Estimating relatedness via data compression

By Brendan Juba. 2006

45 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

How researchers see this paper

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

In Artificial Intelligence

1. Qiang Yang
2. Antonio Torralba
3. Josh Tenenbaum
4. Ruslan Salakhutdinov
5. Yu Zhang
6. Yoshua Bengio
7. Sergey Levine
8. Dacheng Tao

In Computational Theory and Mathematics

1. Antonio Torralba
2. M. H. Mahmud
3. Ruslan Salakhutdinov
4. Qiang Yang
5. Josh Tenenbaum
6. Sylvian R. Ray
7. Yu Zhang

Citations in the corpus

• A Survey on Multi-Task Learning (2017, methodology): “Moreover, as well as the four tools to upper-bound the generalization performance, the Kolmogorov complexity, an analysis tool from information theory, is used in [227] to bound the generalization performance.”
• Learning to share visual appearance for multiclass object detection (2011, methodology): “Our approach to bounding LBayes(ZT ) follows that of previous work on Bayesian GLM regret bounds with logloss (Kakade & Ng, 2004; Kakade et al., 2005; Seeger et al., 2008), relying on the following well-known result: Proposition 2.1 (Kakade & Ng (2004); Banerjee (2006)).”
• Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations (2007, methodology): “We also develop a practical approximation to the method and use it to transfer information between8 arbitrarily chosen databases from the UCI ML repository.”