Tootfinder

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

My solution to the problem @… mentions:
1. Make password the •only• login field. No username/email! Just password, and you’re in!
2. Because they now identify users, passwords must to be unique across all users in a system.
3. For security reasons, require passwords to be unique across all sites on the entire Internet. A password can be used at most once in human history.
4. This renders account recovery impossible in many cases.
5. Over time, users are thus able to use fewer and fewer sites, eventually being forced offline altogether.
6. Success!
https://mastodon.social/@jwz/115776511391611416

This is a very useful overview of the EU Digital Identity Landscape
#eIDAS #EU

EU Digital Identity Landscape - Interactive Map & Solutions
Explore the comprehensive map of European Digital Identity Solutions. An interactive visualization of eID schemes, EUDI Wallets, and Trust Services across the EU and neighboring countries.

NYC-based Opti, an enterprise identity security service that uses AI to analyze user, system, and access relationships, raised a $20M seed led by YL Ventures (Chris Metinko/Axios)
https://www.axios.com/pro/enterprise-software-deals/…

Exclusive: Identity security startup Opti raises $20M
YL Ventures, Mayfield Fund and Hetz Ventures led the seed round.

The man fatally shot by federal officers in Minneapolis this morning has been identified as
#Alex #Jeffrey #Pretti,
Pretti, 37, has an address listed in south Minneapolis.
At a news conference, Minneapolis Police Chief Bri…

Live: Federal agents shot and killed Minneapolis man; DHS officials say he was armed
A bystander video shows several agents wrestling with the man on a city sidewalk moments before the shooting. Police chief Brian O’Hara issued a plea for calm as protesters gathered at the scene: “Please do not destroy our own city.”

Ya wanna know what is a bad idea? “AI-directed experimentation and manufacturing” is.
potus should have just called it a hand out for Oracle.
It is a solution searching for a problem. It literally gives 90 days for them to identify 20 problems it might solve.
It uses public funds for private research.

Launching the Genesis Mission
By the authority vested in me as President by the Constitution and the laws of the United States of America, it is hereby ordered: Section 1.  Purpose.

Highly recommend not to identify yourself with any technology.
Doesn’t matter if it’s AI, bicycles, cars, video games, old computers, photography or Hi-Fi equipment.
If someone says something bad about it (doesn’t matter if true or not) and you feel personally attacked—take a step back and think long and hard about your feelings.
Can you be “into” something? Yes, of course. But don’t lose yourself.

Amazon unveils its Autonomous Threat Analysis system, born from a 2024 internal hackathon, to use AI agents competing in teams to identify vulnerabilities (Lily Hay Newman/Wired)
https://www.wired.com/story/amazon-autonomous-threat-analysis/

Amazon Is Using Specialized AI Agents for Deep Bug Hunting
Born out of an internal hackathon, Amazon’s Autonomous Threat Analysis system uses a variety of specialized AI agents to detect weaknesses and propose fixes to the company’s platforms.

Minneapolis shooting live:
City officials report another incident
‘involving federal law enforcement’
This shooting comes less than three weeks after Renee Good was shot and killed by an ICE officer in the city
City officials said on Saturday morning in a statement that the “shooting involving federal law enforcement”
and occurred in the area of West 26th Street and Nicollet Avenue South
– and that they are
“working to confirm additional details”.

Tying housing costs to homelessness rates, researchers have identified inflection points:
🔸When rents in a community exceed about a third of the median income, homelessness escalates.
🔸“As the share of low-income households with severe rent burdens grows, so does their risk of homelessness,”
said Thomas Byrne of Boston College, an author of the study.
Gregg Colburn, a housing expert at the University of Washington, found that
Seattle and San Francisco, with so…

Trump Says ‘Housing First’ Failed the Homeless. Here’s What the Evidence Says.
The Trump administration has sought to move away from the model, which supporters call “evidence based” but opponents consider overly permissive.