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Henry Gouk
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2020 – today
- 2023
- [c24]Ondrej Bohdal, Yinbing Tian, Yongshuo Zong, Ruchika Chavhan, Da Li, Henry Gouk, Li Guo, Timothy M. Hospedales:
Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn. CVPR 2023: 7693-7703 - [c23]Fady Rezk, Antreas Antoniou, Henry Gouk, Timothy M. Hospedales:
Is Scaling Learned Optimizers Worth It? Evaluating The Value of VeLO's 4000 TPU Months. ICBINB 2023: 65-83 - [c22]Ruchika Chavhan, Henry Gouk, Da Li, Timothy M. Hospedales:
Quality Diversity for Visual Pre-Training. ICCV 2023: 5361-5371 - [c21]Vithya Yogarajan, Gillian Dobbie, Henry Gouk:
Effectiveness of Debiasing Techniques: An Indigenous Qualitative Analysis. Tiny Papers @ ICLR 2023 - [i26]Ruchika Chavhan, Henry Gouk, Jan Stuehmer, Calum Heggan, Mehrdad Yaghoobi, Timothy M. Hospedales:
Amortised Invariance Learning for Contrastive Self-Supervision. CoRR abs/2302.12712 (2023) - [i25]Vithya Yogarajan, Gillian Dobbie, Henry Gouk:
Effectiveness of Debiasing Techniques: An Indigenous Qualitative Analysis. CoRR abs/2304.11094 (2023) - [i24]Ondrej Bohdal, Yinbing Tian, Yongshuo Zong, Ruchika Chavhan, Da Li, Henry Gouk, Li Guo, Timothy M. Hospedales:
Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn. CoRR abs/2305.07625 (2023) - [i23]Luísa Shimabucoro, Timothy M. Hospedales, Henry Gouk:
Evaluating the Evaluators: Are Current Few-Shot Learning Benchmarks Fit for Purpose? CoRR abs/2307.02732 (2023) - [i22]Fady Rezk, Antreas Antoniou, Henry Gouk, Timothy M. Hospedales:
Is Scaling Learned Optimizers Worth It? Evaluating The Value of VeLO's 4000 TPU Months. CoRR abs/2310.18191 (2023) - 2022
- [j2]Linus Ericsson, Henry Gouk, Chen Change Loy, Timothy M. Hospedales:
Self-Supervised Representation Learning: Introduction, advances, and challenges. IEEE Signal Process. Mag. 39(3): 42-62 (2022) - [c20]Linus Ericsson, Henry Gouk, Timothy M. Hospedales:
Why Do Self-Supervised Models Transfer? On the Impact of Invariance on Downstream Tasks. BMVC 2022: 509 - [c19]Pavel Brazdil, Jan N. van Rijn, Henry Gouk, Felix Mohr:
Advances in Metalearning: ECML/PKDD Workshop on Meta-Knowledge Transfer. Meta-Knowledge Transfer @ ECML/PKDD 2022: 1-7 - [c18]Hongyu Wang, Huon Fraser, Henry Gouk, Eibe Frank, Bernhard Pfahringer, Michael Mayo, Geoff Holmes:
Experiments in Cross-domain Few-shot Learning for Image Classification: Extended Abstract. Meta-Knowledge Transfer @ ECML/PKDD 2022: 81-83 - [c17]Boyan Gao, Henry Gouk, Yongxin Yang, Timothy M. Hospedales:
Loss Function Learning for Domain Generalization by Implicit Gradient. ICML 2022: 7002-7016 - [e1]Pavel Brazdil, Jan N. van Rijn, Henry Gouk, Felix Mohr:
ECML/PKDD Workshop on Meta-Knowledge Transfer, 23 September 2022, Grenoble, France. Proceedings of Machine Learning Research 191, PMLR 2022 [contents] - [i21]Da Li, Henry Gouk, Timothy M. Hospedales:
Finding lost DG: Explaining domain generalization via model complexity. CoRR abs/2202.00563 (2022) - [i20]Boyan Gao, Henry Gouk, Haebeom Lee, Timothy M. Hospedales:
Meta Mirror Descent: Optimiser Learning for Fast Convergence. CoRR abs/2203.02711 (2022) - [i19]Adrian El Baz, André C. P. L. F. de Carvalho, Hong Chen, Fabio Ferreira, Henry Gouk, Shell Hu, Frank Hutter, Zhengying Liu, Felix Mohr, Jan N. van Rijn, Xin Wang, Isabelle Guyon:
Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification. CoRR abs/2206.08138 (2022) - [i18]Ruchika Chavhan, Henry Gouk, Jan Stühmer, Timothy M. Hospedales:
HyperInvariances: Amortizing Invariance Learning. CoRR abs/2207.08304 (2022) - [i17]Panagiotis Eustratiadis, Henry Gouk, Da Li, Timothy M. Hospedales:
Attacking Adversarial Defences by Smoothing the Loss Landscape. CoRR abs/2208.00862 (2022) - 2021
- [j1]Henry Gouk, Eibe Frank, Bernhard Pfahringer, Michael J. Cree:
Regularisation of neural networks by enforcing Lipschitz continuity. Mach. Learn. 110(2): 393-416 (2021) - [c16]Linus Ericsson, Henry Gouk, Timothy M. Hospedales:
How Well Do Self-Supervised Models Transfer? CVPR 2021: 5414-5423 - [c15]Xueting Zhang, Debin Meng, Henry Gouk, Timothy M. Hospedales:
Shallow Bayesian Meta Learning for Real-World Few-Shot Recognition. ICCV 2021: 631-640 - [c14]Boyan Gao, Henry Gouk, Timothy M. Hospedales:
Searching for Robustness: Loss Learning for Noisy Classification Tasks. ICCV 2021: 6650-6659 - [c13]Henry Gouk, Timothy M. Hospedales, Massimiliano Pontil:
Distance-Based Regularisation of Deep Networks for Fine-Tuning. ICLR 2021 - [c12]Panagiotis Eustratiadis, Henry Gouk, Da Li, Timothy M. Hospedales:
Weight-covariance alignment for adversarially robust neural networks. ICML 2021: 3047-3056 - [c11]Adrian El Baz, Ihsan Ullah, Edesio Alcobaça, André C. P. L. F. de Carvalho, Hong Chen, Fabio Ferreira, Henry Gouk, Chaoyu Guan, Isabelle Guyon, Timothy M. Hospedales, Shell Hu, Mike Huisman, Frank Hutter, Zhengying Liu, Felix Mohr, Ekrem Öztürk, Jan N. van Rijn, Haozhe Sun, Xin Wang, Wenwu Zhu:
Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification. NeurIPS (Competition and Demos) 2021: 80-96 - [c10]Jack Geary, Subramanian Ramamoorthy, Henry Gouk:
Resolving Conflict in Decision-Making for Autonomous Driving. Robotics: Science and Systems 2021 - [i16]Xueting Zhang, Debin Meng, Henry Gouk, Timothy M. Hospedales:
Shallow Bayesian Meta Learning for Real-World Few-Shot Recognition. CoRR abs/2101.02833 (2021) - [i15]Boyan Gao, Henry Gouk, Timothy M. Hospedales:
Searching for Robustness: Loss Learning for Noisy Classification Tasks. CoRR abs/2103.00243 (2021) - [i14]Jack Geary, Henry Gouk, Subramanian Ramamoorthy:
Active Altruism Learning and Information Sufficiency for Autonomous Driving. CoRR abs/2110.04580 (2021) - [i13]Linus Ericsson, Henry Gouk, Chen Change Loy, Timothy M. Hospedales:
Self-Supervised Representation Learning: Introduction, Advances and Challenges. CoRR abs/2110.09327 (2021) - [i12]Linus Ericsson, Henry Gouk, Timothy M. Hospedales:
Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks. CoRR abs/2111.11398 (2021) - 2020
- [c9]Vithya Yogarajan, Henry Gouk, Tony Smith, Michael Mayo, Bernhard Pfahringer:
Comparing High Dimensional Word Embeddings Trained on Medical Text to Bag-of-Words for Predicting Medical Codes. ACIIDS (1) 2020: 97-108 - [c8]Hongyu Wang, Henry Gouk, Eibe Frank, Bernhard Pfahringer, Michael Mayo:
A Comparison of Machine Learning Methods for Cross-Domain Few-Shot Learning. Australasian Conference on Artificial Intelligence 2020: 445-457 - [c7]Boyan Gao, Yongxin Yang, Henry Gouk, Timothy M. Hospedales:
Deep Clustering for Domain Adaptation. ICASSP 2020: 4247-4251 - [c6]Boyan Gao, Yongxin Yang, Henry Gouk, Timothy M. Hospedales:
Deep Clusteringwith Concrete K-Means. ICASSP 2020: 4252-4256 - [i11]Henry Gouk, Timothy M. Hospedales, Massimiliano Pontil:
Distance-Based Regularisation of Deep Networks for Fine-Tuning. CoRR abs/2002.08253 (2020) - [i10]Linus Ericsson, Henry Gouk, Timothy M. Hospedales:
Don't Wait, Just Weight: Improving Unsupervised Representations by Learning Goal-Driven Instance Weights. CoRR abs/2006.12360 (2020) - [i9]Jack Geary, Henry Gouk:
Altruistic Decision-Making for Autonomous Driving with Sparse Rewards. CoRR abs/2007.07182 (2020) - [i8]Jack Geary, Henry Gouk:
Resolving Conflict in Decision-Making for Autonomous Driving. CoRR abs/2009.06394 (2020) - [i7]Panagiotis Eustratiadis, Henry Gouk, Da Li, Timothy M. Hospedales:
A Stochastic Neural Network for Attack-Agnostic Adversarial Robustness. CoRR abs/2010.08852 (2020) - [i6]Linus Ericsson, Henry Gouk, Timothy M. Hospedales:
How Well Do Self-Supervised Models Transfer? CoRR abs/2011.13377 (2020)
2010 – 2019
- 2019
- [c5]Henry Gouk, Bernhard Pfahringer, Eibe Frank:
Stochastic Gradient Trees. ACML 2019: 1094-1109 - [i5]Henry Gouk, Bernhard Pfahringer, Eibe Frank:
Stochastic Gradient Trees. CoRR abs/1901.07777 (2019) - [i4]Boyan Gao, Yongxin Yang, Henry Gouk, Timothy M. Hospedales:
Deep clustering with concrete k-means. CoRR abs/1910.08031 (2019) - 2018
- [c4]Henry Gouk, Bernhard Pfahringer, Eibe Frank, Michael J. Cree:
MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes. ECML/PKDD (1) 2018: 541-556 - [i3]Henry Gouk, Eibe Frank, Bernhard Pfahringer, Michael J. Cree:
Regularisation of Neural Networks by Enforcing Lipschitz Continuity. CoRR abs/1804.04368 (2018) - [i2]Henry Gouk, Bernhard Pfahringer, Eibe Frank, Michael J. Cree:
MaxGain: Regularisation of Neural Networks by Constraining Activation Magnitudes. CoRR abs/1804.05965 (2018) - 2016
- [c3]Henry Gouk, Bernhard Pfahringer, Michael J. Cree:
Learning Distance Metrics for Multi-Label Classification. ACML 2016: 318-333 - [c2]Michael J. Cree, John A. Perrone, Gehan Anthonys, Aden C. Garnett, Henry Gouk:
Estimating heading direction from monocular video sequences using biologically-based sensors. IVCNZ 2016: 1-6 - 2015
- [i1]Henry Gouk, Bernhard Pfahringer, Michael J. Cree:
Learning Similarity Metrics by Factorising Adjacency Matrices. CoRR abs/1511.06442 (2015) - 2014
- [c1]Henry G. R. Gouk, Anthony M. Blake:
Fast Sliding Window Classification with Convolutional Neural Networks. IVCNZ 2014: 114
Coauthor Index
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last updated on 2024-10-07 22:17 CEST by the dblp team
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