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optimization

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Optimize Your Libraries with Webpack
Using a library in your webpack project? Use these tips to make your bundle smaller!
webpack  optimization  performance  babel  lodash  moment  react 
yesterday by spaceninja
Neuro-Dynamic Programming An Overview
By one of the authors of the book "neuro-dynamic programming" a nice survey from mid naughties on learning and optimization. Insists on the pitfalls and partial solutions. Makes reference to reinforced learning (ie Sutton & Barto)
coink  optimization  machine-learning  neuro-dynamic  programming  bertsekas 
2 days ago by paunit
CPU | PICO-8 Wiki | Fandom
"PICO-8 keeps track of CPU usage using two values: Lua cycles and system cycles. Most operations affect Lua cycles, but some functions have an additional system cycle cost.

There are 4194304 cycles in a second (2^22), so about 69905 cycles per frame at 60 FPS, or 139810 cycles at 30 FPS. The function call stat(1) returns the total (Lua + system) cycle ratio for the current frame, and stat(2) returns the system ratio."
optimization  pico-8  lua 
3 days ago by jwh
From models of galaxies to atoms, simple AI shortcuts speed up simulations by billions of times | Science | AAAS
With little training, neural networks create accurate emulators for physics, astronomy, and earth science
AI  simulation  research  science  optimization 
3 days ago by basemaly
On Parallel Programming
"Theoretical frameworks such a Little's Law, Amdahl's Law, and others can help in making design decisions that lend themselves to parallelism. Understanding and exploiting the different sources of parallelism across the hardware/software stack are the key for high-performance implementations. But perhaps most importantly, it is essential to select an architecture and a programming model, which maximizes your chances of exploiting parallelism for your specific workload."

Note that this is definitely not on concurrency, but on parallelism (threads, shared-nothing, etc.)
piperesearch  optimization  programming  reference 
4 days ago by mechazoidal
Optimization of Conditional Value-at-Risk
Article focus on the minimization structure implicit in tail VaR (wrt fixed proba structure in the context of the article) and general application to portfolio optimization. This is indeed not too far from the hedging problem addressed in DH.
More detailed analysis in the convex case (ie where loss is a linear function of position which is part of a convex set)
coink  risk  management  conditional  VaR  dynamic  programming  optimization  coherent  measure 
4 days ago by paunit

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