Items where City Author is "Garcez, A."

Up a level
Export as [feed] RSS 2.0 [feed] RSS
Group by: Item Type | No Grouping
Number of items: 40.

Article

Sarkar, S., Weyde, T., Garcez, A., Slabaugh, G.G., Dragicevic, S. & Percy, C. (2016). Accuracy and interpretability trade-offs in machine learning applied to safer gambling. CEUR Workshop Proceedings, 1773,

Ali, H., Tran, S.N., Benetos, E. & d'Avila Garcez, A. S. (2016). Speaker recognition with hybrid features from a deep belief network. Neural Computing and Applications, doi: 10.1007/s00521-016-2501-7

Cherla, S., Tran, S.N., Weyde, T. & Garcez, A. (2016). Generalising the Discriminative Restricted Boltzmann Machine.

Forechi, A., De Souza, A.F., Neto, J.D.O., de Aguiar, E., Badue, C., Garcez, A. & Oliveira-Santos, T. (2016). Fat-Fast VG-RAM WNN: A high performance approach. NEUROCOMPUTING, 183, pp. 56-69. doi: 10.1016/j.neucom.2015.06.104

Percy, C., Garcez, A., Dragicevic, S., França, M. V. M., Slabaugh, G.G. & Weyde, T. (2016). The Need for Knowledge Extraction: Understanding Harmful Gambling Behavior with Neural Networks. Frontiers in Artificial Intelligence and Applications, 285, pp. 974-981. doi: 10.3233/978-1-61499-672-9-974

Perotti, A., Boella, G. & Garcez, A. (2014). Runtime Verification Through Forward Chaining. Electronic Proceedings in Theoretical Computer Science, 169, pp. 68-81. doi: 10.4204/EPTCS.169.8

Ali, H., D'Avila Garcez, A.S., Tran, S.N., Zhou, X. & Iqbal, K. (2014). Unimodal late fusion for NIST i-vector challenge on speaker detection. Electronics Letters, 50(15), pp. 1098-1100. doi: 10.1049/el.2014.1207

França, M. V. M., Zaverucha, G. & Garcez, A. (2014). Fast relational learning using bottom clause propositionalization with artificial neural networks. Machine Learning, 94(1), pp. 81-104. doi: 10.1007/s10994-013-5392-1

Sigtia, S., Benetos, E., Boulanger-Lewandowski, N., Weyde, T., Garcez, A. & Dixon, S. (2014). A Hybrid Recurrent Neural Network For Music Transcription. CoRR, 14(11), p. 1623.

Tran, S. & Garcez, A. (2014). Low-cost representation for restricted Boltzmann machines. Lecture Notes in Computer Science, 8834, pp. 69-77. doi: 10.1007/978-3-319-12637-1_9

d'Avila Garcez, A. S., Gabbay, D. M. & Lamb, L. C. (2014). A neural cognitive model of argumentation with application to legal inference and decision making. Journal of Applied Logic, 12(2), pp. 109-127. doi: 10.1016/j.jal.2013.08.004

Borges, Rafael, Garcez, A. & Lamb, L. C. (2011). Learning and Representing Temporal Knowledge in Recurrent Networks. IEEE Transactions on Neural Networks, 22(12), pp. 2409-2421. doi: 10.1109/TNN.2011.2170180

Guillame-Bert, M., Broda, K. & Garcez, A. (2010). First-order logic learning in artificial neural networks. International Joint Conference on Neural Networks (IJCNN 2010), doi: 10.1109/IJCNN.2010.5596491

Garcez, A., Lamb, L. C. & Gabbay, D. M. (2007). Connectionist modal logic: Representing modalities in neural networks. Theoretical Computer Science, 371(1-2), pp. 34-53. doi: 10.1016/j.tcs.2006.10.023

Garcez, A., Gabbay, D. M., Ray, O. & Woods, J. (2007). Abductive reasoning in neural-symbolic learning systems. Topoi: An International Review of Philosophy, 26(1), pp. 37-49. doi: 10.1007/s11245-006-9005-5

Garcez, A., Gabbay, D. M. & Lamb, L. C. (2005). Value-based argumentation frameworks as neural-symbolic learning systems. Journal of Logic and Computation, 15(6), pp. 1041-1058. doi: 10.1093/logcom/exi057

Garcez, A. (2005). Fewer epistemological challenges for connectionism. Lecture Notes in Computer Science, 3526, pp. 289-325. doi: 10.1007/11494645_18

Garcez, A., Broda, K. & Gabbay, D. M. (2001). Symbolic knowledge extraction from trained neural networks: A sound approach. Artificial Intelligence, 125(1-2), pp. 153-205. doi: 10.1016/S0004-3702(00)00077-1

Garcez, A. & Zaverucha, G. (1999). The connectionist inductive learning and logic programming system. Applied Intelligence Journal, 11(1), pp. 59-77. doi: 10.1023/A:1008328630915

Book Section

Cherla, S., Weyde, T., Garcez, A. & Pearce, M. (2013). A Distributed Model For Multiple-Viewpoint Melodic Prediction. In: A. de Souza Britto Jr, F. Gouyon & S. Dixon (Eds.), Proceedings of the 14th International Society for Music Information Retrieval Conference. (pp. 15-20). International Society for Music Information Retrieval. ISBN 978-0-615-90065-0

de Penning, L., Garcez, A., Lamb, L. C. & Meyer, J. J. (2011). A Neural-Symbolic Cognitive Agent for Online Learning and Reasoning. In: Proceedings of the Twenty-Second international joint conference on Artificial Intelligence. (pp. 1653-1658). International Joint Conferences on Artificial Intelligence. ISBN 978-1-57735-514-4

Perotti, A., d'Avila Garcez, A. S. & Boella, G. Neural-Symbolic Monitoring and Adaptation. In: Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN 2015). . IEEE.

Conference or Workshop Item

Sigtia, S., Benetos, E., Boulanger-Lewandowski, N., Weyde, T., Garcez, A. & Dixon, S. (2015). A Hybrid Recurrent Neural Network For Music Transcription. Paper presented at the 40th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2015, 19-04-2015 - 24-04-2015, Brisbane, Australia.

França, M. V. M., Zaverucha, G. & Garcez, A. (2015). Neural Relational Learning Through Semi-Propositionalization of Bottom Clauses. Paper presented at the 2015 AAAI Spring Symposium Series, 23-03-2015 - 25-03-2015, Stanford University, USA.

Garcez, A., Besold, T. R., Raedt, L., Foldiak, P., Hitzler, P., Icard, T., Kuhnberger, K-U., Lamb, L. C., Miikkulainen, R. & Silver, D. L. (2015). Neural-Symbolic Learning and Reasoning: Contributions and Challenges. Paper presented at the 2015 AAAI Spring Symposium Series, 23-03-2015 - 25-03-2015, Stanford University, USA.

Tran, S., Benetos, E. & Garcez, A. (2014). Learning motion-difference features using Gaussian restricted Boltzmann machines for efficient human action recognition. Paper presented at the 2014 International Joint Conference on Neural Networks (IJCNN), 06-07-2014 - 11-07-2014, Beijing, China.

Sigtia, S., Benetos, E., Cherla, S., Weyde, T., Garcez, A. & Dixon, S. (2014). An RNN-based Music Language Model for Improving Automatic Music Transcription. Paper presented at the 15th International Society for Music Information Retrieval Conference (ISMIR), 27-10-2014 - 31-10-2014, Taipei, Taiwan.

Cherla, S., Weyde, T., Garcez, A. & Pearce, M. (2013). Learning Distributed Representations for Multiple-Viewpoint Melodic Prediction. Paper presented at the 14th International Society for Music Information Retrieval Conference, 4 - 8 Nov 2013, Curtiba, PR, Brazil.

Garcez, A. (2010). Neurons and symbols: a manifesto. Paper presented at the Dagstuhl Seminar Proceedings 10302. Learning paradigms in dynamic environments, 25 - 30 July 2010, Dagstuhl, Germany.

Komendantskaya, E., Broda, K. & Garcez, A. (2010). Using inductive types for ensuring correctness of neuro-symbolic computations. Paper presented at the 6th Conference on Computability in Europe, CiE 2010, 30 June - 4 July 2010, Ponta Delgada, Portugal.

Child, C. H. T., Stathis, K. & Garcez, A. (2007). Learning to Act with RVRL Agents. Paper presented at the 14th RCRA Workshop, Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion, Jul 2007, Rome, Italy.

Broda, K., Garcez, A. & Gabbay, D. M. (2005). Metalevel priorities and neural networks. Paper presented at the Workshop on the Foundations of Connectionist-Symbolic Integration ECAI2000, 20 - 25 August 2005, Berlin.

Hitzler, P., Bader, S. & Garcez, A. (2005). Ontology learning as a use-case for neural-symbolic integration. Paper presented at the IJCAI Workshop on Neural-Symbolic Learning and Reasoning NeSy05, 1 August 2005, Edinburgh.

Report

Renou, L. & d'Avila Garcez, A. S. (2008). Rule Extraction from Support Vector Machines: A Geometric Approach. Technical Report (Report No. TR/2008/DOC/01). Department of Computing, City University London: .

d'Avila Garcez, A. S., Hitzler, P. & Tamburrini, G. (2006). Proceedings of ECAI International Workshop on Neural-Symbolic Learning and reasoning NeSy 2006 (Report No. TR/2006/DOC/02). .

Dafas, P. & d'Avila Garcez, A. S. (2005). Applied temporal Rule Mining to Time Series (Report No. TR/2006/DOC/01). .

d'Avila Garcez, A. S. (2005). Proceedings of IJCAI International Workshop on Neural-Symbolic Learning and Reasoning NeSy 2005 (Report No. TR/2005/DOC/01). .

Garcez, A., Gabbay, D. M. & Lamb, L. C. (2004). Argumentation Neural Networks: Value-based Argumentation Frameworks as Neural-Symbolic Learning Systems (Report No. TR/2004/DOC/01). .

Garcez, A. & Gabbay, D. M. (2003). Fibring Neural Networks (Report No. TR/2003/SEG/03). .

Garcez, A., Spanoudakis, G. & Zisman, A. (2003). Proceedings of ACM ESEC/FSE International Workshop on Intelligent Technologies for Software Engineering WITSE03 (Report No. TR/2003/DOC/01). .

This list was generated on Thu Sep 21 06:15:02 2017 UTC.