Alistair Shilton

According to our database, Alistair Shilton authored at least 35 papers between 2005 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties.

A. V. Arun Kumar, Alistair Shilton, Sunil Gupta, Santu Rana, Stewart Greenhill, Svetha Venkatesh

CoRR, 2024

PINN-BO: A Black-box Optimization Algorithm using Physics-Informed Neural Networks.

Dat Phan-Trong, Hung The Tran, Alistair Shilton, Sunil Gupta

CoRR, 2024

2023

BO-Muse: A human expert and AI teaming framework for accelerated experimental design.

Sunil Gupta, Alistair Shilton, Arun Kumar A. V., Shannon Ryan, Majid Abdolshah, Hung Le, Santu Rana, Julian Berk, Mahad Rashid, Svetha Venkatesh

CoRR, 2023

Gradient Descent in Neural Networks as Sequential Learning in RKBS.

Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh

CoRR, 2023

Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space.

Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh

Proceedings of the International Conference on Machine Learning, 2023

2022

Human-AI Collaborative Bayesian Optimisation.

Arun Kumar A. V., Santu Rana, Alistair Shilton, Svetha Venkatesh

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

TRF: Learning Kernels with Tuned Random Features.

Alistair Shilton, Sunil Gupta, Santu Rana, Arun Kumar Anjanapura Venkatesh, Svetha Venkatesh

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Fairness improvement for black-box classifiers with Gaussian process.

Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh

Inf. Sci., 2021

Kernel Functional Optimisation.

Arun Kumar Anjanapura Venkatesh, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Multiclass Anomaly Detector: the CS++ Support Vector Machine.

Alistair Shilton, Sutharshan Rajasegarar, Marimuthu Palaniswami

J. Mach. Learn. Res., 2020

Sequential Subspace Search for Functional Bayesian Optimization Incorporating Experimenter Intuition.

Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh

CoRR, 2020

From deep to Shallow: Equivalent Forms of Deep Networks in Reproducing Kernel Krein Space and Indefinite Support Vector Machines.

Alistair Shilton

CoRR, 2020

Accelerated Bayesian Optimisation through Weight-Prior Tuning.

Alistair Shilton, Sunil Gupta, Santu Rana, Pratibha Vellanki, Cheng Li, Svetha Venkatesh, Laurence Park, Alessandra Sutti, David Rubin, Thomas Dorin, Alireza Vahid, Murray Height, Teo Slezak

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Bayesian Optimization for Categorical and Category-Specific Continuous Inputs.

Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Cost-aware Multi-objective Bayesian optimisation.

Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh

CoRR, 2019

Stable Bayesian Optimisation via Direct Stability Quantification.

Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh, Majid Abdolshah, Dang Nguyen

CoRR, 2019

Multi-objective Bayesian optimisation with preferences over objectives.

Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Bayesian Optimisation for Objective Functions with Varying Smoothness.

A. V. Arun Kumar, Santu Rana, Cheng Li, Sunil Gupta, Alistair Shilton, Svetha Venkatesh

Proceedings of the AI 2019: Advances in Artificial Intelligence, 2019

2018

Kernel Pre-Training in Feature Space via m-Kernels.

Alistair Shilton, Sunil Gupta, Santu Rana, Pratibha Vellanki, Cheng Li, Svetha Venkatesh, Laurence Park, Alessandra Sutti, David Rubin, Thomas Dorin, Alireza Vahid, Murray Height, Teo Slezak

CoRR, 2018

Multi-Target Optimisation via Bayesian Optimisation and Linear Programming.

Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Expected Hypervolume Improvement with Constraints.

Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh

Proceedings of the 24th International Conference on Pattern Recognition, 2018

Exploiting Strategy-Space Diversity for Batch Bayesian Optimization.

Sunil Gupta, Alistair Shilton, Santu Rana, Svetha Venkatesh

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

High Dimensional Bayesian Optimization using Dropout.

Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, Alistair Shilton

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Regret Bounds for Transfer Learning in Bayesian Optimisation.

Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2015

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

Alistair Shilton, Sutharshan Rajasegarar, Christopher Leckie, Marimuthu Palaniswami

Proceedings of the International Conference on Recent Advances in Internet of Things, 2015

2013

Combined multiclass classification and anomaly detection for large-scale Wireless Sensor Networks.

Alistair Shilton, Sutharshan Rajasegarar, Marimuthu Palaniswami

Proceedings of the 2013 IEEE Eighth International Conference on Intelligent Sensors, 2013

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

Braveena K. Santhiranayagam, Daniel T. H. Lai, Alistair Shilton, Rezaul K. Begg, Marimuthu Palaniswami

Proceedings of the 2013 IEEE Eighth International Conference on Intelligent Sensors, 2013

2012

A Note on Octonionic Support Vector Regression.

Alistair Shilton, Daniel T. H. Lai, Braveena K. Santhiranayagam, Marimuthu Palaniswami

IEEE Trans. Syst. Man Cybern. Part B, 2012

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

Alistair Shilton, Daniel T. H. Lai, Marimuthu Palaniswami

Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Automatic detection of different walking conditions using inertial sensor data.

Braveena K. Santhiranayagam, Daniel T. H. Lai, Cancan Jiang, Alistair Shilton, Rezaul K. Begg

Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

2010

A Division Algebraic Framework for Multidimensional Support Vector Regression.

Alistair Shilton, Daniel T. H. Lai, Marimuthu Palaniswami

IEEE Trans. Syst. Man Cybern. Part B, 2010

2007

Quaternionic and complex-valued Support Vector Regression for Equalization and Function Approximation.

Alistair Shilton, Daniel T. H. Lai

Proceedings of the International Joint Conference on Neural Networks, 2007

Iterative Fuzzy Support Vector Machine Classification.

Alistair Shilton, Daniel T. H. Lai

Proceedings of the FUZZ-IEEE 2007, 2007

Real Value Solvent Accessibility Prediction using Adaptive Support Vector Regression.

Jayavardhana Gubbi, Alistair Shilton, Marimuthu Palaniswami, Michael Parker

Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2007

2005

Incremental training of support vector machines.

Alistair Shilton, Marimuthu Palaniswami, Daniel Ralph, Ah Chung Tsoi

IEEE Trans. Neural Networks, 2005