| On-line Q-learning using connectionist systems GA Rummery, M Niranjan University of Cambridge, Department of Engineering 37, 14, 1994 | 2835 | 1994 |
| A function estimation approach to sequential learning with neural networks V Kadirkamanathan, M Niranjan Neural computation 5 (6), 954-975, 1993 | 645 | 1993 |
| A theoretical investigation into the performance of the Hopfield model SVB Aiyer, M Niranjan, F Fallside IEEE transactions on neural networks 1 (2), 204-215, 1990 | 610 | 1990 |
| Sequential Monte Carlo methods to train neural network models JFG de Freitas, M Niranjan, AH Gee, A Doucet Neural computation 12 (4), 955-993, 2000 | 305 | 2000 |
| Financial news predicts stock market volatility better than close price A Atkins, M Niranjan, E Gerding The Journal of Finance and Data Science 4 (2), 120-137, 2018 | 224 | 2018 |
| Neural networks and radial basis functions in classifying static speech patterns M Niranjan, F Fallside Computer Speech & Language 4 (3), 275-289, 1990 | 161 | 1990 |
| Fmix: Enhancing mixed sample data augmentation E Harris, A Marcu, M Painter, M Niranjan, A Prügel-Bennett, J Hare arXiv preprint arXiv:2002.12047, 2020 | 160 | 2020 |
| Deep cascade learning ES Marquez, JS Hare, M Niranjan IEEE transactions on neural networks and learning systems 29 (11), 5475-5485, 2018 | 148 | 2018 |
| On acoustic emotion recognition: compensating for covariate shift A Hassan, R Damper, M Niranjan IEEE Transactions on Audio, Speech, and Language Processing 21 (7), 1458-1468, 2013 | 140 | 2013 |
| Hierarchical Bayesian models for regularization in sequential learning JFG Freitas, M Niranjan, AH Gee Neural computation 12 (4), 933-953, 2000 | 121 | 2000 |
| Data-dependent kernels in SVM classification of speech patterns N Smith, M Niranjan Proc. ICSLP 2000, vol. 1, 297-300, 2000 | 110 | 2000 |
| Trendminer: An architecture for real time analysis of social media text D Preotiuc-Pietro, S Samangooei, T Cohn, N Gibbins, M Niranjan Proceedings of the International AAAI Conference on Web and Social Media 6 …, 2012 | 108 | 2012 |
| Simultaneous pursuit of out-of-sample performance and sparsity in index tracking portfolios A Takeda, M Niranjan, J Gotoh, Y Kawahara Computational Management Science 10, 21-49, 2013 | 90 | 2013 |
| Realisable Classifiers: Improving Operating Performance on Variable Cost Problems. MJJ Scott, M Niranjan, RW Prager BMVC, 1-10, 1998 | 89 | 1998 |
| Sequential adaptation of radial basis function neural networks and its application to time-series prediction V Kadirkamanathan, M Niranjan, F Fallside Advances in Neural Information Processing Systems 3, 1990 | 66 | 1990 |
| A comparison of multitask and single task learning with artificial neural networks for yield curve forecasting M Nunes, E Gerding, F McGroarty, M Niranjan Expert Systems with Applications 119, 362-375, 2019 | 65 | 2019 |
| Biomedical visual data analysis to build an intelligent diagnostic decision support system in medical genetics K Kuru, M Niranjan, Y Tunca, E Osvank, T Azim Artificial intelligence in medicine 62 (2), 105-118, 2014 | 63 | 2014 |
| Sequential Monte Carlo methods for neural networks N De Freitas, C Andrieu, P Højen-Sørensen, M Niranjan, A Gee Sequential Monte Carlo methods in practice, 359-379, 2001 | 61 | 2001 |
| Enhancing the biological relevance of machine learning classifiers for reverse vaccinology AI Heinson, Y Gunawardana, B Moesker, CC Denman Hume, E Vataga, ... International journal of molecular sciences 18 (2), 312, 2017 | 56 | 2017 |
| A probabilistic model for the extraction of expression levels from oligonucleotide arrays M Milo, A Fazeli, M Niranjan, ND Lawrence Biochemical Society Transactions 31 (6), 1510-1512, 2003 | 56 | 2003 |
Nando de FreitasCIFAR & DeepMind在 google.com 的电子邮件经过验证
