Deep learning has emerged as a prominent paradigm in stock return forecasting, demonstrating remarkable capabilities in extracting non-linear patterns from historical stock data. However, existing approaches often process stock features as a monolithic input with fixed temporal receptive fields. This structural inflexi...
Minghui Su, Xiao-Bo Guo, Deyu Tian et al.· Proceedings of the 32nd ACM...· 0 citations
Generative models for top- \(N\) recommendation have garnered significant attention, with Variational Autoencoder (VAE) emerging as a promising approach for modeling user preferences. Yet, traditional VAE-based models encounter two major challenges: simplistic priors may cause posterior collapse, resulting in ineffecti...
Xiao-Bo Guo, Shaoshuai Li, You-Ru Li et al.· ACM Transactions on Informat...· 0 citations
Residual policy adaptation provides a lightweight way to modify a strong reference policy, but a shared scale and a fixed subgroup partition can hide heterogeneous degradation and become fragile when the deployment mixture of information states changes. We introduce RSD-Poker, a structure-adaptive and shift-robust cert...
Miao-Bo Hu, Shu-Hao Hu, Xiao-Bo Guo et al.· 0 citations
Imperfect verifiers can assign a harmful update direction even when clipping and regularization bound its magnitude. We introduce Audit-First VAPO, which separates discrete directional admission from continuous magnitude control. An observation-only accept-appeal-abstain policy uses a finite secondary-verification budg...
Miao-Bo Hu, Shu-Hao Hu, Xiao-Bo Guo et al.· 0 citations
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