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#sparse — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #sparse, aggregated by home.social.

  1. Pelajari cara menghemat ruang disk dan kuota internet menggunakan Git Sparse Checkout. Panduan lengkap mengelola repositori besar dengan mengabaikan folder berat.

    #fediverse #Teknik #Sparse #Checkout

    dalam.web.id/warta-tekno/tekni

  2. Sparse nén mô hình fine-tuned và dataset thành delta từ bản gốc. Nén 14GB xuống 1.4GB (lossless) hoặc 50MB (tương đương LoRA), phục hồi trong 4 giây. Áp dụng sau khi training, phù hợp mọi mô hình đã huấn luyện. Hiệu quả cho AI y tế, tài chính, pháp lý. #AI #MachineLearning #FineTuning #ModelCompression #Sparse #TríTuệNhânTạo #HọcMáy #NénMôHình

    reddit.com/r/LocalLLaMA/commen

  3. Công cụ mới mang tên Sparse giúp nén các mô hình AI đã fine-tune dưới dạng "delta" (phần chênh lệch) so với mô hình gốc.

    Điểm nổi bật:
    - Nén mô hình 14GB xuống còn 1.4GB (không mất dữ liệu) hoặc 50MB (tương đương LoRA).
    - Áp dụng được cho MỌI mô hình đã huấn luyện xong, không cần can thiệp lúc training.
    - Tốc độ khôi phục cực nhanh (khoảng 4 giây).
    - Giải pháp tối ưu cho lưu trữ và phân phối các mô hình AI chuyên biệt.

    #AI #MachineLearning #Sparse #Compression #DeepLearning #CongNghe #TriTueNh

  4. SpiNNcloud’s SpiNNaker2 Deployed at UT San Antonio for NSF-Funded THOR Project A brain-inspired supercomputing platform has been deployed at the University of Texas at San Antonio (UTSA), aimed a...

    #Features #National #Science #Foundation #neuromorphic #computing #sparse #models #SpiNNaker2 #SpiNNcloud #THOR

    Origin | Interest | Match
  5. 🎉 Oh, joy! 🙄 Signal's masterminds have blessed us with a "Sparse #Post #Quantum #Ratchet," because apparently, regular encryption just isn't fancy enough anymore. 🤓 Don't you feel safer already from those imaginary quantum computer threats that totally exist in 2025? 🚀🔒
    signal.org/blog/spqr/ #Signal #Sparse #QuantumEncryption #CyberSecurity #FutureTech #HackerNews #ngated

  6. 🎉 Oh, joy! 🙄 Signal's masterminds have blessed us with a "Sparse #Post #Quantum #Ratchet," because apparently, regular encryption just isn't fancy enough anymore. 🤓 Don't you feel safer already from those imaginary quantum computer threats that totally exist in 2025? 🚀🔒
    signal.org/blog/spqr/ #Signal #Sparse #QuantumEncryption #CyberSecurity #FutureTech #HackerNews #ngated

  7. 🎉 Oh, joy! 🙄 Signal's masterminds have blessed us with a "Sparse #Post #Quantum #Ratchet," because apparently, regular encryption just isn't fancy enough anymore. 🤓 Don't you feel safer already from those imaginary quantum computer threats that totally exist in 2025? 🚀🔒
    signal.org/blog/spqr/ #Signal #Sparse #QuantumEncryption #CyberSecurity #FutureTech #HackerNews #ngated

  8. 🎉 Oh, joy! 🙄 Signal's masterminds have blessed us with a "Sparse #Post #Quantum #Ratchet," because apparently, regular encryption just isn't fancy enough anymore. 🤓 Don't you feel safer already from those imaginary quantum computer threats that totally exist in 2025? 🚀🔒
    signal.org/blog/spqr/ #Signal #Sparse #QuantumEncryption #CyberSecurity #FutureTech #HackerNews #ngated

  9. 'Posterior Concentrations of Fully-Connected Bayesian Neural Networks with General Priors on the Weights', by Insung Kong, Yongdai Kim.

    jmlr.org/papers/v26/24-0425.ht

    #priors #sparse #bnn

  10. 'Posterior Concentrations of Fully-Connected Bayesian Neural Networks with General Priors on the Weights', by Insung Kong, Yongdai Kim.

    jmlr.org/papers/v26/24-0425.ht

    #priors #sparse #bnn

  11. 'Posterior Concentrations of Fully-Connected Bayesian Neural Networks with General Priors on the Weights', by Insung Kong, Yongdai Kim.

    jmlr.org/papers/v26/24-0425.ht

    #priors #sparse #bnn

  12. 'Posterior Concentrations of Fully-Connected Bayesian Neural Networks with General Priors on the Weights', by Insung Kong, Yongdai Kim.

    jmlr.org/papers/v26/24-0425.ht

    #priors #sparse #bnn

  13. 'Posterior Concentrations of Fully-Connected Bayesian Neural Networks with General Priors on the Weights', by Insung Kong, Yongdai Kim.

    jmlr.org/papers/v26/24-0425.ht

    #priors #sparse #bnn

  14. 'High-Dimensional L2-Boosting: Rate of Convergence', by Ye Luo, Martin Spindler, Jannis Kueck.

    jmlr.org/papers/v26/21-0725.ht

    #boosting #lasso #sparse

  15. 'High-Dimensional L2-Boosting: Rate of Convergence', by Ye Luo, Martin Spindler, Jannis Kueck.

    jmlr.org/papers/v26/21-0725.ht

    #boosting #lasso #sparse

  16. 'High-Dimensional L2-Boosting: Rate of Convergence', by Ye Luo, Martin Spindler, Jannis Kueck.

    jmlr.org/papers/v26/21-0725.ht

    #boosting #lasso #sparse

  17. 'High-Dimensional L2-Boosting: Rate of Convergence', by Ye Luo, Martin Spindler, Jannis Kueck.

    jmlr.org/papers/v26/21-0725.ht

    #boosting #lasso #sparse

  18. 'High-Dimensional L2-Boosting: Rate of Convergence', by Ye Luo, Martin Spindler, Jannis Kueck.

    jmlr.org/papers/v26/21-0725.ht

    #boosting #lasso #sparse

  19. 'The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning', by Nikhil Ghosh, Spencer Frei, Wooseok Ha, Bin Yu.

    jmlr.org/papers/v26/23-1022.ht

    #sgd #autoencoder #sparse

  20. 'The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning', by Nikhil Ghosh, Spencer Frei, Wooseok Ha, Bin Yu.

    jmlr.org/papers/v26/23-1022.ht

    #sgd #autoencoder #sparse

  21. 'The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning', by Nikhil Ghosh, Spencer Frei, Wooseok Ha, Bin Yu.

    jmlr.org/papers/v26/23-1022.ht

    #sgd #autoencoder #sparse

  22. 'The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning', by Nikhil Ghosh, Spencer Frei, Wooseok Ha, Bin Yu.

    jmlr.org/papers/v26/23-1022.ht

    #sgd #autoencoder #sparse

  23. 'The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning', by Nikhil Ghosh, Spencer Frei, Wooseok Ha, Bin Yu.

    jmlr.org/papers/v26/23-1022.ht

    #sgd #autoencoder #sparse

  24. 'Extremal graphical modeling with latent variables via convex optimization', by Sebastian Engelke, Armeen Taeb.

    jmlr.org/papers/v26/24-0472.ht

    #multivariate #graphical #sparse

  25. 'Extremal graphical modeling with latent variables via convex optimization', by Sebastian Engelke, Armeen Taeb.

    jmlr.org/papers/v26/24-0472.ht

    #multivariate #graphical #sparse

  26. 'Extremal graphical modeling with latent variables via convex optimization', by Sebastian Engelke, Armeen Taeb.

    jmlr.org/papers/v26/24-0472.ht

    #multivariate #graphical #sparse

  27. 'Extremal graphical modeling with latent variables via convex optimization', by Sebastian Engelke, Armeen Taeb.

    jmlr.org/papers/v26/24-0472.ht

    #multivariate #graphical #sparse

  28. 'Extremal graphical modeling with latent variables via convex optimization', by Sebastian Engelke, Armeen Taeb.

    jmlr.org/papers/v26/24-0472.ht

    #multivariate #graphical #sparse

  29. 'Bayesian Sparse Gaussian Mixture Model for Clustering in High Dimensions', by Dapeng Yao, Fangzheng Xie, Yanxun Xu.

    jmlr.org/papers/v26/23-0142.ht

    #sparse #clustering #clusters