Parametric Herding

By Yutian Chen, Max Welling. 2010

14 citations recorded by the source corpus.

Subfields: Optimization & Training, Statistical Learning Theory

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Optimization & Training

1. Francis R. Bach
2. Simon Lacoste-Julien
3. Alex Smola
4. Peter Richtárik
5. Yutian Chen
6. Martin Jaggi
7. Guillaume Obozinski
8. Sebastian U. Stich

In Statistical Learning Theory

1. Francis R. Bach
2. Guillaume Obozinski
3. Simon Lacoste-Julien
4. Kenji Fukumizu
5. Bernhard Schölkopf
6. Arthur Gretton
7. Alex Smola
8. Bharath K. Sriperumbudur

Citations in the corpus

• On the Equivalence between Herding and Conditional Gradient Algorithms (2012, methodology): “Unlike in frequentist learning of MRFs, the parameter w t never converges to a point in herding and actually follows a “weakly chaotic” walk (Welling & Chen, 2010).”
• Super-Samples from Kernel Herding (2010, background): “If we manage to find the optimal statext exactly at every iteration then the error in (5) decreases at a rateO(T−1).”
• Statistical inference using weak chaos and infinite memory (2010, methodology): “We have shown that the herding system that emerges from that process can be used to compress data and predict attributes of new data (Chen & Welling, 2010).”