On-line Q-learning using connectionist systems GA Rummery, M Niranjan University of Cambridge, Department of Engineering 37, 14, 1994 | 2672 | 1994 |
A function estimation approach to sequential learning with neural networks V Kadirkamanathan, M Niranjan Neural computation 5 (6), 954-975, 1993 | 639 | 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 | 602 | 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 | 298 | 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 | 199 | 2018 |
Neural networks and radial basis functions in classifying static speech patterns M Niranjan, F Fallside Computer Speech & Language 4 (3), 275-289, 1990 | 160 | 1990 |
Deep cascade learning ES Marquez, JS Hare, M Niranjan IEEE transactions on neural networks and learning systems 29 (11), 5475-5485, 2018 | 140 | 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 | 137 | 2013 |
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 | 134 | 2020 |
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 S Nathan ICSLP-2000 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 | 106 | 2012 |
Realisable Classifiers: Improving Operating Performance on Variable Cost Problems. MJJ Scott, M Niranjan, RW Prager BMVC, 1-10, 1998 | 88 | 1998 |
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 | 87 | 2013 |
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 | 64 | 1990 |
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 | 60 | 2001 |
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 |
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 | 55 | 2019 |
Fully vector-quantized neural network-based code-excited nonlinear predictive speech coding L Wu, M Niranjan, F Fallside IEEE transactions on speech and audio processing 2 (4), 482-489, 1994 | 55 | 1994 |
Single-cell transcriptional analysis to uncover regulatory circuits driving cell fate decisions in early mouse development H Chen, J Guo, SK Mishra, P Robson, M Niranjan, J Zheng Bioinformatics 31 (7), 1060-1066, 2015 | 53 | 2015 |