A Novel Compiler Transformation for Fast Sparse Matrix Multiplication in GPUs

#CUDA #Compilers #Sparse #MatrixMultiplication

https://hgpu.org/?p=29951

'Posterior Concentrations of Fully-Connected Bayesian Neural Networks with General Priors on the Weights', by Insung Kong, Yongdai Kim.

http://jmlr.org/papers/v26/24-0425.html

#priors #sparse #bnn

'High-Dimensional L2-Boosting: Rate of Convergence', by Ye Luo, Martin Spindler, Jannis Kueck.

http://jmlr.org/papers/v26/21-0725.html

#boosting #lasso #sparse

'The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning', by Nikhil Ghosh, Spencer Frei, Wooseok Ha, Bin Yu.

http://jmlr.org/papers/v26/23-1022.html

#sgd #autoencoder #sparse

'Extremal graphical modeling with latent variables via convex optimization', by Sebastian Engelke, Armeen Taeb.

http://jmlr.org/papers/v26/24-0472.html

#multivariate #graphical #sparse

'Rank-one Convexification for Sparse Regression', by Alper Atamturk, Andres Gomez.

http://jmlr.org/papers/v26/19-159.html

#sparse #lasso #convexification

Interprocedural Sparse Conditional Type Propagation

https://railsatscale.com/2025-02-24-interprocedural-sparse-conditional-type-propagation/

#HackerNews #Interprocedural #Sparse #Conditional #Type #Propagation #TypePropagation #Programming #HackerNews #SoftwareDevelopment

[New Python code: PyNoiselet] About 15 years ago, I wrote a simple set of matlab functions to compute the #Noiselet transform of Coifman et al (R. Coifman, F. Geshwind, and Y. Meyer, "Noiselets", *Applied and Computational Harmonic Analysis*, 10(1):27–44, 2001). The noiselet transform is used in #CompressiveSensing applications as well as in #Sparse signal coding as noiselets have minimally low coherence with wavelet bases (Haar and Daubechies), which is useful for sparse signal recovery.

Today, from a code request received yesterday by email, I decided to quickly rewrite this old code in Python (with the useful help of one LLM I admit).

Here is the result if you need an O(N log N) (butterfly like) algorithm to compute this transformation:

https://gitlab.com/laurentjacques/PyNoiselet

More information also in this old blog post : https://laurentjacques.gitlab.io/post/some-comments-on-noiselets/

Feel free to fork it and improve this non-optimized code.