Mahesan Niranjan

发表

Supplementary material from "Robust subspace methods for outlier detection in genomic data circumvents the curse of dimensionality"

Omar Shetta, Mahesan Niranjan, M. Niranjan, 2020 .

Neural networks and radial basis functions in classifying static speech patterns

Mahesan Niranjan, Frank Fallside, M. Niranjan, 1990 .

Sequential Inference and Learning

Nando de Freitas, Mahesan Niranjan, Arnaud Doucet, 1998, NIPS 1998.

On-line Q-learning using connectionist systems

Mahesan Niranjan, Gavin Adrian Rummery, M. Niranjan, 1994 .

Handling phrase reordering for machine translation

Mahesan Niranjan, Sandor Szedmak, Yizhao Ni, 2009 .

Temporal decomposition: a framework for enhanced speech recognition

Mahesan Niranjan, Frank Fallside, M. Niranjan, 1989, International Conference on Acoustics, Speech, and Signal Processing,.

Trendminer: An Architecture for Real Time Analysis of Social Media Text

Trevor Cohn, Mahesan Niranjan, Sina Samangooei, 2012, ICWSM 2012.

Maximum Realisable Performance: a Principled Method for Enhancing Performance by Using Multiple Clas

Mahesan Niranjan, Richard W. Prager, Martin J. J. Scott, 1998 .

Speech Feature Extraction Using Neural Networks

Mahesan Niranjan, Frank Fallside, 1990, EURASIP Workshop.

Scalable Reordering Models for SMT based on Multiclass SVM

Mahesan Niranjan, Abdullah Alrajeh, 2015, Prague Bull. Math. Linguistics.

Multi-class Classification on "VINE" Structure

Mahesan Niranjan, Somjet Suppharangsan, 2011, 2011 International Conference on Future Computer Sciences and Application.

A dynamic neural network architecture by sequential partitioning of the input space

Mahesan Niranjan, R. S. Shadafan, 1993, IEEE International Conference on Neural Networks.

A numerical measure of the instability of Mapper-type algorithms pdf

Mahesan Niranjan, Jacek Brodzki, Francisco Belchí Guillamón, 2019, J. Mach. Learn. Res..

Parcel: Feature Subset Selection in Variable Cost Domains

Mahesan Niranjan, Richard W. Prager, Martin J. J. Scott, 1998 .

Self-organization with a large medical database: Using GTM for prediction and clustering

David Lovell, Mahesan Niranjan, Richard W. Prager, 1998 .

A Novel Approach to Improve the Diagnostic Success of Computers in Dysmorphology: The DSESPC methodology and its Applications

Kaya Kuru, Mahesan Niranjan, Yusuf Tunca, 2013 .

A systolic array implementation of a dynamic sequential neural network for pattern recognition

Mahesan Niranjan, R. S. Shadafan, 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

Distance phrase reordering for MOSES - User Manual and Code Guide

Mahesan Niranjan, Sandor Szedmak, Yizhao Ni, 2010 .

Sequential Adaptation of Radial Basis Function Neural Networks and its Application to Time-series Prediction

Visakan Kadirkamanathan, Mahesan Niranjan, Frank Fallside, 1990, NIPS 1990.

Models of dynamic complexity for time-series prediction (neural networks)

Visakan Kadirkamanathan, Mahesan Niranjan, Frank Fallside, 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Generative and Discriminative Reordering Models for Statistical Machine Translation

Mahesan Niranjan, Abdullah Alrajeh, 2016 .

Global optimisation of neural network models via sequential sampling-importance resampling

Mahesan Niranjan, S. E. Johnson, Joao F. G. De Freitas, 1998, ICSLP.