Tootfinder

MacBook-Trackpad: Genau genug, um eine Waage zu sein
Apples Solid-State-Cursorfeld erfasst Druck sehr genau. Das reicht sogar aus, um Gramm-genau festzustellen, was man darauf legt.
https://www.

#TuneTuesday (Jun 24)
For my final pick for #PrideMonth 🏳️‍🌈, here’s #TroyeSivan’s “Strawberries & Cigarettes”. This song by Troye, who came out as gay in 2013, was one of the very first songs t…

🇺🇦 #NowPlaying on KEXP's #MorningShow
Tears for Fears:
🎵 Pale Shelter
#TearsforFears
https://dustinfunkman.bandcamp.com/track/tears-for-fears-pale-shelter-rmx
https://open.spotify.com/track/3bq6GVy7ol5FdMU0OtKVkz

DeCo-SGD: Joint Optimization of Delay Staleness and Gradient Compression Ratio for Distributed SGD
Rongwei Lu, Jingyan Jiang, Chunyang Li, Haotian Dong, Xingguang Wei, Delin Cai, Zhi Wang
https://arxiv.org/abs/2507.17346

DeCo-SGD: Joint Optimization of Delay Staleness and Gradient Compression Ratio for Distributed SGD
Distributed machine learning in high end-to-end latency and low, varying bandwidth network environments undergoes severe throughput degradation. Due to its low communication requirements, distributed SGD (D-SGD) remains the mainstream optimizer in such challenging networks, but it still suffers from significant throughput reduction. To mitigate these limitations, existing approaches typically employ gradient compression and delayed aggregation to alleviate low bandwidth and high latency, respec…

Machine learning-based multimodal prognostic models integrating pathology images and high-throughput omic data for overall survival prediction in cancer: a systematic review
Charlotte Jennings (National Pathology Imaging Cooperative, Leeds Teaching Hospitals NHS Trust, Leeds, UK), Andrew Broad (National Pathology Imaging Cooperative, Leeds Teaching Hospitals NHS Trust, Leeds, UK), Lucy Godson (National Pathology Imaging Cooperative, Leeds Teaching Hospitals NHS Trust, Leeds, UK), Emily…

Machine learning-based multimodal prognostic models integrating pathology images and high-throughput omic data for overall survival prediction in cancer: a systematic review
Multimodal machine learning integrating histopathology and molecular data shows promise for cancer prognostication. We systematically reviewed studies combining whole slide images (WSIs) and high-throughput omics to predict overall survival. Searches of EMBASE, PubMed, and Cochrane CENTRAL (12/08/2024), plus citation screening, identified eligible studies. Data extraction used CHARMS; bias was assessed with PROBAST+AI; synthesis followed SWiM and PRISMA 2020. Protocol: PROSPERO (CRD42024594745)…

dolphins: Dolphin social network (1994-2001)
An undirected social network of frequent associations observed among 62 dolphins (Tursiops) in a community living off Doubtful Sound, New Zealand, from 1994-2001.
This network has 62 nodes and 159 edges.
Tags: Social, Animal, Unweighted
https://networks.skewed.de/net/dolphins…

Neutrinos erstmals mit tragbarem Detektor in einem Atomkraftwerk gemessen
Physiker haben einen handlichen Detektor entwickelt, der Neutrinos aus Kernreaktoren nachweisen kann. Bisher waren dafür riesige Anlagen nötig.

2020 hamnade mitt betänkande SOU 2020:56 i ryska medier, återgivet av en nyhetsbyrå med kopplingar till underrättelsetjänsten. Ett märkligt kvitto på att analysen träffade en nerv. Det påminner mig om att ord kan få liv i sammanhang man inte själv råder över.
https://carlheath.se/ett-kvitto-fran-k

PathWeaver: A High-Throughput Multi-GPU System for Graph-Based Approximate Nearest Neighbor Search
Sukjin Kim, Seongyeon Park, Si Ung Noh, Junguk Hong, Taehee Kwon, Hunseong Lim, Jinho Lee
https://arxiv.org/abs/2507.17094

PathWeaver: A High-Throughput Multi-GPU System for Graph-Based Approximate Nearest Neighbor Search
Graph-based Approximate Nearest Neighbor Search (ANNS) is widely adopted in numerous applications, such as recommendation systems, natural language processing, and computer vision. While recent works on GPU-based acceleration have significantly advanced ANNS performance, the ever-growing scale of datasets now demands efficient multi-GPU solutions. However, the design of existing works overlooks multi-GPU scalability, resulting in naive approaches that treat additional GPUs as a means to extend …

FCPO: Federated Continual Policy Optimization for Real-Time High-Throughput Edge Video Analytics
Lucas Liebe, Thanh-Tung Nguyen, Dongman Lee
https://arxiv.org/abs/2507.18047 htt…

FCPO: Federated Continual Policy Optimization for Real-Time High-Throughput Edge Video Analytics
The growing complexity of Edge Video Analytics (EVA) facilitates new kind of intelligent applications, but creates challenges in real-time inference serving systems. State-of-the-art (SOTA) scheduling systems optimize global workload distributions for heterogeneous devices but often suffer from extended scheduling cycles, leading to sub-optimal processing in rapidly changing Edge environments. Local Reinforcement Learning (RL) enables quick adjustments between cycles but faces scalability, know…