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ORCIDAlistair Shilton
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2020 – today
- 2024
[c23]A. V. Arun Kumar, Alistair Shilton, Sunil Gupta, Santu Rana, Stewart Greenhill, Svetha Venkatesh:
Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties. ECML/PKDD (6) 2024: 234-250- [c22]Dat Phan-Trong
, Hung The Tran, Alistair Shilton, Sunil Gupta:
PINN-BO: A Black-Box Optimization Algorithm Using Physics-Informed Neural Networks. ECML/PKDD (2) 2024: 357-374 - [i12]Dat Phan-Trong, Hung The Tran, Alistair Shilton, Sunil Gupta:
PINN-BO: A Black-box Optimization Algorithm using Physics-Informed Neural Networks. CoRR abs/2402.03243 (2024) - [i11]A. V. Arun Kumar, Alistair Shilton, Sunil Gupta, Santu Rana, Stewart Greenhill, Svetha Venkatesh:
Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties. CoRR abs/2402.17343 (2024) - [i10]Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Novel Kernel Models and Exact Representor Theory for Neural Networks Beyond the Over-Parameterized Regime. CoRR abs/2405.15254 (2024) - 2023
- [c21]Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space. ICML 2023: 31435-31488 - [i9]Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Gradient Descent in Neural Networks as Sequential Learning in RKBS. CoRR abs/2302.00205 (2023) - [i8]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 abs/2303.01684 (2023) - 2022
- [c20]Alistair Shilton, Sunil Gupta, Santu Rana, Arun Kumar Anjanapura Venkatesh, Svetha Venkatesh:
TRF: Learning Kernels with Tuned Random Features. AAAI 2022: 8286-8294 - [c19]Arun Kumar A. V., Santu Rana, Alistair Shilton, Svetha Venkatesh:
Human-AI Collaborative Bayesian Optimisation. NeurIPS 2022 - 2021
- [j5]Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh:
Fairness improvement for black-box classifiers with Gaussian process. Inf. Sci. 576: 542-556 (2021) - [c18]Arun Kumar Anjanapura Venkatesh, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Kernel Functional Optimisation. NeurIPS 2021: 4725-4737 - 2020
- [j4]Alistair Shilton, Sutharshan Rajasegarar, Marimuthu Palaniswami:
Multiclass Anomaly Detector: the CS++ Support Vector Machine. J. Mach. Learn. Res. 21: 213:1-213:39 (2020) - [c17]Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh:
Bayesian Optimization for Categorical and Category-Specific Continuous Inputs. AAAI 2020: 5256-5263 - [c16]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: 635-645 - [i7]Alistair Shilton:
From deep to Shallow: Equivalent Forms of Deep Networks in Reproducing Kernel Krein Space and Indefinite Support Vector Machines. CoRR abs/2007.07459 (2020) - [i6]Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Sequential Subspace Search for Functional Bayesian Optimization Incorporating Experimenter Intuition. CoRR abs/2009.03543 (2020)
2010 – 2019
- 2019
- [c15]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: 460-472 - [c14]Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Multi-objective Bayesian optimisation with preferences over objectives. NeurIPS 2019: 12214-12224 - [i5]Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Multi-objective Bayesian optimisation with preferences over objectives. CoRR abs/1902.04228 (2019) - [i4]Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh, Majid Abdolshah, Dang Nguyen:
Stable Bayesian Optimisation via Direct Stability Quantification. CoRR abs/1902.07846 (2019) - [i3]Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Cost-aware Multi-objective Bayesian optimisation. CoRR abs/1909.03600 (2019) - [i2]Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh:
Bayesian Optimization for Categorical and Category-Specific Continuous Inputs. CoRR abs/1911.12473 (2019) - 2018
- [c13]Sunil Gupta, Alistair Shilton, Santu Rana, Svetha Venkatesh:
Exploiting Strategy-Space Diversity for Batch Bayesian Optimization. AISTATS 2018: 538-547 - [c12]Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Expected Hypervolume Improvement with Constraints. ICPR 2018: 3238-3243 - [c11]Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Multi-Target Optimisation via Bayesian Optimisation and Linear Programming. UAI 2018: 145-155 - [i1]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 abs/1805.07852 (2018) - 2017
- [c10]Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Regret Bounds for Transfer Learning in Bayesian Optimisation. AISTATS 2017: 307-315 - [c9]Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, Alistair Shilton:
High Dimensional Bayesian Optimization using Dropout. IJCAI 2017: 2096-2102 - 2015
- [c8]Alistair Shilton, Sutharshan Rajasegarar, Christopher Leckie, Marimuthu Palaniswami:
DP1SVM: A dynamic planar one-class support vector machine for Internet of Things environment. RIoT 2015: 1-6 - 2013
- [c7]Alistair Shilton, Sutharshan Rajasegarar, Marimuthu Palaniswami:
Combined multiclass classification and anomaly detection for large-scale Wireless Sensor Networks. ISSNIP 2013: 491-496 - [c6]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: 509-514 - 2012
- [j3]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): 950-955 (2012) - [c5]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: 1-6 - [c4]Alistair Shilton, Daniel T. H. Lai, Marimuthu Palaniswami:
The conic-segmentation support vector machine - a target space method for multiclass classification. IJCNN 2012: 1-8 - 2010
- [j2]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): 517-528 (2010)
2000 – 2009
- 2007
- [c3]Jayavardhana Gubbi, Alistair Shilton, Marimuthu Palaniswami, Michael Parker:
Real Value Solvent Accessibility Prediction using Adaptive Support Vector Regression. CIBCB 2007: 395-401 - [c2]Alistair Shilton, Daniel T. H. Lai:
Iterative Fuzzy Support Vector Machine Classification. FUZZ-IEEE 2007: 1-6 - [c1]Alistair Shilton, Daniel T. H. Lai:
Quaternionic and complex-valued Support Vector Regression for Equalization and Function Approximation. IJCNN 2007: 920-925 - 2005
- [j1]Alistair Shilton, Marimuthu Palaniswami, Daniel Ralph, Ah Chung Tsoi:
Incremental training of support vector machines. IEEE Trans. Neural Networks 16(1): 114-131 (2005)
Coauthor Index
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