nitromannitol / stochastic-quasi-newton
modular implementation of new algorithm
☆13Updated 10 years ago
Alternatives and similar repositories for stochastic-quasi-newton:
Users that are interested in stochastic-quasi-newton are comparing it to the libraries listed below
- Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.☆32Updated 9 years ago
- The information sieve for discrete variables.☆36Updated 8 years ago
- Torch implementation of the Deep Network for Global Optimization (DNGO)☆51Updated 8 years ago
- simple example of gradient-based hyperparameter optimization using tensorflow☆19Updated 9 years ago
- Experiment files for the paper "An Analysis of Unsupervised Pre-training in Light of Recent Advances", available here: http://arxiv.org/a…☆18Updated 9 years ago
- The Matlab Code for the ICML 2015 paper "Scalable Deep Poisson Factor Analysis for Topic Modeling"☆19Updated 9 years ago
- miniplaces2 deep residual network in neon☆16Updated 9 years ago
- Fast CPU implementations of several conditional probabilistic models☆36Updated last year
- Discriminant Projection Forest results, datasets, etc.☆44Updated 5 years ago
- An implementation of the Hessian-free optimization algorithm in Theano☆61Updated 13 years ago
- Look Ahead Hamiltonian Monte Carlo☆30Updated 10 years ago
- An iterative neural autoregressive distribution estimator (NADE-K)☆26Updated 10 years ago
- SparseAutoEncoder - Unsupervised Learning☆14Updated 12 years ago
- Code for Max-Margin Deep Generative Models☆12Updated 10 years ago
- A simple tool for small scale experiments using bayesian optimization☆35Updated 6 years ago
- Rank Ordered Autoencoder implementation as described in https://arxiv.org/abs/1605.01749☆33Updated 8 years ago
- Code for the arxiv paper☆9Updated 10 years ago
- ☆19Updated 7 years ago
- ☆11Updated 8 years ago
- Gopalan, P., Ruiz, F. J., Ranganath, R., & Blei, D. M. (2014). Bayesian Nonparametric Poisson Factorization for Recommendation Systems. I…☆15Updated 10 years ago
- solve LASSO formulation with Proximal Gradient Descent, Accelerated Gradient Descent, and Coordinate Gradient Descent