4 citations · 5 across the 5 of their papers we have counts for
4 papers · 1 filter
Parallel Multi-Objective Hyperparameter Optimization with Uniform Normalization and Bounded Objectives
Romain Egele, Tyler Chang, Yixuan Sun +2
Machine learning (ML) methods offer a wide range of configurable hyperparameters that have a significant influence on their performance. While accuracy is a commonly used performan…
Is One Epoch All You Need For Multi-Fidelity Hyperparameter Optimization?
Romain Egele, Isabelle Guyon, Yixuan Sun +1
Hyperparameter optimization (HPO) is crucial for fine-tuning machine learning models but can be computationally expensive. To reduce costs, Multi-fidelity HPO (MF-HPO) leverages in…
Exploiting Mixed Unlabeled Data for Detecting Samples of Seen and Unseen Out-of-Distribution Classes
Yi-Xuan Sun, Wei Wang
Out-of-Distribution (OOD) detection is essential in real-world applications, which has attracted increasing attention in recent years. However, most existing OOD detection methods…
A data-centric weak supervised learning for highway traffic incident detection
Yixuan Sun, Tanwi Mallick, Prasanna Balaprakash +1
Using the data from loop detector sensors for near-real-time detection of traffic incidents in highways is crucial to averting major traffic congestion. While recent supervised mac…