Alistair Shilton

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 27

Top Topics

Bayesian Learning

Reproducing Kernel

Top Venues

Publications

A. V. Arun Kumar, Alistair Shilton, Sunil Gupta, Santu Rana, Stewart Greenhill, Svetha Venkatesh
Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties. CoRR (2024)
Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
Novel Kernel Models and Exact Representor Theory for Neural Networks Beyond the Over-Parameterized Regime. CoRR (2024)
Dat Phan-Trong, Hung The Tran, Alistair Shilton, Sunil Gupta
PINN-BO: A Black-box Optimization Algorithm using Physics-Informed Neural Networks. CoRR (2024)
Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space. ICML (2023)
Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
Gradient Descent in Neural Networks as Sequential Learning in RKBS. CoRR (2023)
Sunil Gupta, Alistair Shilton, Arun Kumar A V, Shannon Ryan, Majid Abdolshah, Hung Le, Santu Rana, Julian Berk, Mahad Rashid, Svetha Venkatesh
BO-Muse: A human expert and AI teaming framework for accelerated experimental design. CoRR (2023)
Alistair Shilton, Sunil Gupta, Santu Rana, Arun Kumar Anjanapura Venkatesh, Svetha Venkatesh
TRF: Learning Kernels with Tuned Random Features. AAAI (2022)
Arun Kumar A V, Santu Rana, Alistair Shilton, Svetha Venkatesh
Human-AI Collaborative Bayesian Optimisation. NeurIPS (2022)
Arun Kumar Anjanapura Venkatesh, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
Kernel Functional Optimisation. NeurIPS (2021)
Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh
Fairness improvement for black-box classifiers with Gaussian process. Inf. Sci. 576 (2021)
Alistair Shilton
From deep to Shallow: Equivalent Forms of Deep Networks in Reproducing Kernel Krein Space and Indefinite Support Vector Machines. CoRR (2020)
Alistair Shilton, Sutharshan Rajasegarar, Marimuthu Palaniswami
Multiclass Anomaly Detector: the CS++ Support Vector Machine. J. Mach. Learn. Res. 21 (2020)
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
Accelerated Bayesian Optimisation through Weight-Prior Tuning. AISTATS (2020)
Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
Sequential Subspace Search for Functional Bayesian Optimization Incorporating Experimenter Intuition. CoRR (2020)
Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh
Bayesian Optimization for Categorical and Category-Specific Continuous Inputs. AAAI (2020)
Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
Cost-aware Multi-objective Bayesian optimisation. CoRR (2019)
Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
Multi-objective Bayesian optimisation with preferences over objectives. CoRR (2019)
Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
Multi-objective Bayesian optimisation with preferences over objectives. NeurIPS (2019)
Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh
Bayesian Optimization for Categorical and Category-Specific Continuous Inputs. CoRR (2019)
A. V. Arun Kumar, Santu Rana, Cheng Li, Sunil Gupta, Alistair Shilton, Svetha Venkatesh
Bayesian Optimisation for Objective Functions with Varying Smoothness. Australasian Conference on Artificial Intelligence (2019)
Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh, Majid Abdolshah, Dang Nguyen
Stable Bayesian Optimisation via Direct Stability Quantification. CoRR (2019)
Sunil Gupta, Alistair Shilton, Santu Rana, Svetha Venkatesh
Exploiting Strategy-Space Diversity for Batch Bayesian Optimization. AISTATS (2018)
Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
Expected Hypervolume Improvement with Constraints. ICPR (2018)
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
Kernel Pre-Training in Feature Space via m-Kernels. CoRR (2018)
Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
Multi-Target Optimisation via Bayesian Optimisation and Linear Programming. UAI (2018)
Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
Regret Bounds for Transfer Learning in Bayesian Optimisation. AISTATS (2017)
Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, Alistair Shilton
High Dimensional Bayesian Optimization using Dropout. IJCAI (2017)
Alistair Shilton, Sutharshan Rajasegarar, Christopher Leckie, Marimuthu Palaniswami
DP1SVM: A dynamic planar one-class support vector machine for Internet of Things environment. RIoT (2015)
Alistair Shilton, Sutharshan Rajasegarar, Marimuthu Palaniswami
Combined multiclass classification and anomaly detection for large-scale Wireless Sensor Networks. ISSNIP (2013)
Braveena K. Santhiranayagam, Daniel T. H. Lai, Alistair Shilton, Rezaul K. Begg, Marimuthu Palaniswami
Autonomous detection of different walking tasks using end point foot trajectory vertical displacement data. ISSNIP (2013)
Alistair Shilton, Daniel T. H. Lai, Marimuthu Palaniswami
The conic-segmentation support vector machine - a target space method for multiclass classification. IJCNN (2012)
Braveena K. Santhiranayagam, Daniel T. H. Lai, Cancan Jiang, Alistair Shilton, Rezaul K. Begg
Automatic detection of different walking conditions using inertial sensor data. IJCNN (2012)
Alistair Shilton, Daniel T. H. Lai, Braveena K. Santhiranayagam, Marimuthu Palaniswami
A Note on Octonionic Support Vector Regression. IEEE Trans. Syst. Man Cybern. Part B 42 (3) (2012)
Alistair Shilton, Daniel T. H. Lai, Marimuthu Palaniswami
A Division Algebraic Framework for Multidimensional Support Vector Regression. IEEE Trans. Syst. Man Cybern. Part B 40 (2) (2010)
Jayavardhana Gubbi, Alistair Shilton, Marimuthu Palaniswami, Michael Parker
Real Value Solvent Accessibility Prediction using Adaptive Support Vector Regression. CIBCB (2007)
Alistair Shilton, Daniel T. H. Lai
Iterative Fuzzy Support Vector Machine Classification. FUZZ-IEEE (2007)
Alistair Shilton, Daniel T. H. Lai
Quaternionic and complex-valued Support Vector Regression for Equalization and Function Approximation. IJCNN (2007)
Alistair Shilton, Marimuthu Palaniswami, Daniel Ralph, Ah Chung Tsoi
Incremental training of support vector machines. IEEE Trans. Neural Networks 16 (1) (2005)