📊 Optimization - eaksquad

🤖Transformers Discussion

news.ycombinator.com··Hacker News

ml-from-scratch-book/code: Companion code for Machine Learning From Scratch — 10 core ML algorithms built from scratch with NumPy, compared with Scikit-learn and PyTorch.

🐍Python Code

github.com··Hacker News

Less-relevant results

The Untrainable

📞Function Calling News Blog

saranormous.substack.com··Substack

Loss Landscape Diagnosis for Gradient-Based Gray-Scott System Inversion: Disentangling the Roles of PINN Components

👁️Computer Vision Academic

arxiv.org·

Machine Learning With Manya: The Great Toy Shop Whisper Game

💬Prompt Engineering Blog

medium.com·

Designing Loops That Prompt Coding Agents: The Six I Actually Run

💬Prompt Engineering

cameronwestland.com··Hacker News

Diverse binding poses of agonistic neurotoxins on human Na v 1.6

🔗n8n Academic

nature.com

Mirror Descent Beyond Euclidean Stability: An Exponential Separation in Initialization Sensitivity

🦙Ollama Academic

arxiv.org·

Growing Pains of Starting a Secret Society

🤖n8n, automation, AI agents, Gemini, Claude, openrouter, grok, chatgpt Blog

mrmarket.bearblog.dev··Hacker News

Uniform Stability and Generalization Error of GD and SGD on Fixed-Point Parameters

🧮Embeddings Academic

arxiv.org·

A guided residual search for nonlinear state-space identification

💬Prompt Engineering Academic

arxiv.org·

Optimal Rates for Generalization of Gradient Descent Methods with Deep Neural Networks

💬Prompt Engineering Academic

arxiv.org·

Generalizable self-supervised learning for imaging flow cytometry on multi-dataset leukocyte differential

👁️Computer Vision Academic

nature.com·

Context-Driven Incremental Compression for Multi-Turn Dialogue Generation

💬Prompt Engineering Academic

arxiv.org·

princezuda/-RequiemGPT-: Fully open source and open weights built and trained by fable five with one prompt. An experience in how AI actually works

🐍Python Code

github.com··Hacker News

Adaptive Learning Rates with Surrogate Probability for Follow-the-Perturbed-Leader

💬Prompt Engineering Academic

arxiv.org·

Second-Order Path Kernel Interpolation Formulas in Machine Learning

🧮Embeddings Academic

arxiv.org·

Noise-Adaptive High-Probability Regret Bounds for Online Convex Optimization

💬Prompt Engineering Academic

arxiv.org·

iblameandrew/open-deepthink: Grok-heavy at the price of API cost. You choose the model. An unlimited army to think about your problem.

💬Prompt Engineering Code

github.com··r/LocalLLaMA

Last-Iterate Convergence of Optimistic Multiplicative Weight Update

The Smallest Brain You Can Build: A Perceptron in Python

ml-from-scratch-book/code: Companion code for Machine Learning From Scratch — 10 core ML algorithms built from scratch with NumPy, compared with Scikit-learn and PyTorch.

The Untrainable

Loss Landscape Diagnosis for Gradient-Based Gray-Scott System Inversion: Disentangling the Roles of PINN Components

Machine Learning With Manya: The Great Toy Shop Whisper Game

Designing Loops That Prompt Coding Agents: The Six I Actually Run

Diverse binding poses of agonistic neurotoxins on human Na v 1.6

Mirror Descent Beyond Euclidean Stability: An Exponential Separation in Initialization Sensitivity

Growing Pains of Starting a Secret Society

Uniform Stability and Generalization Error of GD and SGD on Fixed-Point Parameters

A guided residual search for nonlinear state-space identification

Optimal Rates for Generalization of Gradient Descent Methods with Deep Neural Networks

Generalizable self-supervised learning for imaging flow cytometry on multi-dataset leukocyte differential

Context-Driven Incremental Compression for Multi-Turn Dialogue Generation

princezuda/-RequiemGPT-: Fully open source and open weights built and trained by fable five with one prompt. An experience in how AI actually works

Adaptive Learning Rates with Surrogate Probability for Follow-the-Perturbed-Leader

Second-Order Path Kernel Interpolation Formulas in Machine Learning

Noise-Adaptive High-Probability Regret Bounds for Online Convex Optimization

iblameandrew/open-deepthink: Grok-heavy at the price of API cost. You choose the model. An unlimited army to think about your problem.