Academic
arXiv:2602.20404v1 Announce Type: new Abstract: In tabular Markov decision processes (MDPs) with perfect state observability, each trajectory provides active samples from the transition distributions conditioned …
arXiv:2602.20418v1 Announce Type: new Abstract: Graph neural networks (GNNs) have demonstrated superior performance in various applications, such as recommendation systems and financial risk management. However, …
arXiv:2602.20419v1 Announce Type: new Abstract: Machine Learning as a Service (MLaaS) has emerged as a widely adopted paradigm for providing access to deep neural network …
arXiv:2602.20427v1 Announce Type: new Abstract: Efficient operator scheduling is a fundamental challenge in software compilation and hardware synthesis. While recent differentiable approaches have sought to …
arXiv:2602.20442v1 Announce Type: new Abstract: Machine learning holds great promise for advancing the field of medicine, with electronic health records (EHRs) serving as a primary …
arXiv:2602.20457v1 Announce Type: new Abstract: We study online alignment of large language models under misspecified preference feedback, where the observed preference oracle deviates from an …
arXiv:2602.20461v1 Announce Type: new Abstract: Attention learners, neural networks built on the attention mechanism, e.g., transformers, excel at learning the implicit relationships that relate sequences …
arXiv:2602.20463v1 Announce Type: new Abstract: This paper provides a reinterpretation of the Drifting Model~\cite{deng2026generative} through a semigroup-consistent long-short flow-map factorization. We show that a global …
arXiv:2602.20467v1 Announce Type: new Abstract: The unmatched ability of Deep Neural Networks in capturing complex patterns in large and noisy datasets is often associated with …
arXiv:2602.20468v1 Announce Type: new Abstract: Multivariate time-series anomaly detection is essential for reliable industrial control, telemetry, and service monitoring. However, the evolving inter-variable dependencies and …
arXiv:2602.20480v1 Announce Type: new Abstract: The distinctive architectural features of normalizing flows (NFs), notably bijectivity and tractable Jacobians, make them well-suited for generative modeling. Invertible …
arXiv:2602.20492v1 Announce Type: new Abstract: Decentralized federated learning (DFL) based on low-rank adaptation (LoRA) enables mobile devices with multi-task datasets to collaboratively fine-tune a large …
