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Laboratory for Computational and Statistical Learning (@LCSL)

LCSL

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GURLS

GURLS: a Least Squares Library for Supervised Learning

FALKON_paper

FALKON implementation used in the experimental section of "FALKON: An Optimal Large Scale Kernel Method"

bless

Fast algorithm for leverage score sampling, low rank (kernel) matrix factorization and PCA

RegML

NystromCoRe

Rudi, A., Camoriano, R. and Rosasco, L., Less is more: Nyström computational regularization. In Advances in Neural Information Processing Systems, December 2015.

dpp-vfx

Experiments for the first very fast and exact DPP sampler (Dereziński M, Calandriello D, Valko M. Exact sampling of determinantal point processes with sublinear time preprocessing. NeurIPS 2019)

iterreg

Iterative regularization solvers for non strongly convex penalties : L1, low rank, etc.

incremental_multiclass_RLSC

Camoriano, R.^, Pasquale, G.^, Ciliberto, C., Natale, L., Rosasco, L. and Metta, G., Incremental robot learning of new objects with fixed update time. In IEEE International Conference on Robotics and Automation (ICRA), May 2017.

NYTRO

Camoriano, R.^, Angles, T.^, Rudi, A. and Rosasco, L., Nytro: When subsampling meets early stopping. In Artificial Intelligence and Statistics, May 2016.

MultiplePassesSGM

Lin, J., Camoriano, R. and Rosasco, L., Generalization properties and implicit regularization for multiple passes SGM. In International Conference on Machine Learning, June 2016.

rff-hgp

Random feature approximation of heteroscedastic Gaussian processes (CoRL 2023).

MLCClabs

nys-koop-lqr

Nystroem-based Koopman operator regression for linear quadratic control.