Inverse Ising Inference Using All the Data
2012 (English)In: Physical Review Letters, ISSN 0031-9007, Vol. 108, no 9, 090201- p.Article in journal (Refereed) Published
We show that a method based on logistic regression, using all the data, solves the inverse Ising problem far better than mean-field calculations relying only on sample pairwise correlation functions, while still computationally feasible for hundreds of nodes. The largest improvement in reconstruction occurs for strong interactions. Using two examples, a diluted Sherrington-Kirkpatrick model and a two-dimensional lattice, we also show that interaction topologies can be recovered from few samples with good accuracy and that the use of l(1) regularization is beneficial in this process, pushing inference abilities further into low-temperature regimes.
Place, publisher, year, edition, pages
2012. Vol. 108, no 9, 090201- p.
IdentifiersURN: urn:nbn:se:kth:diva-92054DOI: 10.1103/PhysRevLett.108.090201ISI: 000300943400001ScopusID: 2-s2.0-84857876275OAI: oai:DiVA.org:kth-92054DiVA: diva2:512152
QC 201203262012-03-262012-03-262012-03-26Bibliographically approved