Scott Poll

Statistical Learning Theory · 2007–2009

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Statistical Learning Theory — 5 citations into it

Whom Scott Poll trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Vladimir Naumovich Vapnik

Who trusts Scott Poll overall

1. Michael G. Pecht
2. Yinjiao Xing
3. D. Roman
4. Kailong Liu
5. Lei Ren
6. Anthony Barré
7. Yi Li
8. C. Frey

Papers from Scott Poll's perspective

Ordered by how strongly the researchers Scott Poll trusts endorse each paper. Same corpus, a different order for every researcher.

1. A training algorithm for optimal margin classifiers
2. A and V
3. Impedance measurements on lead–acid batteries for state-of-charge, state-of-health and cranking capability prognosis in electric and hybrid electric vehicles
4. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking (IEEE Transactions on Signal Processing)
5. An integrated approach to battery health monitoring using bayesian regression and state estimation (2007 IEEE Autotestcon)
6. Nonlinear observers for predicting state-of-charge and state-of-health of lead-acid batteries for hybrid-electric vehicles (IEEE Transactions on Vehicular Technology)
7. Dynamic lithium-ion battery model for system simulation
8. Subset Selection in Regression
9. The Nature of Statistical Learning
10. A Bayesian Approach to Filtering Junk E-Mail

Their papers

• Prognostics Methods for Battery Health Monitoring Using a Bayesian Framework (2009) — 769 citations
• An integrated approach to battery health monitoring using bayesian regression and state estimation (2007) — 184 citations