Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. Similar neural adaptation mechanisms underlying face gender and tilt aftereffects

    Zhao, C. R., Series, P., Hancock, P. J. B. & Bednar, J. A., Sep 2011, In : Vision Research. 51, 18, p. 2021-2030 10 p.

    Research output: Contribution to journalArticle

  2. Blind source separation for fmri signals using spatial independent component analysis

    Zhong, M., Tang, H. & Tang, Y., Dec 2002, In : ACTA Biophysica Sinica. 19, 1, p. 79-83 5 p.

    Research output: Contribution to journalArticle

  3. Latent Bayesian melding for integrating individual and population models

    Zhong, M., Goddard, N. & Sutton, C., 2015, Advances in Neural Information Processing Systems 28 (NIPS 2015). p. 3617-3625 9 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  4. Signal Aggregate Constraints in Additive Factorial HMMs, with Application to Energy Disaggregation

    Zhong, M., Goddard, N. & Sutton, C., 2014, Advances in Neural Information Processing Systems 27 (NIPS 2014). Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N. D. & Weinberger, K. Q. (eds.). Palais des Congrès de Montréal, Montréal, CANADA : Curran Associates Inc, p. 3590-3598 9 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  5. The Mathematical Principles of AFNI and One of its Applications to the Research of the Functional Neuroimages

    Zhong, M., Tang, H. & Feng, J., 2002, In : Journal of Basic Science and Engineering. 3, 4 p.

    Research output: Contribution to journalArticle

  6. An EM Algorithm for Independent Component Analysis in the Presence of Gaussian Noise

    Zhong, M., Tang, H., Wang, H. & Tang, Y., Jan 2004, In : Neural Information Processing - Letters and Reviews. p. 11-17 7 p.

    Research output: Contribution to journalArticle

  7. Gaussian Regression and Optimal Finite Dimensional Linear Models

    Zhu, H., Williams, C. K. I., Rohwer, R., Morciniec, M. & Hammel, M., 1997, 20 p.

    Research output: Working paper

  8. Adaptive Stochastic Primal-Dual Coordinate Descent for Separable Saddle Point Problems

    Zhu, Z. & Storkey, A., 2015, Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part I. Appice, A., Rodrigues, P. P., Santos Costa, V., Soares, C., Gama, J. & Jorge, A. (eds.). Springer International Publishing, p. 645-658 14 p. (Lecture Notes in Computer Science; vol. 9284).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  9. Stochastic Parallel Block Coordinate Descent for Large-scale Saddle Point Problems

    Zhu, Z. & Storkey, A. J., Feb 2016, Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence. AAAI Press, p. 2429-2534 106 p. (AAAI'16).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution