Understanding the Design of Optimizers with me
dev.to·12h·
Discuss: DEV
⛰️Gradient Descent
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Phased DMD: Few-step Distribution Matching Distillation via Score Matching within Subintervals
arxiv.org·11h
⛰️Gradient Descent
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A Practitioner's Guide to Kolmogorov-Arnold Networks
arxiviq.substack.com·22h·
Discuss: Substack
⛰️Gradient Descent
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Can-t stop till you get enough
cant.bearblog.dev·22h·
Discuss: Hacker News
🗂️AnnData
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Fast, Scalable LDA in C++ with Stochastic Variational Inference
github.com·1h·
Discuss: r/cpp
🔢Embeddings
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Convex Optimization (or Mathematical Programming) in Go
reddit.com·2d·
Discuss: r/golang
📐Computational Geometry
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Understanding Support Vector Machines SVM: Origins, Working, and Real-World Applications
dev.to·7h·
Discuss: DEV
🗺️UMAP
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Enhanced Richardson Extrapolation via Adaptive Kernel Regression and Uncertainty Quantification
dev.to·2h·
Discuss: DEV
📊Empirical Bayes
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Masked Softmax Layers in PyTorch
mcognetta.github.io·55m·
Discuss: Hacker News
⛰️Gradient Descent
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pDANSE: Particle-based Data-driven Nonlinear State Estimation from Nonlinear Measurements
arxiv.org·11h
⛰️Gradient Descent
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Gated DeltaNet (Linear Attention variant in Qwen3-Next and Kimi Linear)
sebastianraschka.com·13h·
Discuss: r/LLM
⛰️Gradient Descent
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A faster problem-solving tool that guarantees feasibility
news.mit.edu·11h
⛰️Gradient Descent
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Weak-To-Strong Generalization
lesswrong.com·1d
📊Empirical Bayes
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A fun application of Green’s functions and geometric algebra: Residue calculus
peeterjoot.com·12h
📐Computational Geometry
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Deep Learning Part — 9 : Optimizers are what you need.
pub.towardsai.net·3d
⛰️Gradient Descent
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