[ICML 2019] Day 3 - Robotics, Good ol’ Sparse Coding, misc. applications, Transfer, Multitask and Active Learning

Quite tired. Will only post pointers to materials that are of potential interest to me, and investigate them on a rainy week-end back in HK.

Test of Time Award:

  • Online Dictionary Learning for Sparse Coding ** from my professors at ENS **
    • slides
    • Authors think their paper was successful and had a big impact because of a good timing (since datasets were becoming larger and larger, there was a need for more scalable matrix factorization methods), a combination of maths and engineering (they release an efficient software package: the SPAMS toolbox; pip install spams), flexibility in the usage of the package (it was used in other domains, in unexpected contexts).

Session Applications

Session Transfer and Multitask Learning

Session Active Learning


Like many papers this year, this one aims at providing an interpretable model. Interpretability/Explanability is definitely a trending topic. In brief, the latent kernel is a composition of base kernels which is learnt through a stochastic kernel process. The simple composition mechanism can provide a natural language explanation of the model.

Discovering automatically the latent covariance structures for Gaussian Processes on multivariate time series