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@arXiv_csLG_bot@mastoxiv.page
2025-12-22 13:54:45

Replaced article(s) found for cs.LG. arxiv.org/list/cs.LG/new
[3/5]:
- Look-Ahead Reasoning on Learning Platforms
Haiqing Zhu, Tijana Zrnic, Celestine Mendler-D\"unner
arxiv.org/abs/2511.14745 mastoxiv.page/@arXiv_csLG_bot/
- Deep Gaussian Process Proximal Policy Optimization
Matthijs van der Lende, Juan Cardenas-Cartagena
arxiv.org/abs/2511.18214 mastoxiv.page/@arXiv_csLG_bot/
- Spectral Concentration at the Edge of Stability: Information Geometry of Kernel Associative Memory
Akira Tamamori
arxiv.org/abs/2511.23083 mastoxiv.page/@arXiv_csLG_bot/
- xGR: Efficient Generative Recommendation Serving at Scale
Sun, Liu, Zhang, Wu, Yang, Liang, Li, Ma, Liang, Ren, Zhang, Liu, Zhang, Qian, Yang
arxiv.org/abs/2512.11529 mastoxiv.page/@arXiv_csLG_bot/
- Credit Risk Estimation with Non-Financial Features: Evidence from a Synthetic Istanbul Dataset
Atalay Denknalbant, Emre Sezdi, Zeki Furkan Kutlu, Polat Goktas
arxiv.org/abs/2512.12783 mastoxiv.page/@arXiv_csLG_bot/
- The Semantic Illusion: Certified Limits of Embedding-Based Hallucination Detection in RAG Systems
Debu Sinha
arxiv.org/abs/2512.15068 mastoxiv.page/@arXiv_csLG_bot/
- Towards Reproducibility in Predictive Process Mining: SPICE -- A Deep Learning Library
Stritzel, H\"uhnerbein, Rauch, Zarate, Fleischmann, Buck, Lischka, Frey
arxiv.org/abs/2512.16715 mastoxiv.page/@arXiv_csLG_bot/
- Differentially private Bayesian tests
Abhisek Chakraborty, Saptati Datta
arxiv.org/abs/2401.15502 mastoxiv.page/@arXiv_statML_bo
- SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning
Paul Mangold, Sergey Samsonov, Safwan Labbi, Ilya Levin, Reda Alami, Alexey Naumov, Eric Moulines
arxiv.org/abs/2402.04114
- Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?
Guiomar Pescador-Barrios, Sarah Filippi, Mark van der Wilk
arxiv.org/abs/2408.07588 mastoxiv.page/@arXiv_statML_bo
- Non-Perturbative Trivializing Flows for Lattice Gauge Theories
Mathis Gerdes, Pim de Haan, Roberto Bondesan, Miranda C. N. Cheng
arxiv.org/abs/2410.13161 mastoxiv.page/@arXiv_heplat_bo
- Dynamic PET Image Prediction Using a Network Combining Reversible and Irreversible Modules
Sun, Zhang, Xia, Sun, Chen, Yang, Liu, Zhu, Liu
arxiv.org/abs/2410.22674 mastoxiv.page/@arXiv_eessIV_bo
- Targeted Learning for Variable Importance
Xiaohan Wang, Yunzhe Zhou, Giles Hooker
arxiv.org/abs/2411.02221 mastoxiv.page/@arXiv_statML_bo
- Refined Analysis of Federated Averaging and Federated Richardson-Romberg
Paul Mangold, Alain Durmus, Aymeric Dieuleveut, Sergey Samsonov, Eric Moulines
arxiv.org/abs/2412.01389 mastoxiv.page/@arXiv_statML_bo
- Embedding-Driven Data Distillation for 360-Degree IQA With Residual-Aware Refinement
Abderrezzaq Sendjasni, Seif-Eddine Benkabou, Mohamed-Chaker Larabi
arxiv.org/abs/2412.12667 mastoxiv.page/@arXiv_csCV_bot/
- 3D Cell Oversegmentation Correction via Geo-Wasserstein Divergence
Peter Chen, Bryan Chang, Olivia A Creasey, Julie Beth Sneddon, Zev J Gartner, Yining Liu
arxiv.org/abs/2502.01890 mastoxiv.page/@arXiv_csCV_bot/
- DHP: Discrete Hierarchical Planning for Hierarchical Reinforcement Learning Agents
Shashank Sharma, Janina Hoffmann, Vinay Namboodiri
arxiv.org/abs/2502.01956 mastoxiv.page/@arXiv_csRO_bot/
- Foundation for unbiased cross-validation of spatio-temporal models for species distribution modeling
Diana Koldasbayeva, Alexey Zaytsev
arxiv.org/abs/2502.03480
- GraphCompNet: A Position-Aware Model for Predicting and Compensating Shape Deviations in 3D Printing
Juheon Lee (Rachel), Lei (Rachel), Chen, Juan Carlos Catana, Hui Wang, Jun Zeng
arxiv.org/abs/2502.09652 mastoxiv.page/@arXiv_csCV_bot/
- LookAhead Tuning: Safer Language Models via Partial Answer Previews
Liu, Wang, Luo, Yuan, Sun, Liang, Zhang, Zhou, Hooi, Deng
arxiv.org/abs/2503.19041 mastoxiv.page/@arXiv_csCL_bot/
- Constraint-based causal discovery with tiered background knowledge and latent variables in single...
Christine W. Bang, Vanessa Didelez
arxiv.org/abs/2503.21526 mastoxiv.page/@arXiv_statML_bo
toXiv_bot_toot

@arXiv_csDC_bot@mastoxiv.page
2026-01-21 13:28:36

Device Association and Resource Allocation for Hierarchical Split Federated Learning in Space-Air-Ground Integrated Network
Haitao Zhao, Xiaoyu Tang, Bo Xu, Jinlong Sun, Linghao Zhang
arxiv.org/abs/2601.13817

@arXiv_csLG_bot@mastoxiv.page
2025-12-22 13:54:35

Replaced article(s) found for cs.LG. arxiv.org/list/cs.LG/new
[2/5]:
- The Diffusion Duality
Sahoo, Deschenaux, Gokaslan, Wang, Chiu, Kuleshov
arxiv.org/abs/2506.10892 mastoxiv.page/@arXiv_csLG_bot/
- Multimodal Representation Learning and Fusion
Jin, Ge, Xie, Luo, Song, Bi, Liang, Guan, Yeong, Song, Hao
arxiv.org/abs/2506.20494 mastoxiv.page/@arXiv_csLG_bot/
- The kernel of graph indices for vector search
Mariano Tepper, Ted Willke
arxiv.org/abs/2506.20584 mastoxiv.page/@arXiv_csLG_bot/
- OptScale: Probabilistic Optimality for Inference-time Scaling
Youkang Wang, Jian Wang, Rubing Chen, Xiao-Yong Wei
arxiv.org/abs/2506.22376 mastoxiv.page/@arXiv_csLG_bot/
- Boosting Revisited: Benchmarking and Advancing LP-Based Ensemble Methods
Fabian Akkerman, Julien Ferry, Christian Artigues, Emmanuel Hebrard, Thibaut Vidal
arxiv.org/abs/2507.18242 mastoxiv.page/@arXiv_csLG_bot/
- MolMark: Safeguarding Molecular Structures through Learnable Atom-Level Watermarking
Runwen Hu, Peilin Chen, Keyan Ding, Shiqi Wang
arxiv.org/abs/2508.17702 mastoxiv.page/@arXiv_csLG_bot/
- Dual-Distilled Heterogeneous Federated Learning with Adaptive Margins for Trainable Global Protot...
Fatema Siddika, Md Anwar Hossen, Wensheng Zhang, Anuj Sharma, Juan Pablo Mu\~noz, Ali Jannesari
arxiv.org/abs/2508.19009 mastoxiv.page/@arXiv_csLG_bot/
- STDiff: A State Transition Diffusion Framework for Time Series Imputation in Industrial Systems
Gary Simethy, Daniel Ortiz-Arroyo, Petar Durdevic
arxiv.org/abs/2508.19011 mastoxiv.page/@arXiv_csLG_bot/
- EEGDM: Learning EEG Representation with Latent Diffusion Model
Shaocong Wang, Tong Liu, Yihan Li, Ming Li, Kairui Wen, Pei Yang, Wenqi Ji, Minjing Yu, Yong-Jin Liu
arxiv.org/abs/2508.20705 mastoxiv.page/@arXiv_csLG_bot/
- Data-Free Continual Learning of Server Models in Model-Heterogeneous Cloud-Device Collaboration
Xiao Zhang, Zengzhe Chen, Yuan Yuan, Yifei Zou, Fuzhen Zhuang, Wenyu Jiao, Yuke Wang, Dongxiao Yu
arxiv.org/abs/2509.25977 mastoxiv.page/@arXiv_csLG_bot/
- Fine-Tuning Masked Diffusion for Provable Self-Correction
Jaeyeon Kim, Seunggeun Kim, Taekyun Lee, David Z. Pan, Hyeji Kim, Sham Kakade, Sitan Chen
arxiv.org/abs/2510.01384 mastoxiv.page/@arXiv_csLG_bot/
- A Generic Machine Learning Framework for Radio Frequency Fingerprinting
Alex Hiles, Bashar I. Ahmad
arxiv.org/abs/2510.09775 mastoxiv.page/@arXiv_csLG_bot/
- ASecond-Order SpikingSSM for Wearables
Kartikay Agrawal, Abhijeet Vikram, Vedant Sharma, Vaishnavi Nagabhushana, Ayon Borthakur
arxiv.org/abs/2510.14386 mastoxiv.page/@arXiv_csLG_bot/
- Utility-Diversity Aware Online Batch Selection for LLM Supervised Fine-tuning
Heming Zou, Yixiu Mao, Yun Qu, Qi Wang, Xiangyang Ji
arxiv.org/abs/2510.16882 mastoxiv.page/@arXiv_csLG_bot/
- Seeing Structural Failure Before it Happens: An Image-Based Physics-Informed Neural Network (PINN...
Omer Jauhar Khan, Sudais Khan, Hafeez Anwar, Shahzeb Khan, Shams Ul Arifeen
arxiv.org/abs/2510.23117 mastoxiv.page/@arXiv_csLG_bot/
- Training Deep Physics-Informed Kolmogorov-Arnold Networks
Spyros Rigas, Fotios Anagnostopoulos, Michalis Papachristou, Georgios Alexandridis
arxiv.org/abs/2510.23501 mastoxiv.page/@arXiv_csLG_bot/
- Semi-Supervised Preference Optimization with Limited Feedback
Seonggyun Lee, Sungjun Lim, Seojin Park, Soeun Cheon, Kyungwoo Song
arxiv.org/abs/2511.00040 mastoxiv.page/@arXiv_csLG_bot/
- Towards Causal Market Simulators
Dennis Thumm, Luis Ontaneda Mijares
arxiv.org/abs/2511.04469 mastoxiv.page/@arXiv_csLG_bot/
- Incremental Generation is Necessary and Sufficient for Universality in Flow-Based Modelling
Hossein Rouhvarzi, Anastasis Kratsios
arxiv.org/abs/2511.09902 mastoxiv.page/@arXiv_csLG_bot/
- Optimizing Mixture of Block Attention
Guangxuan Xiao, Junxian Guo, Kasra Mazaheri, Song Han
arxiv.org/abs/2511.11571 mastoxiv.page/@arXiv_csLG_bot/
- Assessing Automated Fact-Checking for Medical LLM Responses with Knowledge Graphs
Shasha Zhou, Mingyu Huang, Jack Cole, Charles Britton, Ming Yin, Jan Wolber, Ke Li
arxiv.org/abs/2511.12817 mastoxiv.page/@arXiv_csLG_bot/
toXiv_bot_toot

@arXiv_csLG_bot@mastoxiv.page
2025-12-22 11:50:31

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

@arXiv_csLG_bot@mastoxiv.page
2025-12-22 11:50:19

Crosslisted article(s) found for cs.LG. arxiv.org/list/cs.LG/new
[1/3]:
- Optimizing Text Search: A Novel Pattern Matching Algorithm Based on Ukkonen's Approach
Xinyu Guan, Shaohua Zhang
arxiv.org/abs/2512.16927 mastoxiv.page/@arXiv_csDS_bot/
- SpIDER: Spatially Informed Dense Embedding Retrieval for Software Issue Localization
Shravan Chaudhari, Rahul Thomas Jacob, Mononito Goswami, Jiajun Cao, Shihab Rashid, Christian Bock
arxiv.org/abs/2512.16956 mastoxiv.page/@arXiv_csSE_bot/
- MemoryGraft: Persistent Compromise of LLM Agents via Poisoned Experience Retrieval
Saksham Sahai Srivastava, Haoyu He
arxiv.org/abs/2512.16962 mastoxiv.page/@arXiv_csCR_bot/
- Colormap-Enhanced Vision Transformers for MRI-Based Multiclass (4-Class) Alzheimer's Disease Clas...
Faisal Ahmed
arxiv.org/abs/2512.16964 mastoxiv.page/@arXiv_eessIV_bo
- Probing Scientific General Intelligence of LLMs with Scientist-Aligned Workflows
Wanghan Xu, et al.
arxiv.org/abs/2512.16969 mastoxiv.page/@arXiv_csAI_bot/
- PAACE: A Plan-Aware Automated Agent Context Engineering Framework
Kamer Ali Yuksel
arxiv.org/abs/2512.16970 mastoxiv.page/@arXiv_csAI_bot/
- A Women's Health Benchmark for Large Language Models
Elisabeth Gruber, et al.
arxiv.org/abs/2512.17028 mastoxiv.page/@arXiv_csCL_bot/
- Perturb Your Data: Paraphrase-Guided Training Data Watermarking
Pranav Shetty, Mirazul Haque, Petr Babkin, Zhiqiang Ma, Xiaomo Liu, Manuela Veloso
arxiv.org/abs/2512.17075 mastoxiv.page/@arXiv_csCL_bot/
- Disentangled representations via score-based variational autoencoders
Benjamin S. H. Lyo, Eero P. Simoncelli, Cristina Savin
arxiv.org/abs/2512.17127 mastoxiv.page/@arXiv_statML_bo
- Biosecurity-Aware AI: Agentic Risk Auditing of Soft Prompt Attacks on ESM-Based Variant Predictors
Huixin Zhan
arxiv.org/abs/2512.17146 mastoxiv.page/@arXiv_csCR_bot/
- Application of machine learning to predict food processing level using Open Food Facts
Arora, Chauhan, Rana, Aditya, Bhagat, Kumar, Kumar, Semar, Singh, Bagler
arxiv.org/abs/2512.17169 mastoxiv.page/@arXiv_qbioBM_bo
- Systemic Risk Radar: A Multi-Layer Graph Framework for Early Market Crash Warning
Sandeep Neela
arxiv.org/abs/2512.17185 mastoxiv.page/@arXiv_qfinRM_bo
- Do Foundational Audio Encoders Understand Music Structure?
Keisuke Toyama, Zhi Zhong, Akira Takahashi, Shusuke Takahashi, Yuki Mitsufuji
arxiv.org/abs/2512.17209 mastoxiv.page/@arXiv_csSD_bot/
- CheXPO-v2: Preference Optimization for Chest X-ray VLMs with Knowledge Graph Consistency
Xiao Liang, Yuxuan An, Di Wang, Jiawei Hu, Zhicheng Jiao, Bin Jing, Quan Wang
arxiv.org/abs/2512.17213 mastoxiv.page/@arXiv_csCV_bot/
- Machine Learning Assisted Parameter Tuning on Wavelet Transform Amorphous Radial Distribution Fun...
Deriyan Senjaya, Stephen Ekaputra Limantoro
arxiv.org/abs/2512.17245 mastoxiv.page/@arXiv_condmatmt
- AlignDP: Hybrid Differential Privacy with Rarity-Aware Protection for LLMs
Madhava Gaikwad
arxiv.org/abs/2512.17251 mastoxiv.page/@arXiv_csCR_bot/
- Practical Framework for Privacy-Preserving and Byzantine-robust Federated Learning
Baolei Zhang, Minghong Fang, Zhuqing Liu, Biao Yi, Peizhao Zhou, Yuan Wang, Tong Li, Zheli Liu
arxiv.org/abs/2512.17254 mastoxiv.page/@arXiv_csCR_bot/
- Verifiability-First Agents: Provable Observability and Lightweight Audit Agents for Controlling A...
Abhivansh Gupta
arxiv.org/abs/2512.17259 mastoxiv.page/@arXiv_csMA_bot/
- Warmer for Less: A Cost-Efficient Strategy for Cold-Start Recommendations at Pinterest
Saeed Ebrahimi, Weijie Jiang, Jaewon Yang, Olafur Gudmundsson, Yucheng Tu, Huizhong Duan
arxiv.org/abs/2512.17277 mastoxiv.page/@arXiv_csIR_bot/
- LibriVAD: A Scalable Open Dataset with Deep Learning Benchmarks for Voice Activity Detection
Ioannis Stylianou, Achintya kr. Sarkar, Nauman Dawalatabad, James Glass, Zheng-Hua Tan
arxiv.org/abs/2512.17281 mastoxiv.page/@arXiv_csSD_bot/
- Penalized Fair Regression for Multiple Groups in Chronic Kidney Disease
Carter H. Nakamoto, Lucia Lushi Chen, Agata Foryciarz, Sherri Rose
arxiv.org/abs/2512.17340 mastoxiv.page/@arXiv_statME_bo
toXiv_bot_toot

@arXiv_mathOC_bot@mastoxiv.page
2025-11-14 09:37:10

S-D-RSM: Stochastic Distributed Regularized Splitting Method for Large-Scale Convex Optimization Problems
Maoran Wang, Xingju Cai, Yongxin Chen
arxiv.org/abs/2511.10133 arxiv.org/pdf/2511.10133 arxiv.org/html/2511.10133
arXiv:2511.10133v1 Announce Type: new
Abstract: This paper investigates the problems large-scale distributed composite convex optimization, with motivations from a broad range of applications, including multi-agent systems, federated learning, smart grids, wireless sensor networks, compressed sensing, and so on. Stochastic gradient descent (SGD) and its variants are commonly employed to solve such problems. However, existing algorithms often rely on vanishing step sizes, strong convexity assumptions, or entail substantial computational overhead to ensure convergence or obtain favorable complexity. To bridge the gap between theory and practice, we integrate consensus optimization and operator splitting techniques (see Problem Reformulation) to develop a novel stochastic splitting algorithm, termed the \emph{stochastic distributed regularized splitting method} (S-D-RSM). In practice, S-D-RSM performs parallel updates of proximal mappings and gradient information for only a randomly selected subset of agents at each iteration. By introducing regularization terms, it effectively mitigates consensus discrepancies among distributed nodes. In contrast to conventional stochastic methods, our theoretical analysis establishes that S-D-RSM achieves global convergence without requiring diminishing step sizes or strong convexity assumptions. Furthermore, it achieves an iteration complexity of $\mathcal{O}(1/\epsilon)$ with respect to both the objective function value and the consensus error. Numerical experiments show that S-D-RSM achieves up to 2--3$\times$ speedup compared to state-of-the-art baselines, while maintaining comparable or better accuracy. These results not only validate the algorithm's theoretical guarantees but also demonstrate its effectiveness in practical tasks such as compressed sensing and empirical risk minimization.
toXiv_bot_toot

@chris@mstdn.chrisalemany.ca
2026-01-08 02:00:40

note: links to post of #ice shooting video.
As horrid, tragic, and fascist as this day's news has been... the one bright spot around here is that people are learning about why federated, peer distributed, and non-corporate platforms are essential for our democracy.
We used to all* believe that this was what made the corporate platforms special, but that was just a fake, a feint, and ultimately, a fascism.
sharing this video is democracy, freedom,
resistance.
Spread the word! The #SocialWeb will fight this tyranny!
*tbf: some folks saw the writing on the wall better and a lot earlier than the rest of us. Respect to them.
#peertube #usa #cdnpoli #canpoli #theAmericanFascist #ice #minnessota #fascism #ediverse #socialweb
cc: to some pioneer politicians on Fedi. @… @… @robbotteril@socialbc.ca @… @… social.chinwag.org/@FediThing/