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Technion - Israel Institute of Technology(以色列理工学院)

2026-02-27 至 2026-02-27 共收录 4
2602.23073 2026-02-27 math.ST cs.AI stat.TH

Accelerated Online Risk-Averse Policy Evaluation in POMDPs with Theoretical Guarantees and Novel CVaR Bounds

在POMDP中具有理论保证和新型CVaR界限的加速在线风险厌恶策略评估

Yaacov Pariente, Vadim Indelman

机构 * Technion - Israel Institute of Technology(技术学院-以色列理工学院)

AI总结 本文提出了一种在POMDP中加速风险厌恶策略评估的方法,通过理论保证和新的CVaR界限,实现计算效率的提升。

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2602.23017 2026-02-27 cs.RO

DigiArm: An Anthropomorphic 3D-Printed Prosthetic Hand with Enhanced Dexterity for Typing Tasks

DigiArm: 一种具有增强灵活性的3D打印仿人假手,适用于打字任务

Dean Zadok, Tom Naamani, Yuval Bar-Ratson, Elisha Barash, Oren Salzman, Alon Wolf, Alex M. Bronstein, Nili Krausz

机构 * Department of Computer Science, Technion, Haifa, Israel(计算机科学系,技术学院,海法,以色列) Department of Mechanical Engineering, Technion, Haifa, Israel(机械工程系,技术学院,海法,以色列)

AI总结 DigiArm是一种低成本3D打印假手,专为提高打字任务的灵活性而设计,通过增强手指和腕部控制实现精确操作。

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2505.04733 2026-02-27 cs.LG

Conformal Prediction with Corrupted Labels: Uncertain Imputation and Robust Re-weighting

带有损坏标签的置信预测:不确定填补与鲁棒再加权

Shai Feldman, Stephen Bates, Yaniv Romano

机构 * Department of Computer Science(计算机科学系) Technion, Israel(技术学院,以色列) Department of Electrical Engineering and Computer Science(电气工程与计算机科学系) Massachusetts Institute of Technology(麻省理工学院) Departments of Electrical and Computer Engineering and of Computer Science(电气工程与计算机科学系)

AI总结 本文提出了一种在标签损坏情况下鲁棒的置信预测方法,通过不确定填补和鲁棒再加权技术,确保预测的有效性。

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2602.22275 2026-02-27 eess.IV cs.GR cs.LG

Deep Accurate Solver for the Geodesic Problem

基于深度学习的测地问题精确求解器

Saar Huberman, Amit Bracha, Ron Kimmel

机构 * Technion - Israel Institute of Technology(技术学院-以色列理工学院)

AI总结 本文提出了一种基于深度学习的第三阶准确测地距离求解器,通过神经网络隐式近似连续表面结构,提升了求解精度。

Comments Extended version of Deep Accurate Solver for the Geodesic Problem originally published in Scale Space and Variational Methods in Computer Vision (SSVM 2023), Lecture Notes in Computer Science, Springer. This version includes additional experiments and detailed analysis

Journal ref Scale Space and Variational Methods in Computer Vision (SSVM 2023), Lecture Notes in Computer Science, vol. 14009, Springer

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