Kernel Carpentry for Online Regression Using Randomly Varying Coefficient Model

Edakunni, Narayanan Unny; Schaal, Stefan; Vijayakumar, Sethu

Kernel Carpentry for Online Regression Using Randomly Varying Coefficient Model

Narayanan Unny Edakunni, Stefan Schaal, Sethu Vijayakumar

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Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 762-766.

Abstract

We present a Bayesian formulation of locally weighted learning (LWL) using the novel concept of a randomly varying coefficient model. Based on this, we propose a mechanism for multivariate non-linear regression using spatially localised linear models that learns completely independent of each other, uses only local information and adapts the local model complexity in a data driven fashion. We derive online updates for the model parameters based on variational Bayesian EM. The evaluation of the proposed algorithm against other state-of-the-art methods reveal the excellent, robust generalization performance beside surprisingly efficient time and space complexity properties. This paper, for the first time, brings together the computational efficiency and the adaptability of ‘non-competitive’ locally weighted learning schemes and the modelling guarantees of the Bayesian formulation.

Narayanan Unny Edakunni, Stefan Schaal, and Sethu Vijayakumar. 2007. Kernel Carpentry for Online Regression Using Randomly Varying Coefficient Model. In Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07. IJCAI, 762–766. https://ijcai.org/proceedings/2007/122

@inproceedings{ijcai2007p122,
  title     = {Kernel Carpentry for Online Regression Using Randomly Varying Coefficient Model},
  author    = {Edakunni, Narayanan Unny and Schaal, Stefan and Vijayakumar, Sethu},
  booktitle = {Proceedings of the Twentieth International Joint Conference on
               Artificial Intelligence, {IJCAI-07}},
  publisher = {International Joint Conferences on Artificial Intelligence},
  editor    = {Ramon López de Mántaras},
  pages     = {762--766},
  year      = {2007},
  url       = {https://ijcai.org/proceedings/2007/122},
}

TY  - CPAPER
TI  - Kernel Carpentry for Online Regression Using Randomly Varying Coefficient Model
AU  - Edakunni, Narayanan Unny
AU  - Schaal, Stefan
AU  - Vijayakumar, Sethu
T2  - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07
PB  - International Joint Conferences on Artificial Intelligence
PY  - 2007
SP  - 762
EP  - 766
UR  - https://ijcai.org/proceedings/2007/122
ER  -