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Encoding tree sparsity in multi-task learning: A probabilistic framework
Lei Han
, Yu Zhang
, Guojie Song
*
, Kunqing Xie
*
Corresponding author for this work
Department of Computer Science
Research output
:
Chapter in book/report/conference proceeding
›
Conference proceeding
›
peer-review
26
Citations (Scopus)
Overview
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Dive into the research topics of 'Encoding tree sparsity in multi-task learning: A probabilistic framework'. Together they form a unique fingerprint.
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Keyphrases
Cauchy Distribution
50%
Common Information
50%
Existing Techniques
50%
Expectation-maximization Algorithm
50%
Gaussian Distribution
50%
Generalization Performance
50%
Group Sparsity
50%
Group Structure
50%
Learning Model
50%
Model Coefficients
50%
Model Complexity
50%
Multi-task Learning
100%
Multiple Components
50%
Probabilistic Framework
100%
Probability Tree
50%
Real-world Application
50%
Real-world Problems
50%
Sparse Solution
50%
Sparsity Model
50%
Tree Sparsity
100%
Tree Structure
50%
Computer Science
Cauchy Distribution
33%
Generalization Performance
33%
Group Structure
33%
Information Common
33%
Model Complexity
33%
Multiple Component
33%
Multitask Learning
100%
Probabilistic Framework
100%
Real-World Problem
33%
Sparse Solution
33%
Sparsity
100%
World Application
33%