machinelearning.eecs.qmul.ac.uk

Applied Machine Learning Lab – Machine Learning @ QMUL

Applied Machine Learning Lab. Machine Learning @ QMUL. We’re the Applied Machine Learning lab at Queen Mary University of London,. A research group within Electronic Engineering and Computer Science. Our members belong to various groups within EECS, including Risk and Information Management. We study a variety of ML methodologies:. Transfer and Multi-Task Learning. Cross-modal and zero-shot learning. Active learning and Active perception. Weakly and semi-supervised learning. 8230;and application areas:.

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Applied Machine Learning Lab – Machine Learning @ QMUL | machinelearning.eecs.qmul.ac.uk Reviews

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Applied Machine Learning Lab. Machine Learning @ QMUL. We’re the Applied Machine Learning lab at Queen Mary University of London,. A research group within Electronic Engineering and Computer Science. Our members belong to various groups within EECS, including Risk and Information Management. We study a variety of ML methodologies:. Transfer and Multi-Task Learning. Cross-modal and zero-shot learning. Active learning and Active perception. Weakly and semi-supervised learning. 8230;and application areas:.

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Applied Machine Learning Lab – Machine Learning @ QMUL | machinelearning.eecs.qmul.ac.uk Reviews

https://machinelearning.eecs.qmul.ac.uk

Applied Machine Learning Lab. Machine Learning @ QMUL. We’re the Applied Machine Learning lab at Queen Mary University of London,. A research group within Electronic Engineering and Computer Science. Our members belong to various groups within EECS, including Risk and Information Management. We study a variety of ML methodologies:. Transfer and Multi-Task Learning. Cross-modal and zero-shot learning. Active learning and Active perception. Weakly and semi-supervised learning. 8230;and application areas:.

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machinelearning.eecs.qmul.ac.uk

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Data and Code – Applied Machine Learning Lab

http://machinelearning.eecs.qmul.ac.uk/data-and-code

Applied Machine Learning Lab. Machine Learning @ QMUL. 800K food images and metadata. From Instagram. [Health, Vision, Social Network Analytics]. 8211; Images and Telemetry [ Vision, Domain Adaptation ]. Shoe and Chair Data. 8211; Images and Sketches [ Fine-grained SBIR ]. Deep Neural Network for Sketch Recognition. Multi-task/multi-domain learning framework with neural networks. Sketch Me That Shoe. Code for CVPR’16 fine-grained SBIR paper. 05/2016: Tanmoy and Maryam presenting at PyData London.

2

People – Applied Machine Learning Lab

http://machinelearning.eecs.qmul.ac.uk/people

Applied Machine Learning Lab. Machine Learning @ QMUL. 05/2016: Tanmoy and Maryam presenting at PyData London. 03/2016: Three papers at CVPR'16 including Spotlight and Oral! 02/2016: ESA paper on transfer learning of Bayesian Networks. 09/2015: Our BMVC'15 sketch recognition paper wins Best Science Paper prize! Proudly powered by WordPress. Theme: Radiate by ThemeGrill.

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Projects – Applied Machine Learning Lab

http://machinelearning.eecs.qmul.ac.uk/projects-2

Applied Machine Learning Lab. Machine Learning @ QMUL. Deferred Restructuring of Experience in Autonomous Machines (Horizon 2020, 2015-2018). Fine-Grained Sketch-Based Image Retrieval (QMInnovation Fund, 2016). Live SBIR Demo: Shoes. Live SBIR Demo: Chairs. Transfer Learning for Person Re-Identification (EPSRC, 2014-15). 05/2016: Tanmoy and Maryam presenting at PyData London. 03/2016: Three papers at CVPR'16 including Spotlight and Oral! 02/2016: ESA paper on transfer learning of Bayesian Networks.

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Selected Publications – Applied Machine Learning Lab

http://machinelearning.eecs.qmul.ac.uk/projects

Applied Machine Learning Lab. Machine Learning @ QMUL. See individual members pages for full lists). Y Yang and T. M. Hospedales, Multivariate Regression on the Grassmannian for Predicting Novel Domains, CVPR 2016. pdf. Q Yu, F. Liu, Y-Z. Song, T. Xiang, T. M. Hospedales, C. C. Loy, Sketch Me That Shoe, CVPR 2016. pdf. Y Zhou, T. M. Hospedales, N. Fenton, When and Where to Transfer for Bayes Net Parameter Learning,. Expert Systems with Applications 2016. pdf. ICLR 2015. pdf. Oral, Best paper award! 03/20...

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High Noon GMT | Oh, to be torn 'twixt love an' tenure | Page 2

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Oh, to be torn 'twixt love an' tenure. Newer posts →. Upcoming Events MEET THE COMPUTER COMPOSERS FEAT. MARK D’INVERNO QUINTET Vortex Jazz Club. September 26, 2016. By Bob L. Sturm. Only a few tickets left to this unique event! Source: Upcoming Events MEET THE COMPUTER COMPOSERS FEAT. MARK D’INVERNO QUINTET Vortex Jazz Club. September 25, 2016. By Bob L. Sturm. September 19, 2016 saw the successful premier edition of HORSE2016: On Horses and Potemkin Villages in Applied Machine Learning. I present an exa...

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Applied Machine Learning Lab – Machine Learning @ QMUL

Applied Machine Learning Lab. Machine Learning @ QMUL. We’re the Applied Machine Learning lab at Queen Mary University of London,. A research group within Electronic Engineering and Computer Science. Our members belong to various groups within EECS, including Risk and Information Management. We study a variety of ML methodologies:. Transfer and Multi-Task Learning. Cross-modal and zero-shot learning. Active learning and Active perception. Weakly and semi-supervised learning. 8230;and application areas:.

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Active Learning of Regular Expressions for Entity Extraction. Annotated strings for learning text extractors. Automatic Synthesis of Regular Expressions from Examples. Can A Machine Replace Humans In Building Regular Expressions? Evolutionary Inference of Attribute-based Access Control Policies. Hidden fraudulent URLs dataset. Inference of Regular Expressions for Text Extraction from Examples. Paper citations for important Computer Science venues. XML data for automatic schema generation. New section on ...

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