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arXiv:2602.10239v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has rapidly become a standard for high-fidelity 3D reconstruction, yet its adoption in multiple critical domains...
arXiv:2602.10246v1 Announce Type: new Abstract: Solid State Drives (SSDs) are critical to datacenters, consumer platforms, and mission-critical systems. Yet diagnosing their performance and reliability is...
arXiv:2602.10247v1 Announce Type: new Abstract: The Bayesian approach to inverse problems provides a practical way to solve ill-posed problems by augmenting the observation model with...
arXiv:2602.10248v1 Announce Type: new Abstract: We study the problem of selecting the shape parameter in Radial Basis function (RBF) interpolation using leave-one-out-cross-validation (LOOCV). Since the...
arXiv:2602.10249v1 Announce Type: new Abstract: In this paper, we propose a context-aware recommender system that models students' programming skills using embeddings of the source code...
arXiv:2602.10250v1 Announce Type: new Abstract: As 3GPP systems have strengthened security at the upper layers of the cellular stack, plaintext PHY and MAC layers have...
arXiv:2602.10251v1 Announce Type: new Abstract: AI chatbots are widely used by children and teens today, but they pose significant risks to youth's privacy and safety...
arXiv:2602.10252v1 Announce Type: new Abstract: Datacenter networks are currently locked in a "tyranny of the single objective". While modern workloads demand diverse performance goals, ranging...
arXiv:2602.10253v1 Announce Type: new Abstract: We investigate the parameterized complexity of Bayesian Network Structure Learning (BNSL), a classical problem that has received significant attention in...
arXiv:2602.10254v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) layers activate a subset of model weights, dubbed experts, to improve model performance. MoE is particularly promising for...
arXiv:2602.10258v1 Announce Type: new Abstract: Despite filtered nearest neighbor search being a fundamental task in modern vector search systems, the performance of existing algorithms is...
arXiv:2602.10259v1 Announce Type: new Abstract: This study introduces a new object detection dataset of pedestrians using mobility aids, named PMMA. The dataset was collected in...
arXiv:2602.10261v1 Announce Type: new Abstract: Kernel methods have been extensively utilized in machine learning for classification and prediction tasks due to their ability to capture...
arXiv:2602.10262v1 Announce Type: new Abstract: The AMD MI300A APU integrates CDNA3 GPUs with high-bandwidth memory and advanced accelerator features: FP8 matrix cores, asynchronous compute engines...
arXiv:2602.10265v1 Announce Type: new Abstract: Neural-network-based diagnosis from dermatoscopic images is increasingly used for clinical decision support, yet studies report performance disparities across skin tones....
arXiv:2602.10266v1 Announce Type: new Abstract: This chapter explores neural networks, topological data analysis, and topological deep learning techniques, alongside statistical Bayesian methods, for processing images,...
arXiv:2602.10268v1 Announce Type: new Abstract: We develop an efficient, unconditionally stable, variable step second order exponential time differencing scheme for the incompressible Navier Stokes equations...
arXiv:2602.10271v1 Announce Type: new Abstract: Understanding multimodal long-context documents that comprise multimodal chunks such as paragraphs, figures, and tables is challenging due to (1) cross-modal...
arXiv:2602.10272v1 Announce Type: new Abstract: 5G presents numerous advantages compared to previous generations: improved throughput, lower latency, and improved privacy protection for subscribers. Attacks against...
arXiv:2602.10277v1 Announce Type: new Abstract: This work is concerned with the problem of blind source separation and its applications to imaging. We first establish a...
arXiv:2602.10278v1 Announce Type: new Abstract: Generating 3D content from a single image remains a fundamentally challenging and ill-posed problem due to the inherent absence of...
arXiv:2602.10282v1 Announce Type: new Abstract: Large language models (LLMs) have shown potential in identifying qualitative causal relations, but their ability to perform quantitative causal reasoning...
arXiv:2602.10285v1 Announce Type: new Abstract: Autonomous driving requires reasoning about interactions with surrounding traffic. A prevailing approach is large-scale imitation learning on expert driving datasets,...
arXiv:2602.10286v1 Announce Type: new Abstract: Pairwise preference learning is central to machine learning, with recent applications in aligning language models with human preferences. A typical...