arXiv:2602.15049v1 Announce Type: new Abstract: Optimal Access Point (AP) selection is crucial for accurate indoor localization, yet it is constrained by budget, creating a trade-off between localization accuracy and deployment cost. Classical approaches to AP selection are often computationally expensive, hindering their application in large-scale 3D indoor environments. In this paper, we introduce a quantum APs selection algorithm under a budget constraint. The proposed algorithm leverages quantum annealing to identify the most effective subset of APs allowed within […]

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arXiv:2601.08006v1 Announce Type: new Abstract: The Rosenbluth-Fokker-Planck (RFP) equation describes Coulomb collisional dynamics within and across species in plasmas. It belongs to the broader class of anisotropic-diffusion-advection equations, whose numerical approximation is highly-nontrivial due to its nonlinearity, stiffness, and structural properties such as conservation and entropy dissipation (hence with the Maxwellian distribution as the equilibrium state). In this paper, we propose a structure-preserving penalization scheme for the stiff, single-species RFP equation. The scheme features three novel components: 1) […]

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One of the fiddly parts of regular expressions is how to handle line breaks. Should regular expression searches be applied one line at a time, or should an entire file be treated as a single line? This morning I was trying to track down a LaTeX file that said “discussed in the Section” rather than simply “discussed in Section.” I wanted to search on “the Section” to see whether I had a similar error in other files. Line […]

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Weight regularization methods in continual learning (CL) alleviate catastrophic forgetting by assessing and penalizing changes to important model weights. Elastic Weight Consolidation (EWC) is a foundational and widely used approach within this framework that estimates weight importance based on gradients. However, it has consistently shown suboptimal performance. In this paper, we conduct a systematic analysis of importance estimation in EWC from a gradient-based perspective. For the first time, we find that EWC’s reliance on the Fisher Information Matrix […]

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arXiv:2602.15155v1 Announce Type: new Abstract: Implicit Neural Representations (INRs) have emerged as promising surrogates for large 3D scientific simulations due to their ability to continuously model spatial and conditional fields, yet they face a critical fidelity-speed dilemma: deep MLPs suffer from high inference cost, while efficient embedding-based models lack sufficient expressiveness. To resolve this, we propose the Decoupled Representation Refinement (DRR) architectural paradigm. DRR leverages a deep refiner network, alongside non-parametric transformations, in a one-time offline process to […]

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arXiv:2601.15352v1 Announce Type: new Abstract: Loop vulnerabilities are one major risky construct in software development. They can easily lead to infinite loops or executions, exhaust resources, or introduce logical errors that degrade performance and compromise security. The problem are often undetected by traditional static analyzers because such tools rely on syntactic patterns, which makes them struggle to detect semantic flaws. Consequently, Large Language Models (LLMs) offer new potential for vulnerability detection because of their ability to understand code […]

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Explainable Boosting Machines (EBMs) provide transparent predictions through additive shape functions, enabling direct inspection of feature contributions. However, EBMs can learn non-physical relationships that reduce their reliability in natural hazard applications. This study presents a domain-informed framework to improve the physical consistency of EBMs for lateral spreading prediction. Our approach modifies learned shape functions based on domain knowledge. These modifications correct non-physical behavior while maintaining data-driven patterns. We apply the method to the 2011 Christchurch earthquake dataset and […]

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Hey folks! I’ve compiled a list of available RL-related position in game studios worldwide. I’m sure I captured the majority of positions on the market, although if I missed something please comment below. RL positions are extremely rare so I hope it will be useful to somebody Original list on LinkedIn: https://www.linkedin.com/posts/viktor-zatorskyi_rl-activity-7416719619899576321-X_Tq submitted by /u/bmind7 [link] [comments]

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In-context learning (ICL) adapts large language models by conditioning on a small set of ICL examples, avoiding costly parameter updates. Among other factors, performance is often highly sensitive to the ordering of the examples. However, exhaustive search over the $n!$ possible orderings is infeasible. Therefore more efficient ordering methods use model confidence measures (e.g., label-probability entropy) over label sets or take a direct approach to finding the best ordering. We propose PLR, a probabilistic approach to in-context example […]

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:::info Astounding Stories of Super-Science April 2004, by Astounding Stories is part of HackerNoon’s Book Blog Post series. You can jump to any chapter in this book here. THE COUNTRY OF THE BLIND – VIII. — THE LORD OF THE DYNAMOS. Astounding Stories of Super-Science April 2004: THE COUNTRY OF THE BLIND – VIII. — THE LORD OF THE DYNAMOS. By H. G. Wells ::: The chief attendant of the three dynamos that buzzed and rattled at Camberwell, and […]

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