Elon Musk says X will "pause" new creator monetization rules that would base payouts on engagement from a user's local audience, after criticism from creators (Ivan Mehta/TechCrunch)
https://techcrunch.com/2026/03/25/elon
Elon Musk says X will "pause" new creator monetization rules that would base payouts on engagement from a user's local audiences, after criticism from creators (Ivan Mehta/TechCrunch)
https://techcrunch.com/2026/03/25/elon
I am working on my projects at my job and “suddenly”, I have just finished something different…
https://github.com/jaandrle/git-info
A Git status tool inspired by [GitButler](https:/…
How reality TV is running into the harsh realities of the fast-changing TV business; Luminate says US unscripted and reality premieres fell by ~33% since 2022 (John Koblin/New York Times)
https://www.nytimes.com/2026/03/24/business/media/reality-tv-era-ending.htm…
🇺🇦 #NowPlaying on #BBC6Music's #TheCraigCharlesFunkAndSoulShow
Harris & Orr:
🎵 Here I Go (Through These Changes Again)
#Harris #Orr
https://pvinerecords.bandcamp.com/track/here-i-go-through-these-changes-again
Bikelution: Federated Gradient-Boosting for Scalable Shared Micro-Mobility Demand Forecasting
Antonios Tziorvas, Andreas Tritsarolis, Yannis Theodoridis
https://arxiv.org/abs/2602.20671 https://arxiv.org/pdf/2602.20671 https://arxiv.org/html/2602.20671
arXiv:2602.20671v1 Announce Type: new
Abstract: The rapid growth of dockless bike-sharing systems has generated massive spatio-temporal datasets useful for fleet allocation, congestion reduction, and sustainable mobility. Bike demand, however, depends on several external factors, making traditional time-series models insufficient. Centralized Machine Learning (CML) yields high-accuracy forecasts but raises privacy and bandwidth issues when data are distributed across edge devices. To overcome these limitations, we propose Bikelution, an efficient Federated Learning (FL) solution based on gradient-boosted trees that preserves privacy while delivering accurate mid-term demand forecasts up to six hours ahead. Experiments on three real-world BSS datasets show that Bikelution is comparable to its CML-based variant and outperforms the current state-of-the-art. The results highlight the feasibility of privacy-aware demand forecasting and outline the trade-offs between FL and CML approaches.
toXiv_bot_toot
«Instagram is killing its end-to-end encrypted chats - here's what changes May 8:
Instagram will end support for end-to-end encrypted chats on May 8, 2026. What the feature does, how it works, and what users lose when it goes.»
Instagram has never been safe, because although it uses encryption, the clearly visible metadata says a lot about something.
💬
Replaced article(s) found for math.DG. https://arxiv.org/list/math.DG/new
[1/1]:
- Classification of generalized Yamabe solitons under vanishing conditions on the Weyl, Cotton, and...
Shun Maeta
https://arxiv.org/abs/2107.05487
- Non-collapsing volume estimate for local K\"ahler metrics in big cohomology classes
Thai Duong Do, Duc-Bao Nguyen, Duc-Viet Vu
https://arxiv.org/abs/2502.16136
- The rigidity statement in the Horowitz-Myers conjecture
S. Brendle, P. K. Hung
https://arxiv.org/abs/2504.16812 https://mastoxiv.page/@arXiv_mathDG_bot/114391742095134598
- The $k$th Order Preserving Sets and Isoperimetric Type Inequalities for Planar Ovals
Maksymilian Filip Safarewicz, Micha{\l} Zwierzy\'nski
https://arxiv.org/abs/2505.08017 https://mastoxiv.page/@arXiv_mathDG_bot/114504987361702955
- An improved upper bound for the second eigenvalue on tori
Fan Kang
https://arxiv.org/abs/2506.05846 https://mastoxiv.page/@arXiv_mathDG_bot/114652408234085783
- Pluriclosed metrics on compact semisimple Lie groups
Jorge Lauret, Facundo Montedoro
https://arxiv.org/abs/2506.21725 https://mastoxiv.page/@arXiv_mathDG_bot/114771230739330209
- Finite extinction time of a family of homogeneous Ricci flows
Roberto Araujo
https://arxiv.org/abs/2507.05097 https://mastoxiv.page/@arXiv_mathDG_bot/114817170850209379
- Concavity of spacetimes
Tobias Beran, Darius Er\"os, Shin-ichi Ohta, Felix Rott
https://arxiv.org/abs/2509.26196 https://mastoxiv.page/@arXiv_mathDG_bot/115298277656918174
- A Lower Bound for the First Non-zero Basic Eigenvalue on a Singular Riemannian Foliation
Bach Tran
https://arxiv.org/abs/2602.17501 https://mastoxiv.page/@arXiv_mathDG_bot/116102222415286571
- The Cauchy problem of the Lorentzian Dirac operator with APS boundary conditions
Nicol\`o Drago, Nadine Gro{\ss}e, Simone Murro
https://arxiv.org/abs/2104.00585
- The Eigenvalue Problem for the complex Monge-Amp\`ere operator
Papa Badiane, Ahmed Zeriahi
https://arxiv.org/abs/2306.03285 https://mastoxiv.page/@arXiv_mathCV_bot/110501544679577441
- Geodesic X-ray transform and streaking artifacts on simple surfaces or on spaces of constant curv...
Hiroyuki Chihara
https://arxiv.org/abs/2402.06899 https://mastoxiv.page/@arXiv_mathAP_bot/111924395641033643
- Koopman Regularization
Ido Cohen
https://arxiv.org/abs/2403.11302 https://mastoxiv.page/@arXiv_mathDS_bot/112121157959044047
- Parabolic noncommutative geometry
Magnus Fries, Magnus Goffeng, Ada Masters
https://arxiv.org/abs/2503.12938 https://mastoxiv.page/@arXiv_mathOA_bot/114182247165636785
- A Riemannian approach for PDE-constrained shape optimization over the diffeomorphism group using ...
Estefania Loayza-Romero, Lidiya Pryymak, Kathrin Welker
https://arxiv.org/abs/2503.22872 https://mastoxiv.page/@arXiv_mathOC_bot/114262964177766537
- Varifold solutions to Volume-Preserving Mean Curvature Flow: existence and weak-strong uniqueness
Andrea Poiatti
https://arxiv.org/abs/2507.08783 https://mastoxiv.page/@arXiv_mathAP_bot/114850896417417882
- Rigidity of Spectral Encodings under Weyl Growth Conditions
Anton Alexa
https://arxiv.org/abs/2510.03238 https://mastoxiv.page/@arXiv_mathSP_bot/115331835395254198
- The Regularity of Critical Points to Scale-Invariant Curvature Energies in Dimension 4
Yann Bernard, Tian Lan, Dorian Martino, Tristan Rivi\`ere
https://arxiv.org/abs/2511.01765 https://mastoxiv.page/@arXiv_mathAP_bot/115491294260333438
toXiv_bot_toot
Heroku says it is transitioning to a "sustaining engineering model", as it focuses on "helping organizations build and deploy enterprise-grade AI" (Nitin T Bhat/Heroku)
https://www.heroku.com/blog/an-update-on-heroku/