Asia
Chefs'RandomTables: Non-TrigonometricRandom Features
We introduce chefs' random tables(CRTs), a new class of non-trigonometric random features (RFs) toapproximate Gaussian andsoftmax-kernels.
Gradient-basedAdaptiveMarkovChainMonteCarlo
The basic set up of an MCMC algorithm inanyprobabilistic (e.g.
Modelling and unsupervised learning of symmetric deformable object categories
James Thewlis, Hakan Bilen, Andrea Vedaldi
Top: inputimageswiththeaxisof symmetry superimposed (showningreen). Infact,ourmethodbuildson[38]and also learns a dense geometric embedding for objects, however, by using a different supervision principle,symmetry.
Sampling Sketches for Concave Sublinear Functions of Frequencies
Neural Information Processing Systems http://nips.cc/
Variational Inference with Tail-adaptive f-Divergence
Dilin Wang, Hao Liu, Qiang Liu
However, estimating and optimizingα-divergences require to use importance sampling, which may havelarge orinfinite variance due to heavy tails ofimportance weights.
