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arXiv:2210.05607v2 Announce Type: replace Abstract: Stochastic optimization algorithms using exponential moving averages of the past gradients, such as ADAM, RMSProp and AdaGrad, have been having...
arXiv:2302.11250v2 Announce Type: replace Abstract: A debt swap is an elementary edge swap in a directed, weighted graph, where two edges with the same weight...
arXiv:2306.10432v4 Announce Type: replace Abstract: Automatic structures are first-order structures whose universe and relations can be represented as regular languages. It follows from the standard...
arXiv:2309.16117v2 Announce Type: replace Abstract: Continual learning (CL) aims to learn new tasks without erasing previous knowledge. However, current CL methods primarily emphasize improving accuracy...
arXiv:2311.01591v5 Announce Type: replace Abstract: Graph Neural Networks (GNNs) have achieved state-of-the-art results in many relevant tasks where decisions might disproportionately impact specific communities. However,...
arXiv:2312.08410v4 Announce Type: replace Abstract: We introduce a Banach space-valued extension of random feature learning, a data-driven supervised machine learning technique for large-scale kernel approximation....
arXiv:2401.08742v5 Announce Type: replace Abstract: Generating dynamic 3D object from a single-view video is challenging due to the lack of 4D labeled data. An intuitive...
arXiv:2402.04177v3 Announce Type: replace Abstract: Scaling laws provide important insights that can guide the design of large language models (LLMs). Existing work has primarily focused...
arXiv:2403.05888v5 Announce Type: replace Abstract: In this paper, we propose a class of nonlocal models to approximate the Poisson model on manifolds with homogeneous Neumann...
arXiv:2403.14124v2 Announce Type: replace Abstract: Point cloud processing methods leverage local and global point features %at the feature level to cater to downstream tasks, yet...
arXiv:2403.15711v2 Announce Type: replace Abstract: Causal representation learning (CRL) offers the promise of uncovering the underlying causal model by which observed data was generated, but...
arXiv:2404.00032v2 Announce Type: replace Abstract: Despite the rapid development of AI models in medical image analysis, their validation in real-world clinical settings remains limited. To...
arXiv:2404.10064v2 Announce Type: replace Abstract: Satisfying safety constraints is a priority concern when solving optimal control problems (OCPs). Due to the existence of infeasibility phenomenon,...
arXiv:2404.13318v5 Announce Type: replace Abstract: The increasing volume of electronic health records (EHRs) presents the opportunity to improve the accuracy and robustness of models in...
arXiv:2405.03456v2 Announce Type: replace Abstract: Matrix-vector multiplication forms the basis of many iterative solution algorithms and as such is an important algorithm also for hierarchical...
arXiv:2405.12193v2 Announce Type: replace Abstract: The transformative potential of AI presents remarkable opportunities, but also significant risks, underscoring the importance of responsible AI development and...
arXiv:2406.08440v2 Announce Type: replace Abstract: Simulating physical systems is essential in engineering, but analytical solutions are limited to straightforward problems. Consequently, numerical methods like the...
arXiv:2407.00005v2 Announce Type: replace Abstract: For image-related deep learning tasks, the first step often involves reading data from external storage and performing preprocessing on the...
arXiv:2407.04969v4 Announce Type: replace Abstract: Since LLMs emerged, more attention has been paid to abstractive long-form summarization, where longer input sequences indicate more information contained....
arXiv:2407.11823v3 Announce Type: replace Abstract: The United States Food and Drug Administration's (FDA's) 510(k) pathway allows manufacturers to gain medical device approval by demonstrating substantial...
arXiv:2407.19169v2 Announce Type: replace Abstract: When simulating hyperbolic conservation laws with discontinuous solutions, high-order linear numerical schemes often produce undesirable spurious oscillations. In this paper,...
arXiv:2407.21666v3 Announce Type: replace Abstract: Early detection of drought stress is critical for taking timely measures for reducing crop loss before the drought impact becomes...
arXiv:2408.06787v5 Announce Type: replace Abstract: Traditional knowledge graph completion (KGC) methods rely solely on structural information and struggle with sparsity, while Large Language Models (LLMs)...
arXiv:2408.15578v3 Announce Type: replace Abstract: Spiking Neural Networks (SNNs), with brain-inspired structure using discrete spikes instead of continuous activations, are gaining attention for their efficient...