Solving the bowling problem with dynamic programming (simonensemble.github.io)

Screenshot of simonensemble.github.io: Solving the bowling problem with dynamic programming

First screen, captured 2 years ago.

Looks similar

Screenshot of abhamra.com: Proving Bounds for the Randomized MaxCut Approximation Algorithm in Lean4

Proving Bounds for the Randomized MaxCut Approximation Algorithm in Lean4 (abhamra.com)

55 points by todsacerdoti 10 months ago | 3 comments

Screenshot of log.pfad.fr: Optimi-Zi(n)g Sudoku-Solving

Optimi-Zi(n)g Sudoku-Solving (log.pfad.fr)

14 points by todsacerdoti 1 year ago | 2 comments

Screenshot of blog.andr2i.com: Notes from Optimizing CPU-Bound Go Hot Paths

Notes from Optimizing CPU-Bound Go Hot Paths (blog.andr2i.com)

17 points by nnx 5 months ago | 2 comments

Screenshot of laurmaedje.github.io: Typst's Math Mode Problem

Typst's Math Mode Problem (laurmaedje.github.io)

98 points by marcianx 1 year ago | 44 comments

Screenshot of abenezer.org: Hyrum’s Law in Golang

Hyrum’s Law in Golang (abenezer.org)

294 points by thunderbong 1 year ago | 176 comments

Screenshot of xingjianbai.com: Reactive Optimizers: rewrite the optimizer's source code during training

Reactive Optimizers: rewrite the optimizer's source code during training (xingjianbai.com)

27 points by matt_d 4 days ago | 2 comments

Research blog post introducing OPAL, a reactive optimizer where an LLM agent monitors training dynamics and rewrites the optimizer's source code during a training run.

optimizers llm-agents deep-learning-training muon

Looks similar

Proving Bounds for the Randomized MaxCut Approximation Algorithm in Lean4(abhamra.com)

Optimi-Zi(n)g Sudoku-Solving(log.pfad.fr)

Notes from Optimizing CPU-Bound Go Hot Paths(blog.andr2i.com)

Typst's Math Mode Problem(laurmaedje.github.io)

Hyrum’s Law in Golang(abenezer.org)

Reactive Optimizers: rewrite the optimizer's source code during training(xingjianbai.com)