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Learning Models with Uniform Performance via Distributionally RobustOptimization

dev.to·1d·

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🧠Deep Learning

Cross Entropy Derivatives, Part 6: Using gradient descent to reach the final result

dev.to·36m·

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🧠Deep Learning

B2 L2 U2 F2 U2 R2 U B2 F2 D2 F' D' R2 U2 R' U' R2 B' F2 L' F

metafilter.com·1d

A Trust-First Recipe AI Agent Using Algolia (No Hallucinations)

fayzakseo.com·6h·

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🧠Deep Learning

Linux 6.19 readies release with Intel, AMD gains

kite.kagi.com·22h

Internalizing LLM Reasoning via Discovery and Replay of Latent Actions

arxiv.org·2d

🧠Deep Learning

ML-LIB: Machine Learning Library Proposed For The Linux Kernel

phoronix.com·2d·

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🧠Deep Learning

On the use of LLMs to generate a dataset of Neural Networks

arxiv.org·3d

🧠Deep Learning

Naughty is Nice!

yamlscript.org·1d

reddit.com·23h·

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Building Interactive C/C++ workflows in Jupyter through Clang-REPL [video]

fosdem.org·1d·

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Both GCC and Clang generate strange/inefficient code

codingmarginalia.blogspot.com·1d·

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Tip of the Week #124: <code>absl::StrFormat()</code>

abseil.io·22h

A Normalized Gaussian Wasserstein Distance for Tiny Object Detection

paperium.net·7h·

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🧠Deep Learning

A Lot Of Exciting Changes To Look Forward To With Linux 6.20 -- Or Linux 7.0

phoronix.com·6h

LLMs Are Prediction Machines

kaelandt.github.io·1h·

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🧠Deep Learning

Tip of the Week #108: Avoid <code>std::bind</code>

abseil.io·22h

How to refer to the result location

ziggit.dev·2d

Getting started with C++ MathGL on Windows and Linux

solarianprogrammer.com·22h

Understanding LLM Inference Engines: Inside Nano-vLLM (Part 2)

neutree.ai·2d·

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🧠Deep Learning

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