Alistair Shilton

43 papers A* 7A 4B 6C 1Journal 19Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Accelerated experimental design using a human-AI teaming framework. Knowl. Based Syst. Arun Kumar Anjanapura Venkatesh, Alistair Shilton, Sunil Gupta, Shannon Ryan, Majid Abdolshah, Hung Le, Santu Rana, Julian Berk, Mahad Rashid, Svetha Venkatesh
2024	—	`conf`	Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties. ECML/PKDD (6) A. V. Arun Kumar, Alistair Shilton, Sunil Gupta, Santu Rana, Stewart Greenhill, Svetha Venkatesh
2024	J	`jnl`	Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties. CoRR A. V. Arun Kumar, Alistair Shilton, Sunil Gupta, Santu Rana, Stewart Greenhill, Svetha Venkatesh
2024	J	`jnl`	Novel Kernel Models and Exact Representor Theory for Neural Networks Beyond the Over-Parameterized Regime. CoRR Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
2024	—	`conf`	PINN-BO: A Black-Box Optimization Algorithm Using Physics-Informed Neural Networks. ECML/PKDD (2) Dat Phan-Trong, Hung The Tran, Alistair Shilton, Sunil Gupta
2024	J	`jnl`	PINN-BO: A Black-box Optimization Algorithm using Physics-Informed Neural Networks. CoRR Dat Phan-Trong, Hung The Tran, Alistair Shilton, Sunil Gupta
2023	J	`jnl`	BO-Muse: A human expert and AI teaming framework for accelerated experimental design. CoRR Sunil Gupta, Alistair Shilton, Arun Kumar A. V., Shannon Ryan, Majid Abdolshah, Hung Le, Santu Rana, Julian Berk, Mahad Rashid, Svetha Venkatesh
2023	J	`jnl`	Gradient Descent in Neural Networks as Sequential Learning in RKBS. CoRR Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
2023	A*	`conf`	Gradient Descent in Neural Networks as Sequential Learning in Reproducing Kernel Banach Space. ICML Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
2022	A*	`conf`	Human-AI Collaborative Bayesian Optimisation. NeurIPS Arun Kumar A. V., Santu Rana, Alistair Shilton, Svetha Venkatesh
2022	A*	`conf`	TRF: Learning Kernels with Tuned Random Features. AAAI Alistair Shilton, Sunil Gupta, Santu Rana, Arun Kumar Anjanapura Venkatesh, Svetha Venkatesh
2021	J	`jnl`	Fairness improvement for black-box classifiers with Gaussian process. Inf. Sci. Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh
2021	A*	`conf`	Kernel Functional Optimisation. NeurIPS Arun Kumar Anjanapura Venkatesh, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
2020	A	`conf`	Accelerated Bayesian Optimisation through Weight-Prior Tuning. AISTATS 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
2020	A*	`conf`	Bayesian Optimization for Categorical and Category-Specific Continuous Inputs. AAAI Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh
2020	J	`jnl`	From deep to Shallow: Equivalent Forms of Deep Networks in Reproducing Kernel Krein Space and Indefinite Support Vector Machines. CoRR Alistair Shilton
2020	J	`jnl`	Multiclass Anomaly Detector: the CS++ Support Vector Machine. J. Mach. Learn. Res. Alistair Shilton, Sutharshan Rajasegarar, Marimuthu Palaniswami
2020	J	`jnl`	Sequential Subspace Search for Functional Bayesian Optimization Incorporating Experimenter Intuition. CoRR Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
2019	—	`conf`	Bayesian Optimisation for Objective Functions with Varying Smoothness. Australasian Conference on Artificial Intelligence A. V. Arun Kumar, Santu Rana, Cheng Li, Sunil Gupta, Alistair Shilton, Svetha Venkatesh
2019	J	`jnl`	Bayesian Optimization for Categorical and Category-Specific Continuous Inputs. CoRR Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh
2019	J	`jnl`	Cost-aware Multi-objective Bayesian optimisation. CoRR Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
2019	A*	`conf`	Multi-objective Bayesian optimisation with preferences over objectives. NeurIPS Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
2019	J	`jnl`	Multi-objective Bayesian optimisation with preferences over objectives. CoRR Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
2019	J	`jnl`	Stable Bayesian Optimisation via Direct Stability Quantification. CoRR Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh, Majid Abdolshah, Dang Nguyen
2018	B	`conf`	Expected Hypervolume Improvement with Constraints. ICPR Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
2018	A	`conf`	Exploiting Strategy-Space Diversity for Batch Bayesian Optimization. AISTATS Sunil Gupta, Alistair Shilton, Santu Rana, Svetha Venkatesh
2018	J	`jnl`	Kernel Pre-Training in Feature Space via m-Kernels. CoRR 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
2018	A	`conf`	Multi-Target Optimisation via Bayesian Optimisation and Linear Programming. UAI Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh
2017	A*	`conf`	High Dimensional Bayesian Optimization using Dropout. IJCAI Cheng Li, Sunil Gupta, Santu Rana, Vu Nguyen, Svetha Venkatesh, Alistair Shilton
2017	A	`conf`	Regret Bounds for Transfer Learning in Bayesian Optimisation. AISTATS Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh
2015	—	`conf`	DP1SVM: A dynamic planar one-class support vector machine for Internet of Things environment. RIoT Alistair Shilton, Sutharshan Rajasegarar, Christopher Leckie, Marimuthu Palaniswami
2013	—	`conf`	Autonomous detection of different walking tasks using end point foot trajectory vertical displacement data. ISSNIP Braveena K. Santhiranayagam, Daniel T. H. Lai, Alistair Shilton, Rezaul K. Begg, Marimuthu Palaniswami
2013	—	`conf`	Combined multiclass classification and anomaly detection for large-scale Wireless Sensor Networks. ISSNIP Alistair Shilton, Sutharshan Rajasegarar, Marimuthu Palaniswami
2012	J	`jnl`	A Note on Octonionic Support Vector Regression. IEEE Trans. Syst. Man Cybern. Part B Alistair Shilton, Daniel T. H. Lai, Braveena K. Santhiranayagam, Marimuthu Palaniswami
2012	B	`conf`	Automatic detection of different walking conditions using inertial sensor data. IJCNN Braveena K. Santhiranayagam, Daniel T. H. Lai, Cancan Jiang, Alistair Shilton, Rezaul K. Begg
2012	J	`jnl`	Fast supersymmetry phenomenology at the Large Hadron Collider using machine learning techniques. Comput. Phys. Commun. Andy Buckley, Alistair Shilton, M. J. White
2012	B	`conf`	The conic-segmentation support vector machine - a target space method for multiclass classification. IJCNN Alistair Shilton, Daniel T. H. Lai, Marimuthu Palaniswami
2010	J	`jnl`	A Division Algebraic Framework for Multidimensional Support Vector Regression. IEEE Trans. Syst. Man Cybern. Part B Alistair Shilton, Daniel T. H. Lai, Marimuthu Palaniswami
2007	B	`conf`	Iterative Fuzzy Support Vector Machine Classification. FUZZ-IEEE Alistair Shilton, Daniel T. H. Lai
2007	B	`conf`	Quaternionic and complex-valued Support Vector Regression for Equalization and Function Approximation. IJCNN Alistair Shilton, Daniel T. H. Lai
2007	C	`conf`	Real Value Solvent Accessibility Prediction using Adaptive Support Vector Regression. CIBCB Jayavardhana Gubbi, Alistair Shilton, Marimuthu Palaniswami, Michael Parker
2005	B	`conf`	A convergence rate estimate for the SVM decomposition method. IJCNN Daniel T. H. Lai, Alistair Shilton, Nallasamy Mani, Marimuthu Palaniswami
2005	J	`jnl`	Incremental training of support vector machines. IEEE Trans. Neural Networks Alistair Shilton, Marimuthu Palaniswami, Daniel Ralph, Ah Chung Tsoi