@arXiv_csLG_bot@mastoxiv.page2025-12-22 13:54:24
Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[1/5]:
- Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization a...
Haoyue Bai, Gregory Canal, Xuefeng Du, Jeongyeol Kwon, Robert Nowak, Yixuan Li
https://arxiv.org/abs/2306.09158
- Sparse, Efficient and Explainable Data Attribution with DualXDA
Galip \"Umit Yolcu, Moritz Weckbecker, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin
https://arxiv.org/abs/2402.12118 https://mastoxiv.page/@arXiv_csLG_bot/111962593972369958
- HGQ: High Granularity Quantization for Real-time Neural Networks on FPGAs
Sun, Que, {\AA}rrestad, Loncar, Ngadiuba, Luk, Spiropulu
https://arxiv.org/abs/2405.00645 https://mastoxiv.page/@arXiv_csLG_bot/112370274737558603
- On the Identification of Temporally Causal Representation with Instantaneous Dependence
Li, Shen, Zheng, Cai, Song, Gong, Chen, Zhang
https://arxiv.org/abs/2405.15325 https://mastoxiv.page/@arXiv_csLG_bot/112511890051553111
- Basis Selection: Low-Rank Decomposition of Pretrained Large Language Models for Target Applications
Yang Li, Daniel Agyei Asante, Changsheng Zhao, Ernie Chang, Yangyang Shi, Vikas Chandra
https://arxiv.org/abs/2405.15877 https://mastoxiv.page/@arXiv_csLG_bot/112517547424098076
- Privacy Bias in Language Models: A Contextual Integrity-based Auditing Metric
Yan Shvartzshnaider, Vasisht Duddu
https://arxiv.org/abs/2409.03735 https://mastoxiv.page/@arXiv_csLG_bot/113089789682783135
- Low-Rank Filtering and Smoothing for Sequential Deep Learning
Joanna Sliwa, Frank Schneider, Nathanael Bosch, Agustinus Kristiadi, Philipp Hennig
https://arxiv.org/abs/2410.06800 https://mastoxiv.page/@arXiv_csLG_bot/113283021321510736
- Hierarchical Multimodal LLMs with Semantic Space Alignment for Enhanced Time Series Classification
Xiaoyu Tao, Tingyue Pan, Mingyue Cheng, Yucong Luo, Qi Liu, Enhong Chen
https://arxiv.org/abs/2410.18686 https://mastoxiv.page/@arXiv_csLG_bot/113367101100828901
- Fairness via Independence: A (Conditional) Distance Covariance Framework
Ruifan Huang, Haixia Liu
https://arxiv.org/abs/2412.00720 https://mastoxiv.page/@arXiv_csLG_bot/113587817648503815
- Data for Mathematical Copilots: Better Ways of Presenting Proofs for Machine Learning
Simon Frieder, et al.
https://arxiv.org/abs/2412.15184 https://mastoxiv.page/@arXiv_csLG_bot/113683924322164777
- Pairwise Elimination with Instance-Dependent Guarantees for Bandits with Cost Subsidy
Ishank Juneja, Carlee Joe-Wong, Osman Ya\u{g}an
https://arxiv.org/abs/2501.10290 https://mastoxiv.page/@arXiv_csLG_bot/113859392622871057
- Towards Human-Guided, Data-Centric LLM Co-Pilots
Evgeny Saveliev, Jiashuo Liu, Nabeel Seedat, Anders Boyd, Mihaela van der Schaar
https://arxiv.org/abs/2501.10321 https://mastoxiv.page/@arXiv_csLG_bot/113859392688054204
- Regularized Langevin Dynamics for Combinatorial Optimization
Shengyu Feng, Yiming Yang
https://arxiv.org/abs/2502.00277
- Generating Samples to Probe Trained Models
Eren Mehmet K{\i}ral, Nur\c{s}en Ayd{\i}n, \c{S}. \.Ilker Birbil
https://arxiv.org/abs/2502.06658 https://mastoxiv.page/@arXiv_csLG_bot/113984059089245671
- On Agnostic PAC Learning in the Small Error Regime
Julian Asilis, Mikael M{\o}ller H{\o}gsgaard, Grigoris Velegkas
https://arxiv.org/abs/2502.09496 https://mastoxiv.page/@arXiv_csLG_bot/114000974082372598
- Preconditioned Inexact Stochastic ADMM for Deep Model
Shenglong Zhou, Ouya Wang, Ziyan Luo, Yongxu Zhu, Geoffrey Ye Li
https://arxiv.org/abs/2502.10784 https://mastoxiv.page/@arXiv_csLG_bot/114023667639951005
- On the Effect of Sampling Diversity in Scaling LLM Inference
Wang, Liu, Chen, Light, Liu, Chen, Zhang, Cheng
https://arxiv.org/abs/2502.11027 https://mastoxiv.page/@arXiv_csLG_bot/114023688225233656
- How to use score-based diffusion in earth system science: A satellite nowcasting example
Randy J. Chase, Katherine Haynes, Lander Ver Hoef, Imme Ebert-Uphoff
https://arxiv.org/abs/2505.10432 https://mastoxiv.page/@arXiv_csLG_bot/114516300594057680
- PEAR: Equal Area Weather Forecasting on the Sphere
Hampus Linander, Christoffer Petersson, Daniel Persson, Jan E. Gerken
https://arxiv.org/abs/2505.17720 https://mastoxiv.page/@arXiv_csLG_bot/114572963019603744
- Train Sparse Autoencoders Efficiently by Utilizing Features Correlation
Vadim Kurochkin, Yaroslav Aksenov, Daniil Laptev, Daniil Gavrilov, Nikita Balagansky
https://arxiv.org/abs/2505.22255 https://mastoxiv.page/@arXiv_csLG_bot/114589956040892075
- A Certified Unlearning Approach without Access to Source Data
Umit Yigit Basaran, Sk Miraj Ahmed, Amit Roy-Chowdhury, Basak Guler
https://arxiv.org/abs/2506.06486 https://mastoxiv.page/@arXiv_csLG_bot/114658421178857085
toXiv_bot_toot
@gedankenstuecke@scholar.social2025-11-20 01:55:54
Germany's chancellor really is doing everything he can to continue his far-right fishing expeditions, this time on the back of Brazil. That'll ultimately probably lead to him paving the way for Nazi Germany 2.0 even more…
El canciller alemšn Merz y su paso en falso en Brasil – DW – 19/11/2025
https://www.dw.com/es/contento-de-poder-volver-a-alemania-merz-enfurece-a-brasil/a-74812629?maca=spa-rss-sp-inter-1008-rdf
@usul@piaille.fr2025-11-17 10:56:44
Bilan de la présence du stand #osm au capitole du libre 2025 https://forum.openstreetmap.fr/t/presence-au-capitole-du-libre-2025/34061/19?u=lhirlimann
@degrowthuk@mstdn.social2025-11-12 13:52:32
Degrowth, fears and euphemisms
Reflections beyond growth: Degrowth, fears and euphemisms Álex López translated by Mark Burton In the series Prospects for Degrowth Republished from revista 15/15\15 Reflecting on the Beyond Growth Conference. Madrid, 2025 The Beyond Growth Conference document offers us a promising future: less production, less consumption... but, curiously, more public services, more rights, more democracy, more of everything good and none of the bad.
@jamesthebard@social.linux.pizza2025-12-05 06:28:13
I stayed up far too long tonight for this one, but it was fun. Saw that we were dealing with an absolute metric ton of ranges at the very beginning so my initial thought was to reduce/merge those ranges and that's what I spent most of my time on before even tackling part 1.
It paid off tremendously and made solving everything very, very easy. There's still the Nim version to write, but I'll handle that after I get some sleep.
Solution:
@ruth_mottram@fediscience.org2025-10-16 15:41:26
"For my friends everything, for my critics, the law."
#indictment comes 2 months after #FBI agents found documents labeled “confidential”in Bolton's Washington, DC office that referenced WMDs, unsealed court records show. It was not immediately clear whether the charges prosecutors would seek were related to those documents.
If the #GrandJury decides to indict #JohnBolton [it will, ham sandwich & all], it would mark the 3rd time in recent weeks that the #DOJ has secured #criminal charges against one of #Trump's critics.
#law
@arXiv_astrophEP_bot@mastoxiv.page2025-09-25 08:37:02
Searching for GEMS: TOI-5349b is a Saturn-like planet orbiting a metal-rich early M-dwarf
Angeli Sandoval, Caleb I. Ca\~nas, Shubham Kanodia, Knicole D. Col\'on, Andrew Monson, Alexander Larsen, Tera N. Swaby, Henry A. Kobulnicky, Philip I. Choi, Sage Santomenna, Pei Qin, Michael Rodruck, William D. Cochran, Nina Brown, Madison Brady, Andreas Seifahrt, Arvind F. Gupta, Jesus Higuera, Mark E. Everett, Zuri Barksdale, Ritvik Basant, Jacob L. Bean, Scott A. Diddams, Giannina Guzm\'…
@arXiv_astrophSR_bot@mastoxiv.page2025-09-24 10:07:14
Linking Young Stellar Object Morphology to Evolutionary Stages with Self-Organizing Maps
David Hernandez, Odysseas Dionatos, Marc Audard, G\'abor Marton, Julia Roquette, Ilknur Gezer, M\'at\'e Madar\'asz, Kai L. Polsterer
https://arxiv.org/abs/2509.19069
