FastBO: Fast HPO and NAS with Adaptive Fidelity Identification

J Jiang, A Mian - arXiv preprint arXiv:2409.00584, 2024 - arxiv.org
Hyperparameter optimization (HPO) and neural architecture search (NAS) are powerful in
attaining state-of-the-art machine learning models, with Bayesian optimization (BO) standing …

Fast-PGM: Fast Probabilistic Graphical Model Learning and Inference

J Jiang, Z Wen, P Yang, A Mansoor, A Mian - arXiv preprint arXiv …, 2024 - arxiv.org
Probabilistic graphical models (PGMs) serve as a powerful framework for modeling complex
systems with uncertainty and extracting valuable insights from data. However, users face …

[PDF][PDF] Explaining deep neural networks to establish trust

P Yang - 2024 - research-repository.uwa.edu.au
Explaining Deep Neural Networks to Establish Trust Page 1 Explaining Deep Neural Networks
to Establish Trust Peiyu Yang This thesis is presented for the degree of Doctor of Philosophy of …

Efficient automatic probabilistic graphical model learning and inference

J Jiang - 2024 - research-repository.uwa.edu.au
Probabilistic graphical models (PGMs) serve as a powerful framework for modeling complex
systemsunder uncertainty, finding widespread application across domains such as …