Europe
Adapting to Continuous Covariate Shift via Online Density Ratio Estimation Y u-Jie Zhang
Existing works of coping with covariate shift mainly focused on the "
Semi-supervised Knowledge Transfer Across Multi-omic Single-cell Data
Code is available at https://github.com/zfkarl/DANCE.
Simple and Fast Distillation of Diffusion Models Zhenyu Zhou 1,2 Defang Chen 3 Can Wang 1,2 Chun Chen
To achieve both efficient and high-quality synthesis, various distillation-based accelerated sampling methods have been developed recently.
GloballyConvergentNewtonMethodsfor Ill-conditionedGeneralizedSelf-concordantLosses
Second, in the non-parametric machine learning setting, we provide an explicit algorithm combining the previous scheme with Nyström projection techniques, andprovethatitachievesoptimal generalization bounds with atime complexity of orderO(ndfλ), a memory complexity of orderO(df2λ) and no dependence on the condition number, generalizing the results known for leastsquaresregression.Here nisthenumberofobservationsand dfλ istheassociated degrees of freedom.
HGDL: Heterogeneous Graph Label Distribution Learning
Each distribution quantifies the descriptive degrees of various classes given a specific instance.
