Tag: causal machine learning
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Optimizing AutoML Pipelines with In-Context Decision Making
Discover how in-context decision making enhances AutoML pipeline optimization using PS-PFN, improving model selection and adaptation efficiency.
Estimating Target Task Performance in Semi/Self-Supervised Learning
Discover a low-cost method to estimate target task performance from unsupervised pretext tasks in semi/self-supervised learning for improved AI models.
LLMs’ Library and Language Preferences in Code Generation
Explore how large language models prefer libraries and programming languages, revealing biases and optimization opportunities in AI code generation.
Path Regularization Theory for Neural Networks & Double Descent
Discover a near-complete, optimal generalization theory for multilayer neural networks using path regularization and insights on the double descent phenome...
Matrix Profile for Multidimensional Time Series Anomaly Detection
Discover how Matrix Profile enhances anomaly detection in multidimensional time series with robust performance across supervised and unsupervised setups.