Dr Alistair Shilton

STAFF PROFILE

Position

Research Fellow

Faculty

Applied Artificial Intel Inst

Department

A2I2P

Campus

Geelong Waurn Ponds Campus

Publications

Filter by

2018

Exploiting strategy-space diversity for batch Bayesian optimization

S Gupta, Alistair Shilton, Santu Rana, Svetha Venkatesh

(2018), Vol. 84, pp. 538-547, AISTATS 2018 : Proceedings of the International Conference on Artificial Intelligence and Statistics, Playa Blanca, Lanzarote, Canary Islands, E1

conference

Multi-target optimisation via Bayesian optimisation and linear programming

A Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh

(2018), UAI 2018: Proceedings of the 34th Conference on Uncertainty in Artificial Intelligence, Monterey, Calif., E1

conference

Expected hypervolume improvement with constraints

M Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, svetha Venkatesh

(2018), pp. 3238-3243, ICPR 2018 : Proceedings of the 24th International Conference on Pattern Recognition, Beijing, China, E1

conference
2017

Regret bounds for transfer learning in Bayesian optimisation

A Shilton, S Gupta, S Rana, S Venkatesh

(2017), Vol. 54, pp. 1-9, AISTATS 2017 : Machine Learning Research : Proceedings of the 20th Artificial Intelligence and Statistics International Conference, Fort Lauderdale, Florida, E1

conference

High dimensional bayesian optimization using dropout

C Li, S gupta, S Rana, V Nguyen, S Venkatesh, A Shilton

(2017), pp. 2096-2102, IJCAI 2017 : Proceedings of the 26th International Joint Confrerence on Artificial Intelligence, Melbourne, Victoria, E1

conference
2016

Guidelines for developing and reporting machine learning predictive models in biomedical research : a multidisciplinary view

W Luo, Q Phung, T Tran, S Gupta, S Rana, C Karmakar, A Shilton, J Yearwood, N Dimitrova, T Ho, S Venkatesh, M Berk

(2016), Vol. 18, pp. 1-10, Journal of medical internet research, Toronto, Ont., C1

journal
2015

DP1SVM: a dynamic planar one-class support vector machine for Internet of Things environment

A Shilton, S Rajasegarar, C Leckie, M Palaniswami

(2015), pp. 1-6, RIoT 2015 : Proceedings of the 2015 International Conference on Recent Advances in Internet of Things, Singapore, Singapore, E1-1

conference
2013

Combined multiclass classification and anomaly detection for large-scale wireless sensor networks

A Shilton, S Rajasegarar, M Palaniswami

(2013), pp. 491-496, IEEE ISSNIP 2013 : Proceedings of the 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Melbourne, Vic., E1-1

conference

Autonomous detection of different walking tasks using end point foot trajectory vertical displacement data

B Santhiranayagam, D Lai, A Shilton, R Begg, M Palaniswami

(2013), pp. 509-514, IEEE ISSNIP 2013 : Proceedings of the 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Melbourne, Vic., E1-1

conference
2012

Automatic detection of different walking conditions using inertial sensor data

B Santhiranayagam, D Lai, C Jiang, A Shilton, R Begg

(2012), Proceedings of the International Joint Conference on Neural Networks, E1-1

conference

The conic-segmentation support vector machine - A target space method for multiclass classification

A Shilton, D Lai, M Palaniswami

(2012), Proceedings of the International Joint Conference on Neural Networks, E1-1

conference

A note on octonionic support vector regression

Alistair Shilton, Daniel Lai, Braveena Santhiranayagam, M Palaniswami

(2012), Vol. 42, pp. 950-955, IEEE transactions on systems, man and cybernetics - part B: cybernetics, Piscataway, N.J., C1-1

journal

Fast supersymmetry phenomenology at the Large Hadron Collider using machine learning techniques

A Buckley, A Shilton, M White

(2012), Vol. 183, pp. 960-970, Computer physics communications, Amsterdam, The Netherlands, C1-1

journal

The challenges of monitoring physical activity in children with wearable sensor technologies

G Pendhakar, D Lai, A Shilton, R Polman

(2012), pp. 221-246, Healthcare sensor networks: challenges toward practical implementation, Boca Raton, Fla., B1-1

chapter
2011

Regression models for estimating gait parameters using inertial sensors

B Santhiranayagam, D Lai, A Shilton, R Begg, M Palaniswami

(2011), pp. 46-51, Proceedings of the 2011 7th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2011, E1-1

conference
2010

On the feasibility of learning to predict minimum toe clearance under different walking speeds

Daniel Lai, A Shilton, R Begg

(2010), Vol. 2010, pp. 4890-4893, EMBC'10 : Merging medical humanism and technology : Proceedings of the 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, Buenos Aires, Argentina, E1-1

conference

A division algebraic framework for multidimensional support vector regression

A Shilton, D Lai, M Palaniswami

(2010), Vol. 40, pp. 517-528, IEEE transactions on systems, man, and cybernetics, part B: cybernetics, Piscataway, N.J., C1-1

journal
2009

A machine learning approach to k-step look-ahead prediction of gait variables from acceleration data

D Lai, D Lai, A Shilton, A Shilton, E Charry, E Charry, R Begg, R Begg, M Palaniswami, M Palaniswami

(2009), pp. 384-387, Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Minneapolis, Minnesota, C1-1

journal
2008

Kernel Methods in Protein Structure Prediction

J Gubbi, A Shilton, M Palaniswami

(2008), pp. 209-228, Machine Learning in Bioinformatics, B1-1

chapter
2007

Real value solvent accessibility prediction using adaptive support vector regression

J Gubbi, A Shilton, M Palaniswami, M Parker

(2007), pp. 395-401, 2007 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology, CIBCB 2007, E1-1

conference

Iterative fuzzy support vector machine classification

A Shilton, D Lai

(2007), IEEE International Conference on Fuzzy Systems, E1-1

conference

Quaternionic and complex-valued support vector regression for equalization and function approximation

A Shilton, D Lai

(2007), pp. 920-925, IEEE International Conference on Neural Networks - Conference Proceedings, E1-1

conference

Detecting selective forwarding attacks in wireless sensor networks using support vector machines

S Kaplantzis, A Shilton, N Mani, Y ?ekerci?lu

(2007), pp. 335-340, Proceedings of the 2007 International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP, E1-1

conference
2005

Incremental training of support vector machines

A Shilton, M Palaniswami, D Ralph, A Tsoi

(2005), Vol. 16, pp. 114-131, IEEE transactions on neural networks, Piscataway, N.J., C1-1

journal

A convergence rate estimate for the SVM decomposition method

D Lai, A Shilton, N Mani, M Palaniswami

(2005), Vol. 2, pp. 931-936, Proceedings of the International Joint Conference on Neural Networks, E1-1

conference
2002

Adaptive support vector machines for regression

M Palaniswami, A Shilton

(2002), Vol. 2, pp. 1043-1049, ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age, E1-1

conference

Distributed data fusion using support vector machines

S Challa, M Palaniswami, A Shilton

(2002), Vol. 2, pp. 881-885, Proceedings of the 5th International Conference on Information Fusion, FUSION 2002, E1-1

conference

Funded Projects at Deakin

No Funded Projects at Deakin found

Supervisions

No completed student supervisions to report