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cs.LG2025
From Deep Additive Kernel Learning to Last-Layer Bayesian Neural Networks via Induced Prior Approximation
Wenyuan Zhao, Haoyuan Chen, Tie Liu +2
With the strengths of both deep learning and kernel methods like Gaussian Processes (GPs), Deep Kernel Learning (DKL) has gained considerable attention in recent years. From the co…
cs.LG2024
From Function to Distribution Modeling: A PAC-Generative Approach to Offline Optimization
Qiang Zhang, Ruida Zhou, Yang Shen +1
This paper considers the problem of offline optimization, where the objective function is unknown except for a collection of ``offline" data examples. While recent years have seen…
cs.LG2019
Multiple Sample Clustering
Xiang Wang, Tie Liu
The clustering algorithms that view each object data as a single sample drawn from a certain distribution, Gaussian distribution, for example, has been a hot topic for decades. Man…