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A random key based estimation of distribution algorithm for the permutation flowshop scheduling problem. (2017)
Conference Proceeding
AYODELE, M., MCCALL, J., REGNIER-COUDERT, O. and BOWIE, L. 2017. A random key based estimation of distribution algorithm for the permutation flowshop scheduling problem. In Proceedings of the 2017 IEEE congress on evolutionary computation (CEC 2017), 5-8 June 2017, San Sebastian, Spain. New York: IEEE [online], article number 7969591, pages 2364-2371. Available from: https://doi.org/10.1109/CEC.2017.7969591

Random Key (RK) is an alternative representation for permutation problems that enables application of techniques generally used for continuous optimisation. Although the benefit of RKs to permutation optimisation has been shown, its use within Estima... Read More about A random key based estimation of distribution algorithm for the permutation flowshop scheduling problem..

Neural induction of a lexicon for fast and interpretable stance classification. (2017)
Conference Proceeding
CLOS, J. and WIRATUNGA, N. 2017. Neural induction of a lexicon for fast and interpretable stance classification. In Gracia, J., Bond, F., McCrae, J.P., Buitelaar, P., Chiarcos, C. and Hellmann, S. (eds.) Language, data and knowledge: proceedings of the 1st International conference on language, data and knowledge (LDK 2017), 19-20 June 2017, Galway, Ireland. Lecture notes in computer science, 10318. Cham: Springer [online], pages 181-193. Available from: https://doi.org/10.1007/978-3-319-59888-8_16

Large-scale social media classification faces the following two challenges: algorithms can be hard to adapt to Web-scale data, and the predictions that they provide are difficult for humans to understand. Those two challenges are solved at the cost o... Read More about Neural induction of a lexicon for fast and interpretable stance classification..

Stokes coordinates. (2017)
Conference Proceeding
SAVOYE, Y. 2017. Stokes coordinates. In Spencer, S.N. (ed.) Proceedings of the 33rd Spring conference on computer graphics (SCCG'17), 15-17 May 2017, Mikulov, Czech Republic. New York: ACM [online], article number 5. Available from: https://doi.org/10.1145/3154353.3154354

Cage-based structures are reduced subspace deformers enabling non-isometric stretching deformations induced by clothing or muscle bulging. In this paper, we reformulate the cage-based rigging as an incompressible Stokes problem in the vorticity space... Read More about Stokes coordinates..

Deep reward shaping from demonstrations. (2017)
Conference Proceeding
HUSSEIN, A., ELYAN, E., GABER, M.M. and JAYNE, C. 2017. Deep reward shaping from demonstrations. In Proceedings of the 2017 International joint conference on neural networks (IJCNN 2017), 14-19 May 2017, Anchorage, USA. Piscataway: IEEE [online], article number 7965896, pages 510-517. Available from: https://doi.org/10.1109/IJCNN.2017.7965896

Deep reinforcement learning is rapidly gaining attention due to recent successes in a variety of problems. The combination of deep learning and reinforcement learning allows for a generic learning process that does not consider specific knowledge of... Read More about Deep reward shaping from demonstrations..

An edit distance between graph correspondences. (2017)
Conference Proceeding
MORENO-GARCIA, C.F., SERRATOSA, F. and JIANG, X. 2017. An edit distance between graph correspondences. In Foggia, P., Liu, C.-L. and Vento, M (eds.) 2017. Graph-based representations in pattern recognition: proceedings of the 11th Image analysis in patter recognition technical committee 15th (IAPR-TC-15) international workshop (GbRPR 2017), 16-18 May 2017, Anacapri, Italy. Cham: Springer [online], pages 232-241. Available from: https://doi.org/10.1007/978-3-319-58961-9_21

The Hamming Distance has been largely used to calculate the dissimilarity of a pair of correspondences (also known as labellings or matchings) between two structures (i.e. sets of points, strings or graphs). Although it has the advantage of being sim... Read More about An edit distance between graph correspondences..

Predicting emotional reaction in social networks. (2017)
Conference Proceeding
CLOS, J., BANDHAKAVI, A., WIRATUNGA, N. and CABANAC, G. 2017. Predicting emotional reaction in social networks. In Jose, J.M., Hauff, C., Altingovde, I.S., Song, D., Albakour, D., Watt, S. and Tait, J. (eds.) Advances in information retrieval: proceedings of the 39th European conference on information retrieval (ECIR 2017), 8-13 April 2017, Aberdeen, UK. Lecture notes in computer science, 10193. Cham: Springer [online], pages 527-533. Available from: https://doi.org/10.1007/978-3-319-56608-5_44

Online content has shifted from static and document-oriented to dynamic and discussion-oriented, leading users to spend an increasing amount of time navigating online discussions in order to participate in their social network. Recent work on emotion... Read More about Predicting emotional reaction in social networks..