Tootfinder

Medien: Kiew wurden zwei Optionen für Waffenruhe vorgeschlagen
Russische Unterhändler haben der Ukraine laut Berichten staatlicher russischer Medien zwei Optionen für eine Waffenruhe vorgeschlagen. Die erste Option macht demnach zur Bedingung, dass die Ukraine mit einem Abzug all ihrer Truppen aus den vier ukrainischen Regionen beginnt, die Russland für sich beansprucht. Die zweite Option wäre Teil eines größeren Pakets, das …
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Ukraine-Liveblog: ++ US-Senator Graham rechnet mit scharfen Sanktionen ++
Der republikanische US-Senator Graham zeigt sich in den tagesthemen zuversichtlich, dass scharfe US-Sanktionen gegen Moskau verabschiedet werden. Außenminister Wadephul betont, dass Europa und die USA den Druck auf Putin aufrechterhalten müssen.

This https://arxiv.org/abs/2505.01892 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

OODTE: A Differential Testing Engine for the ONNX Optimizer
With over 700 stars on GitHub and being part of the official ONNX repository, the ONNX Optimizer is the default tool for applying graph-based optimizations to ONNX models. Despite its widespread use, its ability to maintain model accuracy during optimization has not been thoroughly investigated. In this work, we present OODTE, a utility designed to automatically and comprehensively evaluate the correctness of the ONNX Optimizer. OODTE adopts a straightforward yet powerful differential testing a…

USB-C-Mindestanforderungen für Windows-11-Notebooks werden zur Pflicht
Microsoft will das USB-C-Chaos bei Windows-11-Notebooks auflösen. Bisher optionale Leistungsparameter sollen künftig zur Pflicht werden. 

Optimal T depth quantum circuits for implementing arbitrary Boolean functions
Suman Dutta, Anik Basu Bhaumik, Anupam Chattopadhyay, Subhamoy Maitra
https://arxiv.org/abs/2506.01542

Optimal T depth quantum circuits for implementing arbitrary Boolean functions
In this paper we present a generic construction to obtain an optimal T depth quantum circuit for any arbitrary $n$-input $m$-output Boolean function $f: \{0,1\}^n \rightarrow \{0,1\}^m$ having algebraic degree $k\leq n$, and it achieves an exact Toffoli (and T) depth of $\lceil \log_2 k \rceil$. This is a broader generalization of the recent result establishing the optimal Toffoli (and consequently T) depth for multi-controlled Toffoli decompositions (Dutta et al., Phys. Rev. A, 2025). We achie…

SysLLMatic: Large Language Models are Software System Optimizers
Huiyun Peng, Arjun Gupte, Ryan Hasler, Nicholas John Eliopoulos, Chien-Chou Ho, Rishi Mantri, Leo Deng, Konstantin L\"aufer, George K. Thiruvathukal, James C. Davis
https://arxiv.org/abs/2506.01249

SysLLMatic: Large Language Models are Software System Optimizers
Automatic software system optimization can improve software speed, reduce operating costs, and save energy. Traditional approaches to optimization rely on manual tuning and compiler heuristics, limiting their ability to generalize across diverse codebases and system contexts. Recent methods using Large Language Models (LLMs) offer automation to address these limitations, but often fail to scale to the complexity of real-world software systems and applications. We present SysLLMatic, a system th…

Learning to optimize convex risk measures: The cases of utility-based shortfall risk and optimized certainty equivalent risk
Sumedh Gupte, Prashanth L. A., Sanjay P. Bhat
https://arxiv.org/abs/2506.01101

Learning to optimize convex risk measures: The cases of utility-based shortfall risk and optimized certainty equivalent risk
We consider the problems of estimation and optimization of two popular convex risk mea- sures: utility-based shortfall risk (UBSR) and Optimized Certainty Equivalent (OCE) risk. We extend these risk measures to cover possibly unbounded random variables. We cover prominent risk measures like the entropic risk, expectile risk, monotone mean-variance risk, Value-at-Risk, and Conditional Value-at-Risk as few special cases of either the UBSR or the OCE risk. In the context of estimation, we derive n…

Smooth Logic Constraints in Nonlinear Optimization and Optimal Control Problems
J. Wehbeh, E. C. Kerrigan
https://arxiv.org/abs/2506.01742 https://

Smooth Logic Constraints in Nonlinear Optimization and Optimal Control Problems
In some optimal control problems, complex relationships between states and inputs cannot be easily represented using continuous constraints, necessitating the use of discrete logic instead. This paper presents a method for incorporating such logic constraints directly within continuous optimization frameworks, eliminating the need for binary variables or specialized solvers. Our approach reformulates arbitrary logic constraints under minimal assumptions as max-min constraints, which are then sm…

Attention-Aided MMSE for OFDM Channel Estimation: Learning Linear Filters with Attention
TaeJun Ha, Chaehyun Jung, Hyeonuk Kim, Jeongwoo Park, Jeonghun Park
https://arxiv.org/abs/2506.00452

Attention-Aided MMSE for OFDM Channel Estimation: Learning Linear Filters with Attention
In orthogonal frequency division multiplexing (OFDM), accurate channel estimation is crucial. Classical signal processing based approaches, such as minimum mean-squared error (MMSE) estimation, often require second-order statistics that are difficult to obtain in practice. Recent deep neural networks based methods have been introduced to address this; yet they often suffer from high complexity. This paper proposes an Attention-aided MMSE (A-MMSE), a novel model-based DNN framework that learns t…

AJ Cole estš ‘optimista’ después de firmar extensión https://www.raiders.com/news/aj-cole-esta-optimista-despues-de-firmar-extension

AJ Cole estš ‘optimista’ después de firmar extensión https://www.raiders.com/news/aj-cole-esta-optimista-despues-de-firmar-extension