Tootfinder

Russia jails former top general for 17 years in massive military graft case: https://benborges.xyz/2025/07/08/russia-jails-former-top-general.html

Fair Domain Generalization: An Information-Theoretic View
Tangzheng Lian, Guanyu Hu, Dimitrios Kollias, Xinyu Yang, Oya Celiktutan
https://arxiv.org/abs/2507.05823

Fair Domain Generalization: An Information-Theoretic View
Domain generalization (DG) and algorithmic fairness are two critical challenges in machine learning. However, most DG methods focus only on minimizing expected risk in the unseen target domain without considering algorithmic fairness. Conversely, fairness methods typically do not account for domain shifts, so the fairness achieved during training may not generalize to unseen test domains. In this work, we bridge these gaps by studying the problem of Fair Domain Generalization (FairDG), which ai…

Attorney General Bonta, Governor Newsom Challenge Trump Order Seeking to Federalize California National Guard (State of California)
https://oag.ca.gov/news/press-releases/attorney-general-bonta-governor-newsom-challenge-trump-order-seeking-federalize
http://www.memeorandum.com/250609/p96#a250609p96

General Staff: Russia has lost 1,028,610 troops in Ukraine since Feb. 24, 2022: https://benborges.xyz/2025/07/08/general-staff-russia-has-lost.html

On the completeness of the $\delta_{KLS}$-generalized statistical field theory
P. R. S. Carvalho
https://arxiv.org/abs/2506.05537 https://

On the completeness of the $δ_{KLS}$-generalized statistical field theory
In this work we introduce a field-theoretic tool that enable us to evaluate the critical exponents of $δ_{KLS}$-generalized systems undergoing continuous phase transitions, namely $δ_{KLS}$-generalized statistical field theory. It generalizes the standard Boltzmann-Gibbs through the introduction of the $δ_{KLS}$ parameter from which Boltzmann-Gibbs statistics is recovered in the limit $δ_{KLS}\rightarrow 0$. From the results for the critical exponents we provide the referred physical interp…

The Treasury’s Office of Foreign Assets Control (OFAC) sanctioned Song Kum Hyok (Song), a malicious cyber actor associated with the sanctioned Democratic People’s Republic of Korea (DPRK) Reconnaissance General Bureau (RGB) hacking group Andariel.
https://home.treasury.gov/news/press-rel…

Sanctions Imposed on DPRK IT Workers Generating Revenue for the Kim Regime
WASHINGTON — Today, the U.S. Department of the Treasury’s Office of Foreign Assets Control (OFAC) sanctioned Song Kum Hyok, (Song), a malicious cyber actor associated with the sanctioned Democratic People’s Republic of Korea (DPRK) Reconnaissance General Bureau (RGB) hacking group Andariel.Song facilitated an information technology (IT) worker scheme in which individuals, often DPRK nationals working from countries such as China and Russia, were recruited and provided with falsified ident…

General Staff: Russia has lost 1,029,660 troops in Ukraine since Feb. 24, 2022: https://benborges.xyz/2025/07/09/general-staff-russia-has-lost.html

LightGTS: A Lightweight General Time Series Forecasting Model
Yihang Wang, Yuying Qiu, Peng Chen, Yang Shu, Zhongwen Rao, Lujia Pan, Bin Yang, Chenjuan Guo
https://arxiv.org/abs/2506.06005

LightGTS: A Lightweight General Time Series Forecasting Model
Existing works on general time series forecasting build foundation models with heavy model parameters through large-scale multi-source pre-training. These models achieve superior generalization ability across various datasets at the cost of significant computational burdens and limitations in resource-constrained scenarios. This paper introduces LightGTS, a lightweight general time series forecasting model designed from the perspective of consistent periodical modeling. To handle diverse scales…

General Staff: Russia has lost 1,027,540 troops in Ukraine since Feb. 24, 2022: https://benborges.xyz/2025/07/07/general-staff-russia-has-lost.html

Lagrangian-based Equilibrium Propagation: generalisation to arbitrary boundary conditions & equivalence with Hamiltonian Echo Learning
Guillaume Pourcel, Debabrota Basu, Maxence Ernoult, Aditya Gilra
https://arxiv.org/abs/2506.06248

Lagrangian-based Equilibrium Propagation: generalisation to arbitrary boundary conditions & equivalence with Hamiltonian Echo Learning
Equilibrium Propagation (EP) is a learning algorithm for training Energy-based Models (EBMs) on static inputs which leverages the variational description of their fixed points. Extending EP to time-varying inputs is a challenging problem, as the variational description must apply to the entire system trajectory rather than just fixed points, and careful consideration of boundary conditions becomes essential. In this work, we present Generalized Lagrangian Equilibrium Propagation (GLEP), which e…