Tootfinder

@…
Exactly right about the idle server scenario! But here's the part I find most elegant about this approach:
The target server computes absolutely nothing.
With classic rsync --checksum, both source AND target need to calculate checksums for every file. That means:
- Double the CPU load (both machines working)
- Double the …

Well well well... 😉
#Amazon pauses AI-driven #coding chaos: after major outages, stricter code reviews are now mandatory.

From that observer who was taken yesterday, shared here with permission, because we could all use a good laugh. (Note: Whipple is the fed bldg that’s ICE’s MSP HQ)
❝So here’s my story about returning to the world…
When they let you out of Whipple, they give you back your personal effects (minus your phone). And just send you out the front door with whatever you were wearing when you came in.
So I’m walking out the front door of Whipple, probably looking like an ice agent coming off shift, and pulling all of my random shit out of my bag/dropping it in the snowbank, etc.… And I can hear the protesters at the gate, taunting me… “oh did you drop your phone, you piece of shit?” “You’re TERRIBLE!” “Fucking Nazi!” And I was just loving it, actually. But when I got closer and used my big voice “You assholes are barking up the wrong tree…. These MF’ers just released me!” The crowd went absolutely crazy.❞

@… This is, in principle, what an academic discipline is about: a shared understanding of what legit research in this field means, and what the criteria for judging the quality of research are.
The root many of the current issues in academia is that many, if not most, disciplines have outsourced this responsibility to Big Pub cartels.

@… This is, in principle, what an academic discipline is about: a shared understanding of what legit research in this field means, and what the criteria for judging the quality of research are.
The root many of the current issues in academia is that many, if not most, disciplines have outsourced this responsibility to Big Pub cartels.

Development and characterization of hybrid MCP-PMT with embedded Timepix4 ASIC used as pixelated anode
Riccardo Bolzonella, Jerome Alozy, Rafael Ballabriga, Nicol\`o Vladi Biesuz, Michael Campbell, Viola Cavallini, Angelo Cotta Ramusino, Massimiliano Fiorini, Edoardo Franzoso, Marco Guarise, Xavi Llopart Cudie, Gabriele Romolini, Alessandro Saputi
https://arxiv.org/abs/2602.01886 https://arxiv.org/pdf/2602.01886 https://arxiv.org/html/2602.01886
arXiv:2602.01886v1 Announce Type: new
Abstract: We present a novel single-photon detector based on a vacuum tube incorporating a photocathode, a microchannel plate (MCP), and a Timepix4 CMOS ASIC functioning as a pixelated anode. Designed to handle photon rates up to 1 billion per second across a 7 cm$^2$ active area, the detector achieves outstanding spatial and temporal resolutions of 5-10 $\mu$m and below 50 ps r.m.s., respectively.
The Timepix4 ASIC comprises approximately 230,000 pixels, each integrating analog and digital front-end electronics. This enables data-driven acquisition and supports data transmission rates up to 160 Gb/s. External FPGA-based electronics manage both configuration and readout.
In order to test the timing performance of the Timepix4 ASIC we performed preliminary characterization of an assembly bonded to a 100 $\mu$m thick n-on-p silicon sensor using a pulsed infrared laser, which demonstrated a per-pixel timing resolution of 110 ps, with cluster-based averaging methods improving to below 50 ps.
Six prototype detectors incorporating different MCP stack configurations and end-spoiling depths were produced by Hamamatsu Photonics. We report on their characterization, including dark count rates, gain, and spatial and timing resolutions, assessed both in laboratory conditions and during a test-beam campaign at CERN's SPS facility.
toXiv_bot_toot

Das mal in #Deutschland und hier ist Feierabend:
Eine extreme #Kältewelle mit Temperaturen bis zu minus 55 Grad hat weite Teile #Russlands lahmgelegt.
In Regionen wie

Russland droht Kälte-Kollaps: Wetter-Schock bei –55 Grad und Schnee bis zur 7. Etage
Eine massive Kältewelle mit Temperaturen bis zu minus 55 Grad hat weite Teile Russlands fest im Griff. In einigen Regionen türmt sich der Schnee bis zu einer Höhe von sieben Stockwerken.

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[4/6]:
- Neural Proposals, Symbolic Guarantees: Neuro-Symbolic Graph Generation with Hard Constraints
Chuqin Geng, Li Zhang, Mark Zhang, Haolin Ye, Ziyu Zhao, Xujie Si
https://arxiv.org/abs/2602.16954 https://mastoxiv.page/@arXiv_csLG_bot/116102434757760085
- Multi-Probe Zero Collision Hash (MPZCH): Mitigating Embedding Collisions and Enhancing Model Fres...
Ziliang Zhao, et al.
https://arxiv.org/abs/2602.17050 https://mastoxiv.page/@arXiv_csLG_bot/116102517335590034
- MASPO: Unifying Gradient Utilization, Probability Mass, and Signal Reliability for Robust and Sam...
Fu, Lin, Fang, Zheng, Hu, Shao, Qin, Pan, Zeng, Cai
https://arxiv.org/abs/2602.17550 https://mastoxiv.page/@arXiv_csLG_bot/116102581561441103
- A Theoretical Framework for Modular Learning of Robust Generative Models
Corinna Cortes, Mehryar Mohri, Yutao Zhong
https://arxiv.org/abs/2602.17554 https://mastoxiv.page/@arXiv_csLG_bot/116102582216715527
- Multi-Round Human-AI Collaboration with User-Specified Requirements
Sima Noorani, Shayan Kiyani, Hamed Hassani, George Pappas
https://arxiv.org/abs/2602.17646 https://mastoxiv.page/@arXiv_csLG_bot/116102592047544971
- NEXUS: A compact neural architecture for high-resolution spatiotemporal air quality forecasting i...
Rampunit Kumar, Aditya Maheshwari
https://arxiv.org/abs/2602.19654 https://mastoxiv.page/@arXiv_csLG_bot/116125610403473755
- Augmenting Lateral Thinking in Language Models with Humor and Riddle Data for the BRAINTEASER Task
Mina Ghashami, Soumya Smruti Mishra
https://arxiv.org/abs/2405.10385 https://mastoxiv.page/@arXiv_csCL_bot/112472190479013167
- Watermarking Language Models with Error Correcting Codes
Patrick Chao, Yan Sun, Edgar Dobriban, Hamed Hassani
https://arxiv.org/abs/2406.10281 https://mastoxiv.page/@arXiv_csCR_bot/112636307340218522
- Learning to Control Unknown Strongly Monotone Games
Siddharth Chandak, Ilai Bistritz, Nicholas Bambos
https://arxiv.org/abs/2407.00575 https://mastoxiv.page/@arXiv_csMA_bot/112715733875586837
- Classification and reconstruction for single-pixel imaging with classical and quantum neural netw...
Sofya Manko, Dmitry Frolovtsev
https://arxiv.org/abs/2407.12506 https://mastoxiv.page/@arXiv_quantph_bot/112806295477530195
- Statistical Inference for Temporal Difference Learning with Linear Function Approximation
Weichen Wu, Gen Li, Yuting Wei, Alessandro Rinaldo
https://arxiv.org/abs/2410.16106 https://mastoxiv.page/@arXiv_statML_bot/113350611306532443
- Big data approach to Kazhdan-Lusztig polynomials
Abel Lacabanne, Daniel Tubbenhauer, Pedro Vaz
https://arxiv.org/abs/2412.01283 https://mastoxiv.page/@arXiv_mathRT_bot/113587812663608119
- MoEMba: A Mamba-based Mixture of Experts for High-Density EMG-based Hand Gesture Recognition
Mehran Shabanpour, Kasra Rad, Sadaf Khademi, Arash Mohammadi
https://arxiv.org/abs/2502.17457 https://mastoxiv.page/@arXiv_eessSP_bot/114069047434302054
- Tightening Optimality gap with confidence through conformal prediction
Miao Li, Michael Klamkin, Russell Bent, Pascal Van Hentenryck
https://arxiv.org/abs/2503.04071 https://mastoxiv.page/@arXiv_statML_bot/114120074927291283
- SEED: Towards More Accurate Semantic Evaluation for Visual Brain Decoding
Juhyeon Park, Peter Yongho Kim, Jiook Cha, Shinjae Yoo, Taesup Moon
https://arxiv.org/abs/2503.06437 https://mastoxiv.page/@arXiv_csCV_bot/114142690988862508
- How much does context affect the accuracy of AI health advice?
Prashant Garg, Thiemo Fetzer
https://arxiv.org/abs/2504.18310 https://mastoxiv.page/@arXiv_econGN_bot/114414380916957986
- Reproducing and Improving CheXNet: Deep Learning for Chest X-ray Disease Classification
Daniel J. Strick, Carlos Garcia, Anthony Huang, Thomas Gardos
https://arxiv.org/abs/2505.06646 https://mastoxiv.page/@arXiv_eessIV_bot/114499319986528625
- Sharp Gaussian approximations for Decentralized Federated Learning
Soham Bonnerjee, Sayar Karmakar, Wei Biao Wu
https://arxiv.org/abs/2505.08125 https://mastoxiv.page/@arXiv_statML_bot/114505047719395949
- HoloLLM: Multisensory Foundation Model for Language-Grounded Human Sensing and Reasoning
Chuhao Zhou, Jianfei Yang
https://arxiv.org/abs/2505.17645 https://mastoxiv.page/@arXiv_csCV_bot/114572928659057348
- A Copula Based Supervised Filter for Feature Selection in Diabetes Risk Prediction Using Machine ...
Agnideep Aich, Md Monzur Murshed, Sameera Hewage, Amanda Mayeaux
https://arxiv.org/abs/2505.22554 https://mastoxiv.page/@arXiv_statML_bot/114589983451462525
- Synthesis of discrete-continuous quantum circuits with multimodal diffusion models
Florian F\"urrutter, Zohim Chandani, Ikko Hamamura, Hans J. Briegel, Gorka Mu\~noz-Gil
https://arxiv.org/abs/2506.01666 https://mastoxiv.page/@arXiv_quantph_bot/114618420761346125
toXiv_bot_toot

Good Morning #Canada
It's time for our first post in the #CanadaRivers series with #25 in our countdown. The Churchill River, in Atlantic Canada, flows for 856 km from Lake Melville into the Atlantic Ocean. It drains a watershed that covers 79,800 km/2 and has an average volume of 1,580 square metres per second.
The power development at Churchill Falls has backed up the river and created the enormous Smallwood Reservoir. Farther upstream, a hydroelectric plant at the outfall from Menihek Lakes provides power for the former iron-mining town of Schefferville, Québec. With a heavy flow and large drop from the Labrador Plateau, the river has probably the greatest hydroelectric potential of any in North America. The Churchill Falls Generating Station deserves it's own post as it is a massive 5,428 MW underground hydro power plant.
Don't get used to calling it the Churchill River as there are recent campaigns to return to its traditional native name.
#CanadaIsAwesome #Geography
https://www.cbc.ca/news/canada/newfoundland-labrador/churchill-river-innu-name-change-mishta-shipu-1.6444142

There are a lot of takeaways from this:
1. Organizing locally gives you a massive advantage because you will always know your local area better than ICE ever can.
2. Be agile. You can always change tactics faster than a centralized organization.
3. Organize now. The sooner you build your networks, the sooner you can learn.
4. Identify ICE facilities and organize monitoring them directly.
But I think the most interesting one that's not explicitly in there, one that's hinted at the last one, is to go on the offensive. ICE is already afraid. If we all take the anger we have at the murder of #ReneGood, find the local ICE facility that they'll stage from, and bring that anger to #OccupyICE we might be able to just shut the whole thing down preemptively. Completely stop all ICE operations across the US. If they want to fight, they can fight *with everyone, all at once.*
Shut down their ability to operate at all. They have a logistics pipeline. They need cars, they need oil in those cars, they need to be able to move those cars to target areas. They also need money to pay those agents. All of those can be disrupted.
The regime needs your money and labor to maintain the illusion of legitimacy. They chose a bad time because you can hit both of those at once *right now* with a combination of #GeneralStrike and #TaxStrike, and then #BoycottEverything.
The regime is weaker than it's ever been. It's flailing. Their own base is demanding the release of the #EpsteinFiles. Their last gasp attempt to prevent the radical change that's coming is just to ethnically cleanse the US back to the 50's (which is what they always meant by "Make America Great Again"). Trump will do anything to stay in power, even if it means killing everyone on Earth in the process. But Americans can end it now by going on the offensive.
Now is the time.
#USPol