Tootfinder

CLARSTA: A random subspace trust-region algorithm for convex-constrained derivative-free optimization
Yiwen Chen, Warren Hare, Amy Wiebe
https://arxiv.org/abs/2506.20335

CLARSTA: A random subspace trust-region algorithm for convex-constrained derivative-free optimization
This paper proposes a random subspace trust-region algorithm for general convex-constrained derivative-free optimization (DFO) problems. Similar to previous random subspace DFO methods, the convergence of our algorithm requires a certain accuracy of models and a certain quality of subspaces. For model accuracy, we define a new class of models that is only required to provide reasonable accuracy on the projection of the constraint set onto the subspace. We provide a new geometry measure to make …

Global Convergence of Iteratively Reweighted Least Squares for Robust Subspace Recovery
Gilad Lerman, Kang Li, Tyler Maunu, Teng Zhang
https://arxiv.org/abs/2506.20533

Global Convergence of Iteratively Reweighted Least Squares for Robust Subspace Recovery
Robust subspace estimation is fundamental to many machine learning and data analysis tasks. Iteratively Reweighted Least Squares (IRLS) is an elegant and empirically effective approach to this problem, yet its theoretical properties remain poorly understood. This paper establishes that, under deterministic conditions, a variant of IRLS with dynamic smoothing regularization converges linearly to the underlying subspace from any initialization. We extend these guarantees to affine subspace estima…

Dynamic Context-Aware Prompt Recommendation for Domain-Specific AI Applications
Xinye Tang, Haijun Zhai, Chaitanya Belwal, Vineeth Thayanithi, Philip Baumann, Yogesh K Roy
https://arxiv.org/abs/2506.20815

Dynamic Context-Aware Prompt Recommendation for Domain-Specific AI Applications
LLM-powered applications are highly susceptible to the quality of user prompts, and crafting high-quality prompts can often be challenging especially for domain-specific applications. This paper presents a novel dynamic context-aware prompt recommendation system for domain-specific AI applications. Our solution combines contextual query analysis, retrieval-augmented knowledge grounding, hierarchical skill organization, and adaptive skill ranking to generate relevant and actionable prompt sugges…

Unfolding Iterators: Specification and Verification of Higher-Order Iterators, in OCaml
Ion Chirica, M\'ario Pereira
https://arxiv.org/abs/2506.20310 h…

Unfolding Iterators: Specification and Verification of Higher-Order Iterators, in OCaml
Albeit being a central notion of every programming language, formally and modularly reasoning about iteration proves itself to be a non-trivial feat, specially in the context of higher-order iteration. In this paper, we present a generic approach to the specification and deductive verification of higher-order iterators, written in the OCaml language. Our methodology follows two key principles: first, the usage of the Gospel specification language to describe the general behaviour of any iterati…

»Nach über zwanzig Jahren – Zeit für ein neues PNG:
Mit der dritten Ausgabe aktualisiert das W3C jetzt die PNG-Spezifikation. Das Bildformat umfasst jetzt APNGs, HDR-Support und unterstützt Exif-Daten.«
Huch schon 20 Jahre her und nun eine neuer Version von @… neben den einigen weiteren für Web optimierte Images Formate. Mal sehen bis wann dies populäre Browser die…

Nach über zwanzig Jahren: Zeit für ein neues PNG
Mit der dritten Ausgabe aktualisiert das W3C jetzt die PNG-Spezifikation. Das Bildformat umfasst jetzt APNGs, HDR-Support und unterstützt Exif-Daten.

Claiming back space for people. Seen in Stockholm.

GGTalker: Talking Head Systhesis with Generalizable Gaussian Priors and Identity-Specific Adaptation
Wentao Hu, Shunkai Li, Ziqiao Peng, Haoxian Zhang, Fan Shi, Xiaoqiang Liu, Pengfei Wan, Di Zhang, Hui Tian
https://arxiv.org/abs/2506.21513

GGTalker: Talking Head Systhesis with Generalizable Gaussian Priors and Identity-Specific Adaptation
Creating high-quality, generalizable speech-driven 3D talking heads remains a persistent challenge. Previous methods achieve satisfactory results for fixed viewpoints and small-scale audio variations, but they struggle with large head rotations and out-of-distribution (OOD) audio. Moreover, they are constrained by the need for time-consuming, identity-specific training. We believe the core issue lies in the lack of sufficient 3D priors, which limits the extrapolation capabilities of synthesized…

Healthy European peatlands require specific temperature and water level parameters #Europe

Healthy European peatlands require specific temperature and water level parameters
Efforts to enhance peat accumulation in European peatlands, which contain around half of Europe's soil carbon, will require a combination of warm temperatures and a specific depth of the water table, according to a study published in PLOS One by Graeme Swindles of Queen's University Belfast, U.K. and colleagues.

This https://arxiv.org/abs/2307.10434 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csFL_…

Learning Formal Specifications from Membership and Preference Queries
Active learning is a well-studied approach to learning formal specifications, such as automata. In this work, we extend active specification learning by proposing a novel framework that strategically requests a combination of membership labels and pair-wise preferences, a popular alternative to membership labels. The combination of pair-wise preferences and membership labels allows for a more flexible approach to active specification learning, which previously relied on membership labels only. …

#TGIQF: Spaceballs - Das Quiz
Spaceballs 2 kommt 2027 in die Kinos – Mel Brooks' Kultkomödie wird nach 40 Jahren endlich fortgesetzt. Wir feiern mit einem Spaceballs-Quiz. Machen Sie mit!