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Continual Density Ratio Estimation in an Online Setting

Mar 09, 2021
Yu Chen, Song Liu, Tom Diethe, Peter Flach

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Interpretable Anomaly Detection with Mondrian P{贸}lya Forests on Data Streams

Aug 04, 2020
Charlie Dickens, Eric Meissner, Pablo G. Moreno, Tom Diethe

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Bypassing Gradients Re-Projection with Episodic Memories in Online Continual Learning

Jun 19, 2020
Yu Chen, Tom Diethe, Peter Flach

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Optimal Continual Learning has Perfect Memory and is NP-hard

Jun 09, 2020
Jeremias Knoblauch, Hisham Husain, Tom Diethe

* Accepted for publication at ICML (International Conference on Machine Learning) 2020; 13 pages, 8 Figures 

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Similarity of Neural Networks with Gradients

Mar 25, 2020
Shuai Tang, Wesley J. Maddox, Charlie Dickens, Tom Diethe, Andreas Damianou

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Leveraging Hierarchical Representations for Preserving Privacy and Utility in Text

Oct 20, 2019
Oluwaseyi Feyisetan, Tom Diethe, Thomas Drake

* Accepted at ICDM 2019 

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Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations

Oct 20, 2019
Oluwaseyi Feyisetan, Borja Balle, Thomas Drake, Tom Diethe

* Accepted at WSDM 2020 

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HyperStream: a Workflow Engine for Streaming Data

Aug 07, 2019
Tom Diethe, Meelis Kull, Niall Twomey, Kacper Sokol, Hao Song, Miquel Perello-Nieto, Emma Tonkin, Peter Flach

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Automatic Discovery of Privacy-Utility Pareto Fronts

May 26, 2019
Brendan Avent, Javier Gonzalez, Tom Diethe, Andrei Paleyes, Borja Balle

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Distribution Calibration for Regression

May 15, 2019
Hao Song, Tom Diethe, Meelis Kull, Peter Flach

* ICML 2019, 10 pages 

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Facilitating Bayesian Continual Learning by Natural Gradients and Stein Gradients

Apr 24, 2019
Yu Chen, Tom Diethe, Neil Lawrence

* Continual Learning Workshop of 32nd Conference on Neural Information Processing Systems (NeurIPS 2018) 

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Privacy-preserving Active Learning on Sensitive Data for User Intent Classification

Mar 26, 2019
Oluwaseyi Feyisetan, Thomas Drake, Borja Balle, Tom Diethe

* To appear at PAL: Privacy-Enhancing Artificial Intelligence and Language Technologies as part of the AAAI Spring Symposium Series (AAAI-SSS 2019) 

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Continual Learning in Practice

Mar 18, 2019
Tom Diethe, Tom Borchert, Eno Thereska, Borja Balle, Neil Lawrence

* Presented at the NeurIPS 2018 workshop on Continual Learning 

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$尾^3$-IRT: A New Item Response Model and its Applications

Mar 13, 2019
Yu Chen, Telmo Silva Filho, Ricardo B. C. Prud锚ncio, Tom Diethe, Peter Flach

* AISTATS 2019 

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Probabilistic Sensor Fusion for Ambient Assisted Living

Feb 04, 2017
Tom Diethe, Niall Twomey, Meelis Kull, Peter Flach, Ian Craddock

* Journal article. 19 pages; 7 figures 

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A Note on the Kullback-Leibler Divergence for the von Mises-Fisher distribution

Feb 25, 2015
Tom Diethe

* 8 pages 1 figure 

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Data-dependent kernels in nearly-linear time

Oct 20, 2011
Guy Lever, Tom Diethe, John Shawe-Taylor

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Convex Multiview Fisher Discriminant Analysis

Oct 29, 2009
Tom Diethe, John Shawe-Taylor

* This paper has been withdrawn 

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