Quantum Bootstrap Aggregation

Conference paper

Windridge, D. and Nagarajan, R. 2017. Quantum Bootstrap Aggregation. de Barros, J., Coecke, B. and Pothos, E. (ed.) Quantum Interaction. San Francisco, CA, USA 20 - 22 Jul 2016 Springer. pp. 115-121 https://doi.org/10.1007/978-3-319-52289-0_9
TypeConference paper
TitleQuantum Bootstrap Aggregation
AuthorsWindridge, D. and Nagarajan, R.
Abstract

We set out a strategy for quantizing attribute bootstrap aggregation to enable variance-resilient quantum machine learning. To do so, we utilise the linear decomposability of decision boundary parameters in the Rebentrost et al. Support Vector Machine to guarantee that stochastic measurement of the output quantum state will give rise to an ensemble decision without destroying the superposition over projective feature subsets induced within the chosen SVM implementation. We achieve a linear performance advantage, O(d), in addition to the existing O(log(n)) advantages of quantization as applied to Support Vector Machines. The approach extends to any form of quantum learning giving rise to linear decision boundaries.

Research GroupFoundations of Computing group
ConferenceQuantum Interaction
Page range115-121
Proceedings TitleQuantum Interaction: 10th International Conference, QI 2016, San Francisco, CA, USA, July 20-22, 2016, Revised Selected Papers
SeriesLecture Notes in Computer Science
Editorsde Barros, J., Coecke, B. and Pothos, E.
ISSN0302-9743
Electronic1611-3349
ISBN
Hardcover9783319522883
Electronic9783319522890
PublisherSpringer
Publication dates
Online26 Jan 2017
Print26 Jan 2017
Publication process dates
Deposited15 Feb 2017
Accepted01 Nov 2016
Output statusPublished
Accepted author manuscript
Copyright Statement

The final publication is available at http://link.springer.com/book/10.1007/978-3-319-52289-0

Additional information

Published as: Windridge D., Nagarajan R. (2017) Quantum Bootstrap Aggregation. In: de Barros J., Coecke B., Pothos E. (eds) Quantum Interaction. QI 2016. Lecture Notes in Computer Science, vol 10106. Springer, Cham

Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-319-52289-0_9
Scopus EID2-s2.0-85011957088
Web of Science identifierWOS:000418792100009
LanguageEnglish
Book titleQuantum Interaction: 10th International Conference, QI 2016, San Francisco, CA, USA, July 20-22, 2016, Revised Selected Papers
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Poh, N., Tirunagari, S. and Windridge, D. 2014. Challenges in designing an online healthcare platform for personalised patient analytics. 2014 IEEE Symposium on Computational Intelligence in Big Data (CIBD). Orlando, FL., USA 09 - 12 Dec 2014 IEEE. pp. 1-6 https://doi.org/10.1109/CIBD.2014.7011526
Patient level analytics using self-organising maps: a case study on type-1 diabetes self-care survey responses
Tirunagari, S., Poh, N., Aliabadi, K., Windridge, D. and Cooke, D. 2014. Patient level analytics using self-organising maps: a case study on type-1 diabetes self-care survey responses. 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). Orlando, FL., USA 09 - 12 Dec 2014 Institute of Electrical and Electronics Engineers (IEEE). pp. 304-309 https://doi.org/10.1109/CIDM.2014.7008682
Non-enumerative cross validation for the determination of structural parameters in feature-selective SVMs
Chernousova, E., Levdik, P., Tatarchuk, A., Mottl, V. and Windridge, D. 2014. Non-enumerative cross validation for the determination of structural parameters in feature-selective SVMs. 22nd International Conference on Pattern Recognition ICPR 2014. Stockholm, Sweden 24 - 28 Aug 2014 Institute of Electrical and Electronics Engineers (IEEE). pp. 3654-3659 https://doi.org/10.1109/ICPR.2014.628
Linear regression via elastic net: non-enumerative leave-one-out verification of feature selection
Chernousova, E., Razin, N., Krasotkina, O., Mottl, V. and Windridge, D. 2014. Linear regression via elastic net: non-enumerative leave-one-out verification of feature selection. in: Aleskerov, F., Goldengorin, B. and Pardalos, P. (ed.) Clusters, Orders, and Trees: Methods and Applications: In Honor of Boris Mirkin's 70th Birthday New York Springer.
Automatic annotation of tennis games: an integration of audio, vision, and learning
Yan, F., Kittler, J., Windridge, D., Christmas, W., Mikolajczyk, K., Cox, S. and Huang, Q. 2014. Automatic annotation of tennis games: an integration of audio, vision, and learning. Image and Vision Computing. 32 (11), pp. 896-903. https://doi.org/10.1016/j.imavis.2014.08.004
A kernel-based framework for medical big-data analytics
Windridge, D. and Bober, M. 2014. A kernel-based framework for medical big-data analytics. in: Interactive Knowledge Discovery and Data Mining in Biomedical Informatics: State-of-the-Art and Future Challenges Springer. pp. 197-208
Verification of concurrent quantum protocols by equivalence checking
Ardeshir-Larijani, E., Gay, S. and Nagarajan, R. 2014. Verification of concurrent quantum protocols by equivalence checking. TACAS 2014: 20th International Conference on Tools and Algorithms for the Construction and Analysis of Systems. Grenoble, France 05 - 13 Apr 2014 Springer. https://doi.org/10.1007/978-3-642-54862-8_42
Model checking for communicating quantum processes
Davidson, T., Gay, S., Mlnařík, H., Nagarajan, R. and Papanikolaou, N. 2012. Model checking for communicating quantum processes. International Journal of Unconventional Computing. 8 (1), pp. 73-98.
Lossless quantum prefix compression for communication channels that are always open
Müller, M., Rogers, C. and Nagarajan, R. 2009. Lossless quantum prefix compression for communication channels that are always open. Physical Review A. 79 (1). https://doi.org/10.1103/PhysRevA.79.012302
Equivalence checking of quantum protocols
Ardeshir-Larijani, E., Gay, S. and Nagarajan, R. 2013. Equivalence checking of quantum protocols. in: Piterman, N. and Smolka, S. (ed.) Tools and Algorithms for the Construction and Analysis of Systems : 19th International Conference Proceedings (TACAS 2013). Berlin Springer.
QMC: a model checker for quantum systems
Gay, S., Nagarajan, R. and Papanikolaou, N. 2008. QMC: a model checker for quantum systems. in: Gupta, A. and Malik, S. (ed.) Computer Aided Verification : 20th International Conference, (CAV 2008) Proceedings Berlin Springer.
High throughput screening for mammography using a human-computer interface with rapid serial visual presentation (RSVP)
Abbey, C., Hope, C., Sterr, A., Elangovan, P., Geades, N., Windridge, D., Young, K., Wells, K. and Mello-Thoms, C. 2013. High throughput screening for mammography using a human-computer interface with rapid serial visual presentation (RSVP). SPIE Proceedings Vol. 8673. https://doi.org/10.1117/12.2007557
Looking to score: the dissociation of goal influence on eye movement and meta-attentional allocation in a complex dynamic natural scene
Taya, S., Windridge, D. and Osman, M. 2012. Looking to score: the dissociation of goal influence on eye movement and meta-attentional allocation in a complex dynamic natural scene. PLoS ONE. 7 (6). https://doi.org/10.1371/journal.pone.0039060
Addressing missing values in kernel-based multimodal biometric fusion using neutral point substitution
Poh, N., Windridge, D., Mottl, V., Tatarchuk, A. and Eliseyev, A. 2010. Addressing missing values in kernel-based multimodal biometric fusion using neutral point substitution. IEEE Transactions on Information Forensics and Security. 5 (3), pp. 461-469. https://doi.org/10.1109/TIFS.2010.2053535