Mahesan Niranjan
Mahesan Niranjan
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Cited by
Cited by
On-line Q-learning using connectionist systems
GA Rummery, M Niranjan
University of Cambridge, Department of Engineering 37, 14, 1994
A function estimation approach to sequential learning with neural networks
V Kadirkamanathan, M Niranjan
Neural computation 5 (6), 954-975, 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
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
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
Neural networks and radial basis functions in classifying static speech patterns
M Niranjan, F Fallside
Computer Speech & Language 4 (3), 275-289, 1990
Deep cascade learning
ES Marquez, JS Hare, M Niranjan
IEEE transactions on neural networks and learning systems 29 (11), 5475-5485, 2018
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
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
Hierarchical Bayesian models for regularization in sequential learning
JFG Freitas, M Niranjan, AH Gee
Neural computation 12 (4), 933-953, 2000
Data-dependent kernels in SVM classification of speech patterns
S Nathan
ICSLP-2000 1, 297-300, 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
Realisable Classifiers: Improving Operating Performance on Variable Cost Problems.
MJJ Scott, M Niranjan, RW Prager
BMVC, 1-10, 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
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
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
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
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
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
Design of a low-power on-body ECG classifier for remote cardiovascular monitoring systems
T Chen, EB Mazomenos, K Maharatna, S Dasmahapatra, M Niranjan
IEEE Journal on Emerging and Selected Topics in Circuits and Systems 3 (1 …, 2013
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