From fe0d9fc74740f1b51e2f498d4516579d3e48ed02 Mon Sep 17 00:00:00 2001 From: Eduardo Julian Date: Thu, 27 Jan 2022 04:41:30 -0400 Subject: Fixes for the pure-Lux JVM compiler machinery. [Part 11] --- .../differentiable_programming.md | 16 ++++ .../artificial_intelligence/machine_learning.md | 78 ++++++++++++++++++ documentation/bookmark/back_end/c++.md | 1 + documentation/bookmark/machine_learning.md | 93 ---------------------- 4 files changed, 95 insertions(+), 93 deletions(-) create mode 100644 documentation/bookmark/artificial_intelligence/differentiable_programming.md create mode 100644 documentation/bookmark/artificial_intelligence/machine_learning.md delete mode 100644 documentation/bookmark/machine_learning.md (limited to 'documentation/bookmark') diff --git a/documentation/bookmark/artificial_intelligence/differentiable_programming.md b/documentation/bookmark/artificial_intelligence/differentiable_programming.md new file mode 100644 index 000000000..9bfd27186 --- /dev/null +++ b/documentation/bookmark/artificial_intelligence/differentiable_programming.md @@ -0,0 +1,16 @@ +# Reference + +0. [Differentiable Programming in C++ - Vassil Vassilev & William Moses - CppCon 2021](https://www.youtube.com/watch?v=1QQj1mAV-eY) +0. [Demystifying Differentiable Programming: Shift/Reset the Penultimate Backpropagator](https://arxiv.org/abs/1803.10228) +0. [The Taichi Programming Language](http://taichi.graphics/) +0. [The principles behind Differentiable Programming - Erik Meijer](https://www.youtube.com/watch?v=lk0PhtSHE38) +0. [Kotlin∇: Type-safe Symbolic Differentiation for Kotlin](https://github.com/breandan/kotlingrad) +0. [Differentiable Programming Manifesto](https://github.com/apple/swift/blob/master/docs/DifferentiableProgramming.md) +0. [Backpropagation in the Simply Typed Lambda-calculus with Linear Negation](https://arxiv.org/abs/1909.13768) +0. [One-and-a-Half Simple Differential Programming Languages](https://pages.cpsc.ucalgary.ca/~robin/FMCS/FMCS2019/slides/GordonPlotkin-FMCS2019.pdf) +0. [Differentiable Programming Mega-Proposal](https://forums.swift.org/t/differentiable-programming-mega-proposal/28547) +0. https://fluxml.ai/2019/02/07/what-is-differentiable-programming.html +0. https://github.com/breandan/kotlingrad +0. https://colinraffel.com/blog/you-don-t-know-jax.html +0. https://github.com/tensorflow/mlir + diff --git a/documentation/bookmark/artificial_intelligence/machine_learning.md b/documentation/bookmark/artificial_intelligence/machine_learning.md new file mode 100644 index 000000000..a998c7aaa --- /dev/null +++ b/documentation/bookmark/artificial_intelligence/machine_learning.md @@ -0,0 +1,78 @@ +# Transformer + +0. [Transformers from scratch](http://www.peterbloem.nl/blog/transformers) + +# Exemplar + +0. https://ml5js.org/ +0. https://www.csie.ntu.edu.tw/~cjlin/libsvm/ +0. http://halide-lang.org/ + +# Reference + +0. [Why are ML Compilers so Hard?](https://petewarden.com/2021/12/24/why-are-ml-compilers-so-hard/) +0. ["Multi-Level Intermediate Representation" Compiler Infrastructure](https://github.com/tensorflow/mlir) +0. [Sampling can be faster than optimization](https://www.pnas.org/content/116/42/20881) +0. [Layer rotation: a surprisingly powerful indicator of generalization in deep networks](https://arxiv.org/abs/1806.01603v2) +0. https://nostalgebraist.tumblr.com/post/185326092369/the-transformer-explained +0. [HyperE: Hyperbolic Embeddings for Entities](https://hazyresearch.github.io/hyperE/) +0. https://www.samcoope.com/posts/playing_around_with_noise_as_targets +0. https://lobste.rs/s/hgejxf/why_is_machine_learning_most_often +0. https://boingboing.net/2018/11/12/local-optima-r-us.html/amp +0. https://crazyoscarchang.github.io/2019/02/16/seven-myths-in-machine-learning-research/ +0. https://www.c4ml.org/ +0. https://medium.com/@l2k/why-are-machine-learning-projects-so-hard-to-manage-8e9b9cf49641 +0. https://github.com/MikeInnes/diff-zoo +0. https://cloud.google.com/blog/products/ai-machine-learning/introducing-feast-an-open-source-feature-store-for-machine-learning +0. https://towardsdatascience.com/introducing-manifold-db9e90f20347 +0. http://snap.stanford.edu/graphsage/ +0. https://heartbeat.fritz.ai/capsule-networks-a-new-and-attractive-ai-architecture-bd1198cc8ad4 +0. http://super-ms.mit.edu/rum.html + +# Inductive logic programming + +0. [Inductive logic programming at 30: a new introduction](https://arxiv.org/abs/2008.07912) + +# Deep learning + +0. [GAME2020 4. Dr. Vincent Nozick Geometric Neurons](https://www.youtube.com/watch?v=KC3c_Mdj1dk) +0. [Evolution Strategies](https://lilianweng.github.io/lil-log/2019/09/05/evolution-strategies.html) +0. [Monadic Deep Learning: Performing monadic automatic differentiation in parallel](https://deeplearning.thoughtworks.school/assets/paper.pdf) +0. https://github.com/microsoft/tensorwatch +0. https://d2l.ai/ +0. https://hadrienj.github.io/posts/Deep-Learning-Book-Series-Introduction/ +0. http://nlp.seas.harvard.edu/NamedTensor +0. https://tvm.ai/ +0. https://machinelearningmastery.com/framework-for-better-deep-learning/ +0. [Geometric Understanding of Deep Learning](https://arxiv.org/abs/1805.10451) +0. https://towardsdatascience.com/what-is-geometric-deep-learning-b2adb662d91d +0. https://deeplearning4j.org/ +0. [Deep(er) learning](http://www.jneurosci.org/content/early/2018/07/13/JNEUROSCI.0153-18.2018?versioned=true) + +# Neural network + +0. https://github.com/BrainJS/brain.js +0. https://blog.jle.im/entry/practical-dependent-types-in-haskell-1.html +0. https://matloff.wordpress.com/2018/06/20/neural-networks-are-essentially-polynomial-regression/ +0. https://www.quantamagazine.org/foundations-built-for-a-general-theory-of-neural-networks-20190131#AI +0. https://rkevingibson.github.io/blog/neural-networks-as-ordinary-differential-equations/ + +# Tensor + +0. http://nlp.seas.harvard.edu/NamedTensor.html +0. http://nlp.seas.harvard.edu/NamedTensor2 + +# Meta-learning + +0. https://blog.fastforwardlabs.com/2019/05/22/metalearners-learning-how-to-learn.html +0. https://www.bayeswatch.com/2018/11/30/HTYM/ +0. https://bender.dreem.com/ + +# Model + +0. http://onnx.ai/ + +# Training + +0. https://ai.googleblog.com/2019/03/introducing-gpipe-open-source-library.html + diff --git a/documentation/bookmark/back_end/c++.md b/documentation/bookmark/back_end/c++.md index e9e684c4e..21664d692 100644 --- a/documentation/bookmark/back_end/c++.md +++ b/documentation/bookmark/back_end/c++.md @@ -1,5 +1,6 @@ # Reference +0. [Back to Basics: Move Semantics - Nicolai Josuttis - CppCon 2021](https://www.youtube.com/watch?v=Bt3zcJZIalk) 0. [Type-and-resource Safety in Modern C++ - Bjarne Stroustrup - CppCon 2021](https://www.youtube.com/watch?v=l3rvjWfBzZI) 0. [Exceptional C++ - Victor Ciura - CppCon 2021](https://www.youtube.com/watch?v=SjlfhyZn2yA) diff --git a/documentation/bookmark/machine_learning.md b/documentation/bookmark/machine_learning.md deleted file mode 100644 index 6d11d7ca0..000000000 --- a/documentation/bookmark/machine_learning.md +++ /dev/null @@ -1,93 +0,0 @@ -# Transformer - -1. [Transformers from scratch](http://www.peterbloem.nl/blog/transformers) - -# Exemplar - -1. https://ml5js.org/ -1. https://www.csie.ntu.edu.tw/~cjlin/libsvm/ -1. http://halide-lang.org/ - -# Reference - -1. [Why are ML Compilers so Hard?](https://petewarden.com/2021/12/24/why-are-ml-compilers-so-hard/) -1. ["Multi-Level Intermediate Representation" Compiler Infrastructure](https://github.com/tensorflow/mlir) -1. [Sampling can be faster than optimization](https://www.pnas.org/content/116/42/20881) -1. [Layer rotation: a surprisingly powerful indicator of generalization in deep networks](https://arxiv.org/abs/1806.01603v2) -1. https://nostalgebraist.tumblr.com/post/185326092369/the-transformer-explained -1. [HyperE: Hyperbolic Embeddings for Entities](https://hazyresearch.github.io/hyperE/) -1. https://www.samcoope.com/posts/playing_around_with_noise_as_targets -1. https://lobste.rs/s/hgejxf/why_is_machine_learning_most_often -1. https://boingboing.net/2018/11/12/local-optima-r-us.html/amp -1. https://crazyoscarchang.github.io/2019/02/16/seven-myths-in-machine-learning-research/ -1. https://www.c4ml.org/ -1. https://medium.com/@l2k/why-are-machine-learning-projects-so-hard-to-manage-8e9b9cf49641 -1. https://github.com/MikeInnes/diff-zoo -1. https://cloud.google.com/blog/products/ai-machine-learning/introducing-feast-an-open-source-feature-store-for-machine-learning -1. https://towardsdatascience.com/introducing-manifold-db9e90f20347 -1. http://snap.stanford.edu/graphsage/ -1. https://heartbeat.fritz.ai/capsule-networks-a-new-and-attractive-ai-architecture-bd1198cc8ad4 -1. http://super-ms.mit.edu/rum.html - -# Inductive logic programming - -1. [Inductive logic programming at 30: a new introduction](https://arxiv.org/abs/2008.07912) - -# Deep learning - -1. [GAME2020 4. Dr. Vincent Nozick Geometric Neurons](https://www.youtube.com/watch?v=KC3c_Mdj1dk) -1. [Evolution Strategies](https://lilianweng.github.io/lil-log/2019/09/05/evolution-strategies.html) -1. [Monadic Deep Learning: Performing monadic automatic differentiation in parallel](https://deeplearning.thoughtworks.school/assets/paper.pdf) -1. [Demystifying Differentiable Programming: Shift/Reset the Penultimate Backpropagator](https://arxiv.org/abs/1803.10228) -1. https://github.com/microsoft/tensorwatch -1. https://d2l.ai/ -1. https://hadrienj.github.io/posts/Deep-Learning-Book-Series-Introduction/ -1. http://nlp.seas.harvard.edu/NamedTensor -1. https://tvm.ai/ -1. https://machinelearningmastery.com/framework-for-better-deep-learning/ -1. [Geometric Understanding of Deep Learning](https://arxiv.org/abs/1805.10451) -1. https://towardsdatascience.com/what-is-geometric-deep-learning-b2adb662d91d -1. https://deeplearning4j.org/ -1. [Deep(er) learning](http://www.jneurosci.org/content/early/2018/07/13/JNEUROSCI.0153-18.2018?versioned=true) - -# Neural network - -1. https://github.com/BrainJS/brain.js -1. https://blog.jle.im/entry/practical-dependent-types-in-haskell-1.html -1. https://matloff.wordpress.com/2018/06/20/neural-networks-are-essentially-polynomial-regression/ -1. https://www.quantamagazine.org/foundations-built-for-a-general-theory-of-neural-networks-20190131#AI -1. https://rkevingibson.github.io/blog/neural-networks-as-ordinary-differential-equations/ - -# Tensor - -1. http://nlp.seas.harvard.edu/NamedTensor.html -1. http://nlp.seas.harvard.edu/NamedTensor2 - -# Meta-learning - -1. https://blog.fastforwardlabs.com/2019/05/22/metalearners-learning-how-to-learn.html -1. https://www.bayeswatch.com/2018/11/30/HTYM/ -1. https://bender.dreem.com/ - -# Model - -1. http://onnx.ai/ - -# Training - -1. https://ai.googleblog.com/2019/03/introducing-gpipe-open-source-library.html - -# Differentiable programming - -1. [The Taichi Programming Language](http://taichi.graphics/) -1. [The principles behind Differentiable Programming - Erik Meijer](https://www.youtube.com/watch?v=lk0PhtSHE38) -1. [Kotlin∇: Type-safe Symbolic Differentiation for Kotlin](https://github.com/breandan/kotlingrad) -1. [Differentiable Programming Manifesto](https://github.com/apple/swift/blob/master/docs/DifferentiableProgramming.md) -1. [Backpropagation in the Simply Typed Lambda-calculus with Linear Negation](https://arxiv.org/abs/1909.13768) -1. [One-and-a-Half Simple Differential Programming Languages](https://pages.cpsc.ucalgary.ca/~robin/FMCS/FMCS2019/slides/GordonPlotkin-FMCS2019.pdf) -1. [Differentiable Programming Mega-Proposal](https://forums.swift.org/t/differentiable-programming-mega-proposal/28547) -1. https://fluxml.ai/2019/02/07/what-is-differentiable-programming.html -1. https://github.com/breandan/kotlingrad -1. https://colinraffel.com/blog/you-don-t-know-jax.html -1. https://github.com/tensorflow/mlir - -- cgit v1.2.3