Tootfinder

Replaced article(s) found for stat.ML. https://arxiv.org/list/stat.ML/new
[1/1]:
- Learning to sample fibers for goodness-of-fit testing
Ivan Gvozdanovi\'c, Sonja Petrovi\'c

Use multi level models with {parsnip}: http://multilevelmod.tidymodels.org/ #rstats #ML

Crosslisted article(s) found for stat.ML. https://arxiv.org/list/stat.ML/new
[1/1]:
- Replicable Clustering
Hossein Esfandiari, Amin Karbasi, Vahab Mirrokni, Grigoris Velegkas, Felix Zhou

Robust ML-based Detection of Conventional, LLM-Generated, and Adversarial Phishing Emails Using Advanced Text Preprocessing
Deeksha Hareesha Kulal, Chidozie Princewill Arannonu, Afsah Anwar, Nidhi Rastogi, Quamar Niyaz
https://arxiv.org/abs/2510.11915

Robust ML-based Detection of Conventional, LLM-Generated, and Adversarial Phishing Emails Using Advanced Text Preprocessing
Phishing remains a critical cybersecurity threat, especially with the advent of large language models (LLMs) capable of generating highly convincing malicious content. Unlike earlier phishing attempts which are identifiable by grammatical errors, misspellings, incorrect phrasing, and inconsistent formatting, LLM generated emails are grammatically sound, contextually relevant, and linguistically natural. These advancements make phishing emails increasingly difficult to distinguish from legitimat…

Wireless Channel Modeling for Machine Learning -- A Critical View on Standardized Channel Models
Benedikt B\"ock, Amar Kasibovic, Wolfgang Utschick
https://arxiv.org/abs/2510.12279

Wireless Channel Modeling for Machine Learning -- A Critical View on Standardized Channel Models
Standardized (link-level) channel models such as the 3GPP TDL and CDL models are frequently used to evaluate machine learning (ML)-based physical-layer methods. However, in this work, we argue that a link-level perspective incorporates limiting assumptions, causing unwanted distributional shifts or necessitating impractical online training. An additional drawback is that this perspective leads to (near-)Gaussian channel characteristics. Thus, ML-based models, trained on link-level channel data,…

Cross-correlation of Luminous Red Galaxies with ML-selected AGN in HSC-SSP III: HOD Parameters for Type I and Type II Quasars
Rodrigo C\'ordova Rosado, Andy D. Goulding, Jenny E. Greene, Nickolas Kokron, Andrina Nicola, Michael A. Strauss, Ryan C. Hickox
https://arxiv.org/abs/2510.11780

Cross-correlation of Luminous Red Galaxies with ML-selected AGN in HSC-SSP III: HOD Parameters for Type I and Type II Quasars
Understanding the dark matter (DM) halo environment in which galaxies that host active galactic nuclei (AGN) reside is a window into the nature of supermassive black hole (SMBH) accretion. We apply halo occupation distribution (HOD) modeling tools to interpret the angular cross-correlation functions between $1.5\times10^6$ luminous red galaxies (LRGs) and our $\sim28,500$ Hyper Suprime-Cam + Wide-field Infrared Survey Explorer-selected (and $L_{6 μm}$-limited) AGN to infer the halo properties …

LED Lighting: Mini Reviews - Real-world testing! - https://m.earth.org.uk/LED-lighting.html

LED Lighting: Mini Reviews
Real-world testing!

Tracing Multilingual Knowledge Acquisition Dynamics in Domain Adaptation: A Case Study of English-Japanese Biomedical Adaptation
Xin Zhao, Naoki Yoshinaga, Yuma Tsuta, Akiko Aizawa
https://arxiv.org/abs/2510.12115

Tracing Multilingual Knowledge Acquisition Dynamics in Domain Adaptation: A Case Study of English-Japanese Biomedical Adaptation
Multilingual domain adaptation (ML-DA) is widely used to learn new domain knowledge across languages into large language models (LLMs). Although many methods have been proposed to improve domain adaptation, the mechanisms of multilingual knowledge acquisition, how domain knowledge is learned within a language and transferred across languages, remain underexplored. This gap leads to suboptimal performance, particularly in low-resource settings. This work examines the learning dynamics of LLMs du…

Warum meine Großmutter zurück in die Stadt zog und ich mein Nest nicht auf dem Land bauen will: kurze Wege und mehr Menschen heißt auch leichter sozialer Kontakt.
https://loma.ml/display/373ebf56-c2de9553-e191b82d366f91de
Ich finde die Initiative vom Land SH dennoc…

Там вышла 4я часть иски по финалке
Сначала думал, что опять Ютуб древние архивы поднял, а потом увидел время публикации... Я поражен до глубины души
https://youtu.be/X2SDwyldfzU

ML-KEM Mythbusting
"There have been some recent concerns about ML-KEM, NIST’s standard for encryption with Post-Quantum Cryptography, related standards of the IETF, and lots of conspiracy theories about malicious actors subverting the standardization process. "
#pqc #pqcrypto

Formal Models and Convergence Analysis for Context-Aware Security Verification
Ayush Chaudhary
https://arxiv.org/abs/2510.12440 https://arxiv.org/pdf/2510.…

Formal Models and Convergence Analysis for Context-Aware Security Verification
We present a formal framework for context-aware security verification that establishes provable guarantees for ML-enhanced adaptive systems. We introduce context-completeness - a new security property - and prove: (1) sample complexity bounds showing when adaptive verification succeeds, (2) information-theoretic limits relating context richness to detection capability, (3) convergence guarantees for ML-based payload generators, and (4) compositional soundness bounds. We further provide a formal…

First the nucleus of #comet SWAN split - https://skyweek.wordpress.com/2025/11/02/allgemeines-live-blog-ab-dem-2-november-2025/#Nov06 ("Der Kern des Kometen C/2025 R2 (SWAN) ist zerbrochen ...") - and now C/2025 K1 (ATLAS) has suffered the same fate: a 2-meter-telescope image from https://www.astronomerstelegram.org/?read=17487 ("Multiple Fragmentation Observed"), also https://groups.io/g/comets-ml/topic/116216567 (several amateur observations) and https://www.astronomerstelegram.org/?read=17488 (Hubble detections of more fragments, sadly no pictures included).

Replaced article(s) found for stat.ML. https://arxiv.org/list/stat.ML/new
[1/1]:
- Provably Scalable Black-Box Variational Inference with Structured Variational Families
Joohwan Ko, Kyurae Kim, Woo Chang Kim, Jacob R. Gardner

An online service I’m subscribed to emailed me to say that I would be placed on the “Pro Legacy” plan at the same price of $29 annually in December.
But if upgrade to their $60/year Pro plan, I get access to AI/ML “innovations”. Uh, no, thank you!
#AI #ML

Crosslisted article(s) found for stat.ML. https://arxiv.org/list/stat.ML/new
[1/1]:
- Group Averaging for Physics Applications: Accuracy Improvements at Zero Training Cost
Valentino F. Foit, David W. Hogg, Soledad Villar

Ethical Considerations Around Machine Learning-Engaged Online Participatory Research - poster from Zooniverse community at #FF2025 https://zenodo.org/records/17779992

AWS implemented a 15% price hike for EC2 Capacity Blocks for ML on January 3; Amazon says it "reflects the supply/demand patterns we expect this quarter" (Corey Quinn/The Register)
https://www.theregister.com/2026/01/05/aws_price_increase/

AWS raises GPU prices 15% on a Saturday, hopes you weren't paying attention
: An anomaly or the beginning of a new trend? My bet's on the latter

RE: https://mastodon.social/@firefoxwebdevs/115849251057488746
A Killswitch should of course kill all ML/AI functionality and people could then reactivate certain specific features of they want to, it's really not that hard. Just cause you consi…

Мне очень жаль терять мой стрик в Duolingo... Но введение энергии, которая тратится на каждое выполненное задание в уроке, вместо сердец, которые тратятся только когда ты ошибся — это прямо красная линия для меня. За безошибочный урок я получил -5 энергии.
Пришёл момент когда надо закончить эти абьюзивные отношения с зелёной птицей
#duolingo

LED Lighting: Mini Reviews - Real-world testing! - https://m.earth.org.uk/LED-lighting.html

LED Lighting: Mini Reviews
Real-world testing!

[2025-10-15 Wed (UTC), 15 new articles found for stat.ML Machine Learning]
toXiv_bot_toot

About how AI tools can be useful.
#ai #coding

Claude Code Can Debug Low-level Cryptography
Surprisingly (to me) Claude Code debugged my new ML-DSA implementation faster than I would have, finding the non-obvious low-level issue that was making Verify fail.

Replaced article(s) found for stat.ML. https://arxiv.org/list/stat.ML/new
[2/2]:
- Differentiable, Bit-shifting, and Scalable Quantization without training neural network from scratch
Zia Badar

RE: #Merz during visit in

#Kubernetes 1.35 Released with In-Place Pod Resize and AI-Optimized Scheduling
https://www.infoq.com/news/2025/12/kubernetes-1-35/

What’s disgusting is speaking to a Palestinian person in Gaza this way.
Maybe Mastodon server admins should check for basic humanity before allowing people on. Unless that’s not a necessary prerequisite for membership in your community, of course. https://lemmy.ca/comment/20336687

🇺🇦 #NowPlaying on KEXP's #90TEEN
Molina:
🎵 Organs
#Molina
https://corpusmolina.bandcamp.com/track/organs-feat-ml-buch
https://open.spotify.com/track/3XrEOFbHz26fgR8UTmPxmP

Replaced article(s) found for stat.ML. https://arxiv.org/list/stat.ML/new
[1/2]:
- Dataset-Free Weight-Initialization on Restricted Boltzmann Machine
Muneki Yasuda, Ryosuke Maeno, Chako Takahashi

from my link log —
The HP-35.
http://codex99.com/design/the-hp35.html
saved 2020-12-13 https://dotat.at/:/F9KEM.html

Crosslisted article(s) found for stat.ML. https://arxiv.org/list/stat.ML/new
[1/1]:
- A metrological framework for uncertainty evaluation in machine learning classification models
Samuel Bilson, Maurice Cox, Anna Pustogvar, Andrew Thompson

🚴 Benchmarking On-Device Machine Learning on Apple Silicon with MLX
#apple #hardware

Benchmarking On-Device Machine Learning on Apple Silicon with MLX
The recent widespread adoption of Large Language Models (LLMs) and machine learning in general has sparked research interest in exploring the possibilities of deploying these models on smaller devices such as laptops and mobile phones. This creates a need for frameworks and approaches that are capable of taking advantage of on-device hardware. The MLX framework was created to address this need. It is a framework optimized for machine learning (ML) computations on Apple silicon devices, facilita…

LED Lighting: Mini Reviews - Real-world testing! - https://m.earth.org.uk/LED-lighting.html

LED Lighting: Mini Reviews
Real-world testing!

Lightning talks include IIIF's AI/ML working group presented by the excellent Martin Kalfatovic https://www.conftool.org/fantastic-futures-2025/index.php?page=browseSessions&ismobile=true&form_session=26

I finally got Link Previews in Firefox today. I disabled the ‘AI’ feature and then disabled link previews altogether as I played with it.
But the setting disappeared completely, so I couldn’t turn it on again.
If this happens to you:
about:config − set browser.ml.linkPreview.enabled to true

I'm installing and tweaking #Immich, a really neat "Google Photos" like app that runs locally. It uses ML to do face detection and other neat features. I've been tuning my server and needed a better way to measure performance, so I vibe wrote a helper script. If you run Immich, this might be useful to you:

GitHub - rubix1138/immich_eta: Script that queries the Immich API and calculates and ETA
Script that queries the Immich API and calculates and ETA - rubix1138/immich_eta

[2025-11-14 Fri (UTC), 6 new articles found for stat.ML Machine Learning]
toXiv_bot_toot

I so hope this blows up in his face spectacularly.
Note that I do not believe that any LLM can become as skilled as the least skilled #InfoSec professional using conventional tools, so I’m quite confident this will not reach any useful goal.
I’m saying he needs to learn a lesson, and it would be great if it were useful for others as well. @…

Pangram Labs: ~21% of the 75,800 peer reviews submitted for ICLR 2026, a major ML conference, were fully AI-generated, and 50% contained signs of AI use (Miryam Naddaf/Nature)
https://www.nature.com/articles/d41586-025-03506-6

Major AI conference flooded with peer reviews written fully by AI
Controversy has erupted after 21% of manuscript reviews for an international AI conference were found to be generated by artificial intelligence.

Dear Reader,

Today I'm delighted to announce a Take Control book about a fantastic new Mac email app called #MailMaven. Developed by our friends at SmallCubed (best known for their popular MailSuite plugin for Apple Mail), MailMaven is a powerful and flexible alternative to apps like Apple Mail, Outlook, and Thunderbird.
The Manual is free from :

Übermorgen bei unseren Nachbarn:
#UniGöttingen

Another ML(#MarxismLeninism) blocked me when I posted this: https://social.linux.pizza/@midtsveen/115581081054226799
Love it or hate it, we can disagree on topics …

Marked safe from AI in Firefox 144 on Linux!
(about:config is your friend: search for ".ml.")
https://www.mozilla.org/en-US/firefox/144.0/whatsnew/?oldversion=143.0.4

Believe it or not, I've never actually submitted an academic paper for peer-reviewed publication before, and I'm a lil nail-bitey.
Is there anyone here who's active in ACL (the Association for Computational Linguistics) who wants to swap papers with me for a deep critique of methods/code/conclusions? I have a fun classic ML model that will entertain you, I swear.

60 years ago #OTD #comet #IkeyaSeki reached perihelion, -10 mag., was visible in daylight and showed a spectacular tail in the following weeks: https://groups.io/g/comets-ml/message/32770 and https://www.astronomy.com/today-in-the-history-of-astronomy/sept-18-1965-discovery-of-comet-ikeya-seki/ and https://noirlab.edu/public/images/noao-01854/

The totality of the evidence supports the thesis that displacement of long-established dietary patterns by ultra-processed foods is a key driver of the escalating global burden of multiple diet-related chronic diseases.
Monteiro CA, Louzada ML, Steele-Martinez E, Cannon G, Andrade GC, Baker P, et al. (2025): Ultra-processed foods and human health: the main thesis and the evidence. The Lancet 0. DOI: 10.1016/S0140-6736(25)01565-X

I can't hide that AMD cosplaying as Nvidia was a nasty surprise to me. But I am just a lowly gamer. Mad respect to the Linux hackers for knowing that corporations are not their friends, and - respectfully to AMD - bringing the goods only to Linux 🙂 ->
Modder gets FSR Redstone ML-powered Frame Generation running on RDNA 3 GPUs - VideoCardz.com

@… , we hadden het laatst over kaasfondue van schaap, hier heeft mijn websuper ineens Kaasfondue van geitenkaas - Kant en Klaar - Hofweb - de boerderij ken ik, die is, ondanks de suffe naam, goed. Ze doen er wel te weinig wijn in.

from my link log —
A brief history of NSA backdoors. (2013)
https://www.ethanheilman.com/x/12/index.html
saved 2025-11-29 https://d…

Model ML, which aims to use AI agents to automate grunt work done by investment bankers like making pitch decks, raised $75M, after raising $12M earlier in 2025 (Aisha S Gani/Bloomberg)
https://www.bloomberg.com/news/articles/20

das #nvidia

from my link log —
psychec: ML-style type inference for C.
https://github.com/ltcmelo/psychec
saved 2019-09-09 https://dotat.at/:/GN6G4.html

GitHub - ltcmelo/psychec: A compiler frontend for the C programming language
A compiler frontend for the C programming language - ltcmelo/psychec

The {purrr} package is a powerfull way to replace loops. The {furrr} package takes this approach one step further by parallel execution: #rstats

Apply Mapping Functions in Parallel using Futures
Implementations of the family of map() functions from purrr that can be resolved using any future-supported backend, e.g. parallel on the local machine or distributed on a compute cluster.

Crosslisted article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[2/3]:
- Sharp Structure-Agnostic Lower Bounds for General Functional Estimation
Jikai Jin, Vasilis Syrgkanis
https://arxiv.org/abs/2512.17341 https://mastoxiv.page/@arXiv_statML_bot/115762312049963700
- Timely Information Updating for Mobile Devices Without and With ML Advice
Yu-Pin Hsu, Yi-Hsuan Tseng
https://arxiv.org/abs/2512.17381 https://mastoxiv.page/@arXiv_csNI_bot/115762180316858485
- SWE-Bench : A Framework for the Scalable Generation of Software Engineering Benchmarks from Open...
Wang, Ramalho, Celestino, Pham, Liu, Sinha, Portillo, Osunwa, Maduekwe
https://arxiv.org/abs/2512.17419 https://mastoxiv.page/@arXiv_csSE_bot/115762487015279852
- Perfect reconstruction of sparse signals using nonconvexity control and one-step RSB message passing
Xiaosi Gu, Ayaka Sakata, Tomoyuki Obuchi
https://arxiv.org/abs/2512.17426 https://mastoxiv.page/@arXiv_statML_bot/115762346108219997
- MULTIAQUA: A multimodal maritime dataset and robust training strategies for multimodal semantic s...
Jon Muhovi\v{c}, Janez Per\v{s}
https://arxiv.org/abs/2512.17450 https://mastoxiv.page/@arXiv_csCV_bot/115762717053353674
- When Data Quality Issues Collide: A Large-Scale Empirical Study of Co-Occurring Data Quality Issu...
Emmanuel Charleson Dapaah, Jens Grabowski
https://arxiv.org/abs/2512.17460 https://mastoxiv.page/@arXiv_csSE_bot/115762500123147574
- Behavioural Effects of Agentic Messaging: A Case Study on a Financial Service Application
Olivier Jeunen, Schaun Wheeler
https://arxiv.org/abs/2512.17462 https://mastoxiv.page/@arXiv_csIR_bot/115762430673347625
- Linear Attention for Joint Power Optimization and User-Centric Clustering in Cell-Free Networks
Irched Chafaa, Giacomo Bacci, Luca Sanguinetti
https://arxiv.org/abs/2512.17466 https://mastoxiv.page/@arXiv_eessSY_bot/115762336277179643
- Translating the Rashomon Effect to Sequential Decision-Making Tasks
Dennis Gross, J{\o}rn Eirik Betten, Helge Spieker
https://arxiv.org/abs/2512.17470 https://mastoxiv.page/@arXiv_csAI_bot/115762556506696539
- Alternating Direction Method of Multipliers for Nonlinear Matrix Decompositions
Atharva Awari, Nicolas Gillis, Arnaud Vandaele
https://arxiv.org/abs/2512.17473 https://mastoxiv.page/@arXiv_eessSP_bot/115762580078964235
- TwinSegNet: A Digital Twin-Enabled Federated Learning Framework for Brain Tumor Analysis
Almustapha A. Wakili, Adamu Hussaini, Abubakar A. Musa, Woosub Jung, Wei Yu
https://arxiv.org/abs/2512.17488 https://mastoxiv.page/@arXiv_csCV_bot/115762726884307901
- Resource-efficient medical image classification for edge devices
Mahsa Lavaei, Zahra Abadi, Salar Beigzad, Alireza Maleki
https://arxiv.org/abs/2512.17515 https://mastoxiv.page/@arXiv_eessIV_bot/115762459510336799
- PathBench-MIL: A Comprehensive AutoML and Benchmarking Framework for Multiple Instance Learning i...
Brussee, Valkema, Weijer, Doeleman, Schrader, Kers
https://arxiv.org/abs/2512.17517 https://mastoxiv.page/@arXiv_csCV_bot/115762741957639051
- HydroGym: A Reinforcement Learning Platform for Fluid Dynamics
Christian Lagemann, et al.
https://arxiv.org/abs/2512.17534 https://mastoxiv.page/@arXiv_physicsfludyn_bot/115762391350754768
- When De-noising Hurts: A Systematic Study of Speech Enhancement Effects on Modern Medical ASR Sys...
Chondhekar, Murukuri, Vasani, Goyal, Badami, Rana, SN, Pandia, Katiyar, Jagadeesh, Gulati
https://arxiv.org/abs/2512.17562 https://mastoxiv.page/@arXiv_csSD_bot/115762423443170715
- Enabling Disaggregated Multi-Stage MLLM Inference via GPU-Internal Scheduling and Resource Sharing
Lingxiao Zhao, Haoran Zhou, Yuezhi Che, Dazhao Cheng
https://arxiv.org/abs/2512.17574 https://mastoxiv.page/@arXiv_csDC_bot/115762425409322293
- SkinGenBench: Generative Model and Preprocessing Effects for Synthetic Dermoscopic Augmentation i...
N. A. Adarsh Pritam, Jeba Shiney O, Sanyam Jain
https://arxiv.org/abs/2512.17585 https://mastoxiv.page/@arXiv_eessIV_bot/115762479150695610
- MAD-OOD: A Deep Learning Cluster-Driven Framework for an Out-of-Distribution Malware Detection an...
Tosin Ige, Christopher Kiekintveld, Aritran Piplai, Asif Rahman, Olukunle Kolade, Sasidhar Kunapuli
https://arxiv.org/abs/2512.17594 https://mastoxiv.page/@arXiv_csCR_bot/115762509298207765
- Confidence-Credibility Aware Weighted Ensembles of Small LLMs Outperform Large LLMs in Emotion De...
Menna Elgabry, Ali Hamdi
https://arxiv.org/abs/2512.17630 https://mastoxiv.page/@arXiv_csCL_bot/115762575512981257
- Generative Multi-Objective Bayesian Optimization with Scalable Batch Evaluations for Sample-Effic...
Madhav R. Muthyala, Farshud Sorourifar, Tianhong Tan, You Peng, Joel A. Paulson
https://arxiv.org/abs/2512.17659 https://mastoxiv.page/@arXiv_statML_bot/115762554519447500
toXiv_bot_toot

Soumith Chintala, who co-created the PyTorch ML framework at Meta and left the company this month, has joined Mira Murati's Thinking Machines Lab (Pranav Dixit/Business Insider)
https://www.businessinsider.com/meta-soumith-chinta…

A top Meta AI researcher has joined Mira Murati's hot new startup, Thinking Machines Lab
Thinking Machines Lab, led by Mira Murati, hires Meta AI veteran Soumith Chintala as it rapidly expands its team and prepares for major funding.

SPAM's Carbon Footprint @Home (2017) - The carbon cost of fending off SPAM (and other networked malice) at home... - https://m.earth.org.uk/SPAM-and-CO2.html

SPAMs Carbon Footprint @Home (2017)
The carbon cost of fending off SPAM (and other networked malice) at home...

LED Lighting: Mini Reviews - Real-world testing! - https://m.earth.org.uk/LED-lighting.html

LED Lighting: Mini Reviews
Real-world testing!

On 16WW Data Collections and Graphs - Open for research #dataset - https://m.earth.org.uk/note-on-data.html

On 16WW Data Collections and Graphs
Open for research #dataset

LED Lighting: Mini Reviews - Real-world testing! - https://m.earth.org.uk/LED-lighting.html

LED Lighting: Mini Reviews
Real-world testing!