Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. Conference contribution › Research
  2. Perceptions and expectation about Learning Analytics from a Brazilian Higher Education Institution

    Pontual Falcão, T., Ferreira Mello, R., Lins Rodrigues, R., Regueira Bast Diniz, J., Tsai, Y-S. & Gasevic, D., 23 Mar 2020, LAK '20: Proceedings of the Tenth International Conference on Learning Analytics & Knowledge. Association for Computing Machinery (ACM), p. 240-249 10 p.

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

  3. Performance Aware Convolutional Neural Network Channel Pruning for Embedded GPUs

    Radu, V., Kaszyk, J., Wen, Y., Turner, J., Cano, J., Crowley, E., Franke, B., Storkey, A. & O'Boyle, M., 19 Mar 2020, 2019 IEEE International Symposium on Workload Characterization (IISWC). Orlando, FL, USA: Institute of Electrical and Electronics Engineers (IEEE), p. 24-34 11 p.

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

  4. Physiological Monitoring with Factorial Switching Linear Dynamical Systems

    Quinn, J. A. & Williams, C. K. I., Aug 2011, Bayesian Time Series Models. Barber, D., Cemgil, A. T. & Chiappa, S. (eds.). Cambridge University Press, p. 182-204 23 p.

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

  5. Piecewise Pseudolikelihood for Efficient Training of Conditional Random Fields

    Sutton, C. & McCallum, A., 2007, Proceedings of the 24th International Conference on Machine Learning. New York, NY, USA: ACM, p. 863-870 8 p.

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

  6. Piecewise Training for Undirected Models

    Sutton, C. & McCallum, A., 2005, Proceedings of the Twenty-First Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-05). Arlington, Virginia: AUAI Press, p. 568-575 8 p.

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

  7. Piecewise Training with Parameter Independence Diagrams: Comparing Globally- and Locally-trained Linear-chain CRFs

    McCallum, A. & Sutton, C., 2004, NIPS Workshop on Learning with Structured Outputs. NIPS Foundation, 10 p.

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

  8. Policy Matters: Expert Recommendations for Learning Analytics Policy

    Scheffel, M., Tsai, Y-S., Gasevic, D. & Drachsler, H., 9 Sep 2019, Transforming Learning with Meaningful Technologies. EC-TEL 2019.. Springer, p. 510-524 15 p. (Lecture Notes in Computer Science; vol. 11722).

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

  9. Policy learning for time-bounded reachability in Continuous-Time Markov Decision Processes via doubly-stochastic gradient ascent

    Bartocci, E., Bortolussi, L., Brázdil, T., Milios, D. & Sanguinetti, G., 3 Aug 2016, Quantitative Evaluation of Systems: 13th International Conference, QEST 2016, Quebec City, QC, Canada, August 23-25, 2016, Proceedings. Springer International Publishing, p. 244-259 16 p. (Lecture Notes in Computer Science (LNCS); vol. 9826).

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

  10. Poster: Space and Time Optimal DNN Primitive Selection with Integer Linear Programming

    Wen, Y., Anderson, A., Radu, V., O'Boyle, M. & Gregg, D., 7 Nov 2019, 2019 28th International Conference on Parallel Architectures and Compilation Techniques (PACT). Institute of Electrical and Electronics Engineers (IEEE), p. 488-489 2 p.

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

  11. Predicting Ambulance Diversion in an Adult Emergency Department using a Gaussian Process

    Leegon, J., Hoot, N., Aronsky, D. & Storkey, A., 2006, AMIA 2007 Symposium Proceedings. p. 1026 1 p.

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