Tootfinder

Now out in #TMLR:
🍇 GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks 🍇
There's lots of work on sampling subgraphs for GNNs, but relatively little on making this sampling process _adaptive_. That is, learning to select the data from the graph that is relevant for your task.
We introduce an RL-based and a GFLowNet-based sampler and show that the approach perf…

'Forever chemicals' detected in 65% of sampled private wells in Pennsylvania https://phys.org/news/2025-06-chemicals-sampled-private-wells-pennsylvania.html
PFAS Found in 65% of Private Wells Sampled in Pennsylvania

'Forever chemicals' detected in 65% of sampled private wells in Pennsylvania
In Pennsylvania, 3.5 million people are served by private well systems, according to Penn State Extension. To better understand potential contamination of the groundwater feeding these systems, a team of researchers from Penn State conducted a novel three-year citizen science study of per- and poly-fluoroalkyl substances (PFAS)—often referred to as forever chemicals—in 167 private wells across Pennsylvania.

🇺🇦 #NowPlaying on KEXP's #VarietyMix
Sampology:
🎵 Morning Sun
#Sampology
https://sampology.bandcamp.com/track/morning-sun
https://open.spotify.com/track/0ODz72aWsdWhKqgEmJYZ7Q

Enhancing Symbolic Machine Learning by Subsymbolic Representations
Stephen Roth, Lennart Baur, Derian Boer, Stefan Kramer
https://arxiv.org/abs/2506.14569 …

Enhancing Symbolic Machine Learning by Subsymbolic Representations
The goal of neuro-symbolic AI is to integrate symbolic and subsymbolic AI approaches, to overcome the limitations of either. Prominent systems include Logic Tensor Networks (LTN) or DeepProbLog, which offer neural predicates and end-to-end learning. The versatility of systems like LTNs and DeepProbLog, however, makes them less efficient in simpler settings, for instance, for discriminative machine learning, in particular in domains with many constants. Therefore, we follow a different approach:…

Umfragen zeigen: Kleine Symbole für Gen-Z besonders wichtig
Wer mit der Gen Z arbeitet, sollte allmählich die Sprache der Emojis erlernen. Das legen Umfrageergebnisse nahe.
https://www.

Adaptive Data Augmentation for Thompson Sampling
Wonyoung Kim
https://arxiv.org/abs/2506.14479 https://arxiv.org/pdf/2506.14479

Adaptive Data Augmentation for Thompson Sampling
In linear contextual bandits, the objective is to select actions that maximize cumulative rewards, modeled as a linear function with unknown parameters. Although Thompson Sampling performs well empirically, it does not achieve optimal regret bounds. This paper proposes a nearly minimax optimal Thompson Sampling for linear contextual bandits by developing a novel estimator with the adaptive augmentation and coupling of the hypothetical samples that are designed for efficient parameter learning. …

Recht simples, doch untrügerisches Basilikum-Vinaigrette-Rezept, mundet mit etwas weniger Olivenöl ebenfalls ausgezeichnet. #nommention
https://www.simplyrecipes.com/recipes/basil_vi…

An Exact and Efficient Sampler for Dynamic Discrete Distributions
Lilith Orion Hafner, Adriano Meligrana
https://arxiv.org/abs/2506.14062 https://

An Exact and Efficient Sampler for Dynamic Discrete Distributions
Sampling from a dynamic discrete distribution involves sampling from a dynamic set of weighted elements, where elements can be added or removed at any stage of the sampling process. Although efficient for static sets, the Alias method becomes impractical in dynamic settings due to the need to reconstruct the sampler after each update, which incurs a computational cost proportional to the size of the distribution, making it unsuitable for applications requiring frequent insertions, deletions, or…

The Sample Complexity of Distributed Simple Binary Hypothesis Testing under Information Constraints
Hadi Kazemi, Ankit Pensia, Varun Jog
https://arxiv.org/abs/2506.13686

The Sample Complexity of Distributed Simple Binary Hypothesis Testing under Information Constraints
This paper resolves two open problems from a recent paper, arXiv:2403.16981, concerning the sample complexity of distributed simple binary hypothesis testing under information constraints. The first open problem asks whether interaction reduces the sample complexity of distributed simple binary hypothesis testing. In this paper, we show that sequential interaction does not help. The second problem suggests tightening existing sample complexity bounds for communication-constrained simple binary …

Ungewöhnlich warme #Meeresströmungen vor Japans Küste können zu extremem #Schneefall führen.
Zu diesem Ergebnis kamen Wissenschaftler der Rissho-Universität und der Universität Hokkaido. Im Februar fielen auf

Steigende Meerestemperaturen erhöhen das Risiko für extremen Schneefall in Japan
Ein Forschungsteam aus Japan hat untersucht, warum es im Februar in der Stadt Obihiro auf Hokkaido zu einem außergewöhnlich starken Schneefall kam. Die