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arXiv:2507.02890v3 Announce Type: replace-cross Abstract: In Industry 4.0 manufacturing environments, forecasting Overall Equipment Efficiency (OEE) is critical for data-driven operational control and predictive maintenance. However,...
arXiv:2506.22488v2 Announce Type: replace-cross Abstract: Accurate decoding of lower-limb motion from EEG signals is essential for advancing brain-computer interface (BCI) applications in movement intent recognition...
arXiv:2506.18846v2 Announce Type: replace-cross Abstract: In many inverse problems, the unknown is composed of multiple components with different regularities, for example, in imaging problems, where...
arXiv:2506.18314v2 Announce Type: replace-cross Abstract: Foundation models are transforming neuroscience but are often prohibitively large, data-hungry, and difficult to deploy. Here, we introduce BrainSymphony, a...
arXiv:2505.18362v2 Announce Type: replace-cross Abstract: We develop a general theoretical framework for optimal probability density control on standard measure spaces, aimed at addressing large-scale multi-agent...
arXiv:2505.13732v5 Announce Type: replace-cross Abstract: We introduce $\textit{Backward Conformal Prediction}$, a method that guarantees conformal coverage while providing flexible control over the size of prediction...
arXiv:2505.07078v5 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have recently been leveraged for asset pricing tasks and stock trading applications, enabling AI agents to...
arXiv:2504.06475v2 Announce Type: replace-cross Abstract: Tensor networks like matrix product states (MPSs) and matrix product operators (MPOs) are powerful tools for representing exponentially large states...
arXiv:2504.03757v2 Announce Type: replace-cross Abstract: Decoding gait dynamics from EEG signals presents significant challenges due to the complex spatial dependencies of motor processes, the need...
arXiv:2501.02942v3 Announce Type: replace-cross Abstract: Building on the blueprint from Goemans and Williamson (1995) for the Max-Cut problem, we construct a polynomial-time approximation algorithm for...
arXiv:2412.10251v2 Announce Type: replace-cross Abstract: We present a novel, model-free, and data-driven methodology for controlling complex dynamical systems into previously unseen target states, including those...
arXiv:2409.17525v3 Announce Type: replace-cross Abstract: Spoken language is often, if not always, understood in a context formed by the identity of the speaker. For example,...
arXiv:2409.01869v3 Announce Type: replace-cross Abstract: For optimization models to be used in practice, it is crucial that users trust the results. A key factor in...
arXiv:2404.18104v2 Announce Type: replace-cross Abstract: The relevance of shallow-depth quantum circuits has recently increased, mainly due to their applicability to near-term devices. In this context,...
arXiv:2403.17770v3 Announce Type: replace-cross Abstract: Despite the significant success achieved by deep learning methods in medical image segmentation, researchers still struggle in the computer-aided diagnosis...
arXiv:2309.04414v3 Announce Type: replace-cross Abstract: The expectation that scientific productivity follows regular patterns over a career underpins many scholarly evaluations. However, recent studies of individual...
arXiv:2306.14851v4 Announce Type: replace-cross Abstract: Given a high-dimensional covariate matrix and a response vector, ridge-regularized sparse linear regression selects a subset of features that explains...
arXiv:2211.03997v3 Announce Type: replace-cross Abstract: Online platforms increasingly rely on sequential decision-making algorithms to allocate resources, match users, or control exposure, while facing growing pressure...
arXiv:2106.14010v4 Announce Type: replace-cross Abstract: In 2019 P. Patak and M. Tancer obtained the following higher-dimensional generalization of the Heawood inequality on embeddings of graphs...
arXiv:2602.11136v2 Announce Type: replace Abstract: As LLM-based agents increasingly operate in high-stakes domains with real-world consequences, ensuring their behavioral safety becomes paramount. The dominant oversight...
arXiv:2602.11106v2 Announce Type: replace Abstract: Misinformation detection is a critical task that can benefit significantly from the integration of external knowledge, much like manual fact-checking....
arXiv:2602.11073v2 Announce Type: replace Abstract: Current large vision-language models (LVLMs) typically rely on text-only reasoning based on a single-pass visual encoding, which often leads to...
arXiv:2602.11063v2 Announce Type: replace Abstract: To ensure frequency security in power systems, both the rate of change of frequency (RoCoF) and the frequency nadir (FN)...
arXiv:2602.11047v2 Announce Type: replace Abstract: We frame embedding inversion as conditional masked diffusion, recovering all tokens in parallel through iterative denoising rather than sequential autoregressive...