Published as a conference paper at ICLRM ULTI - TASK S EQUENCE TO S EQUENCE L EARNING Minh-Thang Luong∗, Quoc V. Le, Ilya Sutskever, Oriol Vinyals, Lukasz Kaiser Google Brain ,{qvl,ilyasu,vin

Source URL: arxiv.org

• Machine learning
• Computational linguistics
• Artificial neural networks
• Computational neuroscience
• Computer-assisted translation
• Feature learning
• Parsing
• Machine translation
• Neural machine translation
• Autoencoder
• Evaluation of machine translation
• Multi-task learning

Urban Water Quality Prediction based on Multi-task Multi-view Learning Ye Liu1,2∗ , Yu Zheng2,3,4 , Yuxuan Liang3,2∗ , Shuming Liu5 , David S. Rosenblum1 1 School of Computing, National University of Singapore, Singa

Source URL: www.comp.nus.edu.sg

Convex Multi-Task Learning by Clustering Aviad Barzilai Department of Electrical Engineering The Technion, Haifa, Israel

Source URL: jmlr.org

Sparse Bayesian Multi-Task Learning C´edric Archambeau, Shengbo Guo, Onno Zoeter Xerox Research Centre Europe {Cedric.Archambeau, Shengbo.Guo, Onno.Zoeter}@xrce.xerox.com

Source URL: www0.cs.ucl.ac.uk

Multi-task and Transfer Learning Massimiliano Pontil Department of Computer Science Centre for Computational Statistics and Machine Learning University College London

Source URL: mlss.tuebingen.mpg.de

Learning with Whom to Share in Multi-task Feature Learning Zhuoliang Kang Department of Computer Science, U. of Southern California, Los Angeles, CAKristen Grauman Department of Computer Science, U. of Texas, Aus

Source URL: zhuoliang.me

Robust Multi-Task Learning with t-Processes Shipeng Yu† CAD and Knowledge Solutions, Siemens Medical Solutions, Malvern, PA 19355, USA Volker Tresp

Source URL: www.dbs.informatik.uni-muenchen.de

REGULARIZATION OF CONTEXT-DEPENDENT DEEP NEURAL NETWORKS WITH CONTEXT-INDEPENDENT MULTI-TASK TRAINING Peter Bell and Steve Renals Centre for Speech Technology Research, University of Edinburgh, Edinburgh EH8 9AB, UK ABST

Source URL: www.cstr.ed.ac.uk

• Artificial neural networks
• Machine learning
• Artificial intelligence
• Applied mathematics
• Speech recognition
• Boltzmann machine
• Recurrent neural network
• Multi-task learning
• Deep belief network
• Backpropagation
• Acoustic model
• Language model

Complementary tasks for context-dependent deep neural network acoustic models Peter Bell, Steve Renals Centre for Speech Technology Research, University of Edinburgh, Edinburgh EH8 9AB, UK {peter.bell, s.renals}@ed.ac.uk

Source URL: www.cstr.ed.ac.uk

• Artificial intelligence
• Machine learning
• Learning
• Applied mathematics
• Computational linguistics
• Automatic identification and data capture
• Computer accessibility
• Speech recognition
• Artificial neural network
• Multi-task learning
• Recurrent neural network
• Statistical classification

Fusion of multiple parameterisations for DNN-based sinusoidal speech synthesis with multi-task learning Qiong Hu1 , Zhizheng Wu1 , Korin Richmond1 , Junichi Yamagishi1 , Yannis Stylianou2 , Ranniery Maia2 1 The Centre f

Source URL: www.cstr.ed.ac.uk

• Music
• Computational linguistics
• Audio electronics
• Artificial intelligence
• Music hardware
• Robotics
• Vocoder
• Speech recognition
• Speech synthesis
• Synthesizer
• Artificial neural network
• Frequency modulation