Tootfinder

CISA staff who were furloughed could soon be back in the saddle.
https://www.nytimes.com/2026/03/27/us/politics/senate-dhs-ice-shutdown-funding.html

Senate Votes to Fund Most of D.H.S. in Bid to End Partial Shutdown
The bill excludes funding for ICE and the Border Patrol but restores it for federal airport security workers. The House could consider the package on Friday.

#FotoVorschlag #Lichtkunst
Spätabendlicher Rücktransport des #ProVeloZürich Eventstandes ins Lager mit einem Lastenrad und einem Tourenrad mit je einem Lastenanhänger mit hellen Rückleu…

#Bremen stattet #Straßenbahnen mit dem KI System #AIWatch aus, das Situationen in Echtzeit analysieren und bei möglicher

Algorithmen auf Streife: Bremens Straßenbahnen werden zur KI-Überwachungszone
Mit AI-Watch führt die BSAG eine Echtzeit-Analyse von Fahrgästen ein. Was als Sicherheitsgewinn verkauft wird, markiert eine neue Stufe der Videoüberwachung.

There is no reason to think that Markwayne Mullin will change course in any significant way at DHS.
Like Kristy Noem, he will be answering primarily to White House deputy chief of staff Stephen Miller, a man who spends all day on X implying that non-white immigrants are the primary source of crime and economic deprivation.
Miller’s demand that Immigration and Customs Enforcement, which is overseen by DHS,
arrest 3,000 people a day is the force behind Noem’s worst choices a…

ICE “course correction”? Markwayne Mullin isn't it
The department of homeland security shutdown shows Republicans still answer to Stephen Miller

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[2/6]:
- Performance Asymmetry in Model-Based Reinforcement Learning
Jing Yu Lim, Rushi Shah, Zarif Ikram, Samson Yu, Haozhe Ma, Tze-Yun Leong, Dianbo Liu
https://arxiv.org/abs/2505.19698 https://mastoxiv.page/@arXiv_csLG_bot/114578810521008766
- Towards Robust Real-World Multivariate Time Series Forecasting: A Unified Framework for Dependenc...
Jinkwan Jang, Hyungjin Park, Jinmyeong Choi, Taesup Kim
https://arxiv.org/abs/2506.08660 https://mastoxiv.page/@arXiv_csLG_bot/114664238967892509
- Wasserstein Barycenter Soft Actor-Critic
Zahra Shahrooei, Ali Baheri
https://arxiv.org/abs/2506.10167 https://mastoxiv.page/@arXiv_csLG_bot/114675175949432731
- Foundation Models for Causal Inference via Prior-Data Fitted Networks
Yuchen Ma, Dennis Frauen, Emil Javurek, Stefan Feuerriegel
https://arxiv.org/abs/2506.10914 https://mastoxiv.page/@arXiv_csLG_bot/114675529854402158
- FREQuency ATTribution: benchmarking frequency-based occlusion for time series data
Dominique Mercier, Andreas Dengel, Sheraz Ahmed
https://arxiv.org/abs/2506.18481 https://mastoxiv.page/@arXiv_csLG_bot/114738421450807709
- Complexity-aware fine-tuning
Andrey Goncharov, Daniil Vyazhev, Petr Sychev, Edvard Khalafyan, Alexey Zaytsev
https://arxiv.org/abs/2506.21220 https://mastoxiv.page/@arXiv_csLG_bot/114754764750730849
- Transfer Learning in Infinite Width Feature Learning Networks
Clarissa Lauditi, Blake Bordelon, Cengiz Pehlevan
https://arxiv.org/abs/2507.04448 https://mastoxiv.page/@arXiv_csLG_bot/114818005803079705
- A hierarchy tree data structure for behavior-based user segment representation
Liu, Kang, Iyer, Malik, Li, Wang, Lu, Zhao, Wang, Liu, Liu, Liang, Yu
https://arxiv.org/abs/2508.01115 https://mastoxiv.page/@arXiv_csLG_bot/114975999992144374
- One-Step Flow Q-Learning: Addressing the Diffusion Policy Bottleneck in Offline Reinforcement Lea...
Thanh Nguyen, Chang D. Yoo
https://arxiv.org/abs/2508.13904 https://mastoxiv.page/@arXiv_csLG_bot/115060568241390847
- Uncertainty Propagation Networks for Neural Ordinary Differential Equations
Hadi Jahanshahi, Zheng H. Zhu
https://arxiv.org/abs/2508.16815 https://mastoxiv.page/@arXiv_csLG_bot/115094785677272005
- Learning Unified Representations from Heterogeneous Data for Robust Heart Rate Modeling
Zhengdong Huang, Zicheng Xie, Wentao Tian, Jingyu Liu, Lunhong Dong, Peng Yang
https://arxiv.org/abs/2508.21785 https://mastoxiv.page/@arXiv_csLG_bot/115128450608548173
- Monte Carlo Tree Diffusion with Multiple Experts for Protein Design
Liu, Cao, Jiang, Luo, Duan, Wang, Sosnick, Xu, Stevens
https://arxiv.org/abs/2509.15796 https://mastoxiv.page/@arXiv_csLG_bot/115247429156900905
- From Samples to Scenarios: A New Paradigm for Probabilistic Forecasting
Xilin Dai, Zhijian Xu, Wanxu Cai, Qiang Xu
https://arxiv.org/abs/2509.19975 https://mastoxiv.page/@arXiv_csLG_bot/115264498084813952
- Why High-rank Neural Networks Generalize?: An Algebraic Framework with RKHSs
Yuka Hashimoto, Sho Sonoda, Isao Ishikawa, Masahiro Ikeda
https://arxiv.org/abs/2509.21895 https://mastoxiv.page/@arXiv_csLG_bot/115287261047939306
- From Parameters to Behaviors: Unsupervised Compression of the Policy Space
Davide Tenedini, Riccardo Zamboni, Mirco Mutti, Marcello Restelli
https://arxiv.org/abs/2509.22566 https://mastoxiv.page/@arXiv_csLG_bot/115287379672141023
- RHYTHM: Reasoning with Hierarchical Temporal Tokenization for Human Mobility
Haoyu He, Haozheng Luo, Yan Chen, Qi R. Wang
https://arxiv.org/abs/2509.23115 https://mastoxiv.page/@arXiv_csLG_bot/115293273559547106
- Polychromic Objectives for Reinforcement Learning
Jubayer Ibn Hamid, Ifdita Hasan Orney, Ellen Xu, Chelsea Finn, Dorsa Sadigh
https://arxiv.org/abs/2509.25424 https://mastoxiv.page/@arXiv_csLG_bot/115298579764580635
- Recursive Self-Aggregation Unlocks Deep Thinking in Large Language Models
Siddarth Venkatraman, et al.
https://arxiv.org/abs/2509.26626 https://mastoxiv.page/@arXiv_csLG_bot/115298789487177431
- Cautious Weight Decay
Chen, Li, Liang, Su, Xie, Pierse, Liang, Lao, Liu
https://arxiv.org/abs/2510.12402 https://mastoxiv.page/@arXiv_csLG_bot/115377759317818093
- TeamFormer: Shallow Parallel Transformers with Progressive Approximation
Wei Wang, Xiao-Yong Wei, Qing Li
https://arxiv.org/abs/2510.15425 https://mastoxiv.page/@arXiv_csLG_bot/115405933861293858
- Latent-Augmented Discrete Diffusion Models
Dario Shariatian, Alain Durmus, Umut Simsekli, Stefano Peluchetti
https://arxiv.org/abs/2510.18114 https://mastoxiv.page/@arXiv_csLG_bot/115417332500265972
- Predicting Metabolic Dysfunction-Associated Steatotic Liver Disease using Machine Learning Method...
Mary E. An, Paul Griffin, Jonathan G. Stine, Ramakrishna Balakrishnan, Soundar Kumara
https://arxiv.org/abs/2510.22293 https://mastoxiv.page/@arXiv_csLG_bot/115451746201804373
toXiv_bot_toot

DHS staff to get back pay starting Friday
https://federalnewsnetwork.com/government-shutdown/2026/04/dhs-staff-to-get-back-pay-starting-friday/

DHS staff to get back pay starting Friday
DHS employees are set to receive back pay through April 4 thanks to re-directed funding, but future paychecks likely depend on Congress ending the shutdown.

Die Kämpfer für die Christenheit haben bei der Planung für ihre Kreuzzüge so viel zu tun, dass man auch gern den Inhalt der Bibel ignorieren kann.
https://flipboard.social/@newsguyusa/116415088384481830

I dag, på sidste dag af ferien sydpå, er solen endelig fremme. Vi stod på en rasteplads for lidt siden med en kop kaffe og missede med Ÿjnene mod solen.
Til gengæld kan vi se frem til et helt nedkŸlet hus når vi kommer hjem: Fyret gik i stå for et par dage siden (det gŸr det engang i mellem), og det er ikke noget man kan genstarte på afstand. Så nu er der ca. 13 grader i hele huset …

"Ihre Forschung bekommt eine Stimme": in der stabi berlin (@…) gibts jetzt ein podcast-studio!
https://blog.sbb.berlin/neues-podcasts…

Senator Chuck Schumer,
the New York Democrat and minority leader,
knew things were moving in his direction in the spending showdown on Wednesday afternoon when he got a surprise phone call in his Capitol office suite.
It was Donald Trump, not a frequent contact in these days of hyper-polarized politics.
“He says, ‘Chuck, I hate shutdowns. I don’t like shutdowns. We’ve got to stop them,’”
Mr. Schumer said in an interview as he recalled his conversation with Mr. T…

Facing Immigration Backlash, Trump Called Schumer to Cut a Deal
The president and the top Senate Democrat, who are often at each other’s throats, agreed to try to keep the government open and to start talks on new limits on federal immigration agents.