approximation techniques 1kernel design 1kernel pca 1non-linear subspace 1out-of-distribution detection 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.LG2026
Kernel PCA for Out-of-Distribution Detection: Non-Linear Kernel Selection and Approximation
Kun Fang, Qinghua Tao, Mingzhen He +6
The paper proposes a kernel PCA based method for out-of-distribution detection that learns a discriminative non-linear subspace using a newly designed Cosine-Gaussian kernel and in…
cs.LG2026
MLOW: Interpretable Low-Rank Frequency Magnitude Decomposition of Multiple Effects for Time Series Forecasting
Runze Yang, Longbing Cao, Xiaoming Wu +4
Separating multiple effects in time series is fundamental yet challenging for time-series forecasting (TSF). However, existing TSF models cannot effectively learn interpretable mul…
cs.LG2025
Fourier Basis Mapping: A Time-Frequency Learning Framework for Time Series Forecasting
Runze Yang, Longbing Cao, Xin You +3
The integration of Fourier transform and deep learning opens new avenues for time series forecasting. We reconsider the Fourier transform from a basis functions perspective. Specif…