
real world
multi task
high dimensional
learning tasks
gaussian processes
transfer learning
learning problems
high order
data mining
data sets
theoretical analysis
learning algorithm
click through rate
machine learning
regression model
inductive learning
learning models
search engine