2 citations · 2 across the 6 of their papers we have counts for
4 papers · 1 filter
EEG-AS: Instance-Level Foundation Model Selection for EEG Foundation Models via Behavior Reconstruction
Yunzhen Zhang, Ruoxi Piao, Hasan Onur Keles +2
Electroencephalography (EEG) is a non-invasive technique for measuring neural activity and has been widely used in neuroscience applications. Recent advances in EEG foundation mode…
Graph Neural Network-based Algorithm Selection for the Traveling Salesman Problem: A Systematic Study of Cost and Rank Losses under Distinct Budget Regimes
Zhaoxuan Li, Jiale Yang, Yifei Lu +1
Automated Algorithm Selection (AS) aims to improve problem-solving performance by selecting, for each problem instance, the most suitable algorithm from a predefined portfolio. Thi…
Geometric Probing for Algorithm Selection in Continuous Black-Box Optimization
Jiabao Brad Wang, Xiang Shi, Yiliang Yuan +2
Automated algorithm selection for continuous black-box optimization depends on what information is acquired from a problem under a limited probing budget and how that information i…
Beyond Numerical Features: CNN-Driven Algorithm Selection via Contour Plots for Continuous Black-Box Optimization
Yiliang Yuan, Xiang Shi, Mustafa Misir
The present paper introduces a new representation-driven approach to per-instance algorithm selection, applied to black-box optimization, for automatically choosing the most promis…