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Largest dyadic dual VC-dimension of non-piercing families
Xinqi Huang, Yuzhen Qi, Mingyuan Rong, Zixiang Xu
https://arxiv.org/abs/2506.13606 https://

Largest dyadic dual VC-dimension of non-piercing families
The dyadic dual VC-dimension of a set system \( \mathcal{F} \) is the largest integer \( \ell \) such that there exist \( \ell \) sets \( F_1, F_{2}, \dots, F_\ell \in \mathcal{F} \), where every pair \( \{i, j\} \in \binom{[\ell]}{2} \) is witnessed by an element \( a_{i,j} \in F_i \cap F_j \) that does not belong to any other set \( F_k \) with \( k \in [\ell] \setminus \{i, j\} \). In this paper, we determine the largest dyadic dual VC-dimension of a non-piercing family is exactly $4$, provi…

Strijd om lijsttrekkerschap zorgt binnen NSC voor chaos en verdeeldheid - #nos
https://nos.nl/artikel/2571405-strijd-om-lijsttrekkerscha…

Trump Organization eyes a new Trump-branded wireless service, complete with gold phones (Steve Benen/MSNBC)
https://www.msnbc.com/rachel-maddow-show/maddowblog/trump-mobile-phone-service-t1-rcna213261
http://www.memeorandum.com/250616/p76#a250616p76

Maximally-Informative Retrieval for State Space Model Generation
Evan Becker, Benjamin Bowman, Matthew Trager, Tian Yu Liu, Luca Zancato, Wei Xia, Stefano Soatto
https://arxiv.org/abs/2506.12149

Maximally-Informative Retrieval for State Space Model Generation
Given a query and dataset, the optimal way of answering the query is to make use all the information available. Modern LLMs exhibit impressive ability to memorize training data, but data not deemed important during training is forgotten, and information outside that training set cannot be made use of. Processing an entire dataset at inference time is infeasible due to the bounded nature of model resources (e.g. context size in transformers or states in state space models), meaning we must resor…

Fünf weitere Jahre - 65 Mio. pro Jahr! Bayern vor Vertragsverlängerung #News #Nachrichten

Feeling Machines: Ethics, Culture, and the Rise of Emotional AI
Vivek Chavan, Arsen Cenaj, Shuyuan Shen, Ariane Bar, Srishti Binwani, Tommaso Del Becaro, Marius Funk, Lynn Greschner, Roberto Hung, Stina Klein, Romina Kleiner, Stefanie Krause, Sylwia Olbrych, Vishvapalsinhji Parmar, Jaleh Sarafraz, Daria Soroko, Daksitha Withanage Don, Chang Zhou, Hoang Thuy Duong Vu, Parastoo Semnani, Daniel Weinhardt, Elisabeth Andre, J\"org Kr\"uger, Xavier Fresquet

Feeling Machines: Ethics, Culture, and the Rise of Emotional AI
This paper explores the growing presence of emotionally responsive artificial intelligence through a critical and interdisciplinary lens. Bringing together the voices of early-career researchers from multiple fields, it explores how AI systems that simulate or interpret human emotions are reshaping our interactions in areas such as education, healthcare, mental health, caregiving, and digital life. The analysis is structured around four central themes: the ethical implications of emotional AI, …

Convergence Analysis of a Dual-Wind Discontinuous Galerkin Method for an Elliptic Optimal Control Problem with Control Constraints
Satyajith Bommana Boyana, Thomas Lewis, Sijing Liu, Yi Zhang
https://arxiv.org/abs/2506.12330

Convergence Analysis of a Dual-Wind Discontinuous Galerkin Method for an Elliptic Optimal Control Problem with Control Constraints
This paper investigates a symmetric dual-wind discontinuous Galerkin (DWDG) method for solving an elliptic optimal control problem with control constraints. The governing constraint is an elliptic partial differential equation (PDE), which is discretized using the symmetric DWDG approach. We derive error estimates in the energy norm for both the state and the adjoint state, as well as in the $L^2$ norm of the control variable. Numerical experiments are provided to demonstrate the robustness and…

This👇needs to be remembered. https://substack.com/@johncleese/note/c-125827219?r=e7vv

John Cleese on Substack
Steve Bannon illustrates the key point we made in ‘The Life of Brian’ - that people makes what they like of religious teaching Matthew 26,52 And then Jesus said unto him ‘Put your sword back into its place, for those who take the sword will perish by the sword” Steve Bannon has rewritten this as “Live by the sword, die by the sword” as though it was a command. I prefer Jesus’s warning of the consequences of violence Only a MAGA Christian could believe that Christ was inciti…

This👇needs to be remembered. https://substack.com/@johncleese/note/c-125827219?r=e7vv

John Cleese on Substack
Steve Bannon illustrates the key point we made in ‘The Life of Brian’ - that people makes what they like of religious teaching Matthew 26,52 And then Jesus said unto him ‘Put your sword back into its place, for those who take the sword will perish by the sword” Steve Bannon has rewritten this as “Live by the sword, die by the sword” as though it was a command. I prefer Jesus’s warning of the consequences of violence Only a MAGA Christian could believe that Christ was inciti…

Moment Restrictions for Nonlinear Panel Data Models with Feedback
St\'ephane Bonhomme, Kevin Dano, Bryan S. Graham
https://arxiv.org/abs/2506.12569 htt…

Moment Restrictions for Nonlinear Panel Data Models with Feedback
Many panel data methods, while allowing for general dependence between covariates and time-invariant agent-specific heterogeneity, place strong a priori restrictions on feedback: how past outcomes, covariates, and heterogeneity map into future covariate levels. Ruling out feedback entirely, as often occurs in practice, is unattractive in many dynamic economic settings. We provide a general characterization of all feedback and heterogeneity robust (FHR) moment conditions for nonlinear panel data…