I have moved to France (Sept., 2016); my new webpage
Zoltán Szabó [on Bitbucket, GitHub]
Powerful linear-time two-sample tests:
A linear-time nonparametric two-sample test which returns a set of local features indicating why the two distribution differ; its power matches quadratic-time tests.
KMC (Kernel Hamiltonian Monte Carlo):
- A gradient-free adaptive MCMC algorithm based on Hamiltonian Monte Carlo (HMC). On target densities where classical HMC is not an option due to intractable gradients, KMC adaptively learns the target's gradient structure from the sample path, by fitting an exponential family model in a Reproducing Kernel Hilbert Space.
LL-LVM (Locally Linear Latent Variable Model):
- A probabilistic model for non-linear manifold discovery that describes a joint distribution over observations, their manifold coordinates and locally linear maps conditioned on a set of neighbourhood relationships; 'Bayesian LLE'.
Kernel-EP (Kernel based just-in-time Expectation Propagation):
- A fast, online algorithm for nonparametric learning of EP message updates.
- Information Theoretical Estimators (ITE) Toolbox:
- ITE provides
- several entropy, mutual information, divergence, association measure, cross quantity, distribution kernel estimators,
- with applications in (i) distribution regression (supervised entropy learning, aerosol prediction based on multispectral satellite images), (ii) independent subspace analysis and its extensions, (iii) information theoretical image registration.
OSDL [Online Group-Structured Dictionary Learning (rar/zip/tar)]:
- Structured-sparse dictionary learning method which (i) is online, (ii) allows overlapping group structures with (iii) non-convex group-structure inducing regularization, and (iv) handles incomplete observations.