Laboratory for Computational and Statistical Learning
Massachusetts Institute of Technology, Bldg. 46-5155, 43 Vassar Street, Cambridge, MA
Pinned Repositories
bless
Fast algorithm for leverage score sampling, low rank (kernel) matrix factorization and PCA
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)
FALKON_paper
FALKON implementation used in the experimental section of "FALKON: An Optimal Large Scale Kernel Method"
GURLS
GURLS: a Least Squares Library for Supervised Learning
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.
iterreg
Iterative regularization solvers for non strongly convex penalties : L1, low rank, etc.
matMTL
Multi Task Learning Package for Matlab
NystromCoRe
Rudi, A., Camoriano, R. and Rosasco, L., Less is more: Nyström computational regularization. In Advances in Neural Information Processing Systems, December 2015.
NYTRO
Camoriano, R.^, Angles, T.^, Rudi, A. and Rosasco, L., Nytro: When subsampling meets early stopping. In Artificial Intelligence and Statistics, May 2016.
RegML
Laboratory for Computational and Statistical Learning's Repositories
LCSL/GURLS
GURLS: a Least Squares Library for Supervised Learning
LCSL/FALKON_paper
FALKON implementation used in the experimental section of "FALKON: An Optimal Large Scale Kernel Method"
LCSL/bless
Fast algorithm for leverage score sampling, low rank (kernel) matrix factorization and PCA
LCSL/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)
LCSL/NystromCoRe
Rudi, A., Camoriano, R. and Rosasco, L., Less is more: Nyström computational regularization. In Advances in Neural Information Processing Systems, December 2015.
LCSL/RegML
LCSL/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.
LCSL/iterreg
Iterative regularization solvers for non strongly convex penalties : L1, low rank, etc.
LCSL/NYTRO
Camoriano, R.^, Angles, T.^, Rudi, A. and Rosasco, L., Nytro: When subsampling meets early stopping. In Artificial Intelligence and Statistics, May 2016.
LCSL/matMTL
Multi Task Learning Package for Matlab
LCSL/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.
LCSL/rff-hgp
Random feature approximation of heteroscedastic Gaussian processes (CoRL 2023).
LCSL/MLCClabs
2017
LCSL/nys-koop-lqr
Nystroem-based Koopman operator regression for linear quadratic control.
LCSL/MLCC-Labs
This repository contains the implementations of the MLCC laboratories in python