Steve R. Gunn - RankMe

74 papers A 6B 8C 3Journal 30Unranked 24

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Lurie Networks with Robust Convergent Dynamics. Trans. Mach. Learn. Res. Carl R. Richardson, Matthew C. Turner, Steve R. Gunn
2024	—	`conf`	Computational Resource Optimisation in Feature Selection under Class Imbalance Conditions. SciPy Amadi Gabriel Udu, Andrea Lecchini-Visintini, Steve R. Gunn, Norman Osa-uwagboe, Maryam Khaksar Ghalati, Hongbiao Dong
2024	—	`conf`	Strengthened stability analysis of discrete-time Lurie systems involving ReLU neural networks. L4DC Carl R. Richardson, Matthew C. Turner, Steve R. Gunn, Ross Drummond
2023	J	`jnl`	Errata on "Strengthened Circle and Popov Criteria for the Stability Analysis of Feedback Systems With ReLU Neural Networks". IEEE Control. Syst. Lett. Carl R. Richardson, Matthew C. Turner, Steve R. Gunn
2023	A	`conf`	Exploiting Epistemic Uncertainty at Inference Time for Early-Exit Power Saving. ECAI Jack Dymond, Sebastian Stein, Steve R. Gunn
2023	J	`jnl`	Strengthened Circle and Popov Criteria for the Stability Analysis of Feedback Systems With ReLU Neural Networks. IEEE Control. Syst. Lett. Carl R. Richardson, Matthew C. Turner, Steve R. Gunn
2022	A	`conf`	Adapting branched networks to realise progressive intelligence. BMVC Jack Dymond, Sebastian Stein, Steve R. Gunn
2021	—	`conf`	A Variance Controlled Stochastic Method with Biased Estimation for Faster Non-convex Optimization. ECML/PKDD (3) Jia Bi, Steve R. Gunn
2021	J	`jnl`	A Variance Controlled Stochastic Method with Biased Estimation for Faster Non-convex Optimization. CoRR Jia Bi, Steve R. Gunn
2020	C	`conf`	Product Lifecycle De-trending for Sales Forecasting. COMPLEXIS Albert F. H. M. Lechner, Steve R. Gunn
2020	J	`jnl`	Sparse Deep Neural Network Optimization for Embedded Intelligence. Int. J. Artif. Intell. Tools Jia Bi, Steve R. Gunn
2019	—	`conf`	A Stochastic Gradient Method with Biased Estimation for Faster Nonconvex Optimization. PRICAI (2) Jia Bi, Steve R. Gunn
2019	J	`jnl`	A Stochastic Gradient Method with Biased Estimation for Faster Nonconvex Optimization. CoRR Jia Bi, Steve R. Gunn
2018	—	`conf`	Lightweight PUF-Based Authentication Protocol for IoT Devices. IVSW Yildiran Yilmaz, Steve R. Gunn, Basel Halak
2018	B	`conf`	Sparse Deep Neural Networks for Embedded Intelligence. ICTAI Jia Bi, Steve R. Gunn
2017	J	`jnl`	Coarse-Grained Online Monitoring of BTI Aging by Reusing Power-Gating Infrastructure. IEEE Trans. Very Large Scale Integr. Syst. Vasileios Tenentes, Daniele Rossi, Sheng Yang, S. Saqib Khursheed, Bashir M. Al-Hashimi, Steve R. Gunn
2013	—	`conf`	Towards Pareto Descent Directions in Sampling Experts for Multiple Tasks in an On-Line Learning Paradigm. AAAI Spring Symposium: Lifelong Machine Learning Shaona Ghosh, Chris Lovell, Steve R. Gunn
2012	B	`conf`	Enabling the discovery of computational characteristics of enzyme dynamics. IEEE Congress on Evolutionary Computation Gareth L. Jones, Chris Lovell, Steve R. Gunn, Hywel Morgan, Klaus-Peter Zauner
2012	—	`conf`	Exploration and Exploitation with Insufficient Resources. ICML On-line Trading of Exploration and Exploitation Chris Lovell, Gareth L. Jones, Klaus-Peter Zauner, Steve R. Gunn
2012	B	`conf`	Towards improved theoretical problems for autonomous discovery. IJCNN Chris Lovell, Steve R. Gunn
2011	—	`conf`	Autonomous Experimentation. Active Learning and Experimental Design @ AISTATS Chris Lovell, Gareth L. Jones, Steve R. Gunn, Klaus-Peter Zauner
2011	—	`conf`	Scale Space Smoothing, Image Feature Extraction and Bessel Filters. SCIA Sasan Mahmoodi, Steve R. Gunn
2011	B	`conf`	Snake based unsupervised texture segmentation using Gaussian Markov Random Field Models. ICIP Sasan Mahmoodi, Steve R. Gunn
2010	B	`conf`	An Artificial Experimenter for Enzymatic Response Characterisation. Discovery Science Chris Lovell, Gareth L. Jones, Steve R. Gunn, Klaus-Peter Zauner
2010	C	`conf`	Characterising Enzymes for Information Processing: Towards an Artificial Experimenter. UC Chris Lovell, Gareth L. Jones, Steve R. Gunn, Klaus-Peter Zauner
2010	—	`conf`	Maximum Margin Learning with Incomplete Data: Learning Networks instead of Tables. WAPA Sándor Szedmák, Yizhao Ni, Steve R. Gunn
2009	J	`jnl`	A signal theory approach to support vector classification: The sinc kernel. Neural Networks James D. B. Nelson, Robert I. Damper, Steve R. Gunn, Baofeng Guo
2009	J	`jnl`	Efficient Sparse Kernel Feature Extraction Based on Partial Least Squares. IEEE Trans. Pattern Anal. Mach. Intell. Charanpal Dhanjal, Steve R. Gunn, John Shawe-Taylor
2009	—	`conf`	Hardware efficient fixed-point VLSI architecture for 2D Kurtotic FastICA. ECCTD Amit Acharyya, Koushik Maharatna, Jinhong Sun, Bashir M. Al-Hashimi, Steve R. Gunn
2009	—	`conf`	Learning to rank images from eye movements. ICCV Workshops Kitsuchart Pasupa, Craig Saunders, Sándor Szedmák, Arto Klami, Samuel Kaski, Steve R. Gunn
2009	J	`jnl`	Memory Reduction Methodology for Distributed-Arithmetic-Based DWT/IDWT Exploiting Data Symmetry. IEEE Trans. Circuits Syst. II Express Briefs Amit Acharyya, Koushik Maharatna, Bashir M. Al-Hashimi, Steve R. Gunn
2008	J	`jnl`	A fast separability-based feature-selection method for high-dimensional remotely sensed image classification. Pattern Recognit. Baofeng Guo, Robert I. Damper, Steve R. Gunn, James D. B. Nelson
2008	J	`jnl`	Customizing Kernel Functions for SVM-Based Hyperspectral Image Classification. IEEE Trans. Image Process. Baofeng Guo, Steve R. Gunn, Robert I. Damper, James D. B. Nelson
2008	J	`jnl`	Signal theory for SVM kernel design with applications to parameter estimation and sequence kernels. Neurocomputing James D. B. Nelson, Robert I. Damper, Steve R. Gunn, Baofeng Guo
2007	—	`conf`	Exploiting Uncertain Data in Support Vector Classification. KES (3) Jianqiang Yang, Steve R. Gunn
2006	J	`jnl`	Band Selection for Hyperspectral Image Classification Using Mutual Information. IEEE Geosci. Remote. Sens. Lett. Baofeng Guo, Steve R. Gunn, Robert I. Damper, James D. B. Nelson
2006	—	`ch.`	Design and Analysis of the NIPS2003 Challenge. Feature Extraction Isabelle Guyon, Steve R. Gunn, Asa Ben-Hur, Gideon Dror
2006	—	`book`	Feature Extraction - Foundations and Applications Feature Extraction Isabelle Guyon, Masoud Nikravesh, Steve R. Gunn, Lotfi A. Zadeh
2006	—	`ed.`	Subspace, Latent Structure and Feature Selection, Statistical and Optimization, Perspectives Workshop, SLSFS 2005, Bohinj, Slovenia, February 23-25, 2005, Revised Selected Papers SLSFS Craig Saunders, Marko Grobelnik, Steve R. Gunn, John Shawe-Taylor
2005	—	`conf`	Identifying Feature Relevance Using a Random Forest. SLSFS Jeremy Rogers, Steve R. Gunn
2004	—	`conf`	Classifiers Combination for Improved Motion Segmentation. ICIAR (2) Ahmad Al-Mazeed, Mark S. Nixon, Steve R. Gunn
2004	—	`conf`	Ensemble Algorithms for Feature Selection. Deterministic and Statistical Methods in Machine Learning Jeremy Rogers, Steve R. Gunn
2004	—	`conf`	Result Analysis of the NIPS 2003 Feature Selection Challenge. NIPS Isabelle Guyon, Steve R. Gunn, Asa Ben-Hur, Gideon Dror
2003	J	`jnl`	An Approach to Off-Line Handwritten Chinese Character Recognition Based on Hierarchical Radical Decomposition. J. Quant. Linguistics Daming Shi, Robert I. Damper, Steve R. Gunn
2003	A	`conf`	Fusing Complementary Operators to Enhance Foreground/Background Segmentation. BMVC Ahmad Al-Mazeed, Mark S. Nixon, Steve R. Gunn
2003	J	`jnl`	Handwritten Chinese Radical Recognition Using Nonlinear Active Shape Models. IEEE Trans. Pattern Anal. Mach. Intell. Daming Shi, Steve R. Gunn, Robert I. Damper
2003	J	`jnl`	Mean field method for the support vector machine regression. Neurocomputing Junbin Gao, Steve R. Gunn, Chris J. Harris
2003	A	`conf`	Nonlinear Active Handwriting Models and Their Applications to Handwritten Chinese Radical Recognition. ICDAR Geok See Ng, Daming Shi, Steve R. Gunn, Robert I. Damper
2003	J	`jnl`	Offline handwritten Chinese character recognition by radical decomposition. ACM Trans. Asian Lang. Inf. Process. Daming Shi, Robert I. Damper, Steve R. Gunn
2003	J	`jnl`	SVM regression through variational methods and its sequential implementation. Neurocomputing Junbin Gao, Steve R. Gunn, Chris J. Harris
2002	J	`jnl`	A Probabilistic Framework for SVM Regression and Error Bar Estimation. Mach. Learn. Junbin Gao, Steve R. Gunn, Chris J. Harris, Martin Brown
2002	—	`conf`	Adapting Kernels by Variational Approach in SVM. Australian Joint Conference on Artificial Intelligence Junbin Gao, Steve R. Gunn, Jaz S. Kandola
2002	J	`jnl`	Errata to "The relevance vector machine technique for channel equalization application". IEEE Trans. Neural Networks Sheng Chen, Steve R. Gunn, Chris J. Harris
2002	J	`jnl`	Handwritten Chinese character recognition using nonlinear active shape models and the Viterbi algorithm. Pattern Recognit. Lett. Daming Shi, Steve R. Gunn, Robert I. Damper
2002	J	`jnl`	Structural Modelling with Sparse Kernels. Mach. Learn. Steve R. Gunn, Jaz S. Kandola
2001	—	`conf`	A Radical Approach to Handwritten Chinese Character Recognition Using Active Handwriting Models. CVPR (1) Daming Shi, Steve R. Gunn, Robert I. Damper
2001	A	`conf`	Active Radical Modeling for Handwritten Chinese Characters. ICDAR Daming Shi, Steve R. Gunn, Robert I. Damper
2001	—	`conf`	Markov Random Field Models for Segmentation of PET Images. IPMI Jun L. Chen, Steve R. Gunn, Mark S. Nixon, Roger N. Gunn
2001	J	`jnl`	On a Class of Support Vector Kernels Based on Frames in Function Hilbert Spaces. Neural Comput. Junbin Gao, Chris J. Harris, Steve R. Gunn
2001	B	`conf`	Texture analysis with the Volterra model using conjugate gradient optimisation. ESANN Adam I. Wilmer, Tania Stathaki, Steve R. Gunn, Robert I. Damper
2001	J	`jnl`	The relevance vector machine technique for channel equalization application. IEEE Trans. Neural Networks Sheng Chen, Steve R. Gunn, Chris J. Harris
2000	J	`jnl`	Extracting Phonetic Knowledge from Learning Systems: Perceptrons, Support Vector Machines and Linear Discriminants. Appl. Intell. Robert I. Damper, Steve R. Gunn, Mathew O. Gore
2000	J	`jnl`	Linear spectral mixture models and support vector machines for remote sensing. IEEE Trans. Geosci. Remote. Sens. Martin Brown, Hugh G. Lewis, Steve R. Gunn
1999	—	`conf`	Learning phonetic distinctions from speech signals. EUROSPEECH Robert I. Damper, Steve R. Gunn
1999	J	`jnl`	On the discrete representation of the Laplacian of Gaussian. Pattern Recognit. Steve R. Gunn
1998	—	`conf`	Edge Detection Error in the Discrete Laplacian of Gaussian. ICIP (2) Steve R. Gunn
1998	J	`jnl`	Global and Local Active Contours for Head Boundary Extraction. Int. J. Comput. Vis. Steve R. Gunn, Mark S. Nixon
1998	—	`conf`	On the learnability of the voicing contrast for initial stops. ICSLP Robert I. Damper, Steve R. Gunn
1997	J	`jnl`	A Robust Snake Implementation; A Dual Active Contour. IEEE Trans. Pattern Anal. Mach. Intell. Steve R. Gunn, Mark S. Nixon
1997	B	`conf`	Network Performance Assessment for Neurofuzzy Data Modelling. IDA Steve R. Gunn, Martin Brown, Kev M. Bossley
1997	—	`conf`	Using MRI to image the moving vocal tract during speech. EUROSPEECH Moshrefi Mohammad, E. Moore, John N. Carter, Christine H. Shadle, Steve R. Gunn
1996	B	`conf`	Snake head boundary extraction using global and local energy minimisation. ICPR Steve R. Gunn, Mark S. Nixon
1995	C	`conf`	Improving snake performance via a dual active contour. CAIP Steve R. Gunn, Mark S. Nixon
1994	A	`conf`	A Model Based Dual Active Contour. BMVC Steve R. Gunn, Mark S. Nixon