Snehanshu Saha
Snehanshu Saha
Professor, CSIS and Head-APPCAIR, BITS Pilani Goa Campus
Verified email at - Homepage
Cited by
Cited by
Predicting the direction of stock market prices using tree-based classifiers
S Basak, S Kar, S Saha, L Khaidem, SR Dey
The North American Journal of Economics and Finance 47, 552-567, 2019
Predicting the direction of stock market prices using random forest
L Khaidem, S Saha, SR Dey
arXiv preprint arXiv:1605.00003, 2016
Forecasting to Classification: Predicting the direction of stock market price using Xtreme Gradient Boosting
S Dey, Y Kumar, S Saha, S Basak
PESIT South Campus, 1-10, 2016
A novel revenue optimization model to address the operation and maintenance cost of a data center
S Saha, J Sarkar, A Dwivedi, N Dwivedi, AM Narasimhamurthy, R Roy
Journal of Cloud Computing 5, 1-23, 2016
Cd-hpf: New habitability score via data analytic modeling
K Bora, S Saha, S Agrawal, M Safonova, S Routh, A Narasimhamurthy
Astronomy and Computing 17, 129-143, 2016
ChaosNet: A chaos based artificial neural network architecture for classification
HN Balakrishnan, A Kathpalia, S Saha, N Nagaraj
Chaos: An Interdisciplinary Journal of Nonlinear Science 29 (11), 2019
A communication paradigm using subvocalized speech: translating brain signals into speech
K Mohanchandra, S Saha
Augmented Human Research 1 (1), 3, 2016
Theoretical validation of potential habitability via analytical and boosted tree methods: An optimistic study on recently discovered exoplanets
S Saha, S Basak, M Safonova, K Bora, S Agrawal, P Sarkar, J Murthy
Astronomy and computing 23, 141-150, 2018
ScientoBASE: a framework and model for computing scholastic indicators of non-local influence of journals via native data acquisition algorithms
G Ginde, S Saha, A Mathur, S Venkatagiri, S Vadakkepat, ...
Scientometrics 108, 1479-1529, 2016
Lipschitzlr: Using theoretically computed adaptive learning rates for fast convergence
R Yedida, S Saha, T Prashanth
Applied Intelligence 51, 1460-1478, 2021
Evolution of novel activation functions in neural network training for astronomy data: habitability classification of exoplanets
S Saha, N Nagaraj, A Mathur, R Yedida, S HR
The European Physical Journal Special Topics 229 (16), 2629-2738, 2020
AdaSwarm: Augmenting gradient-based optimizers in Deep Learning with Swarm Intelligence
SS Rohan Mohapatra, Snehanshu Saha, Carlos A. Coello, Anwesh Bhattacharya ...
IEEE Transactions on Emerging Topics in Computational Intelligence; https …, 2021
QoS guaranteed intelligent routing using hybrid PSO-GA in wireless mesh networks
V Sarasvathi, NCSN Iyengar, S Saha
Cybernetics and Information Technologies 15 (1), 69-83, 2015
EEG based brain computer interface for speech communication: principles and applications
K Mohanchandra, S Saha, GM Lingaraju
Brain-Computer Interfaces: Current Trends and Applications, 273-293, 2015
A novel exoplanetary habitability score via particle swarm optimization of CES production functions
A Theophilus, S Saha, S Basak, J Murthy
2018 IEEE Symposium Series on Computational Intelligence (SSCI), 2139-2147, 2018
TeamDL at SemEval-2018 task 8: Cybersecurity text analysis using convolutional neural network and conditional random fields
R Manikandan, K Madgula, S Saha
Proceedings of The 12th International Workshop on Semantic Evaluation, 868-873, 2018
Distinct adoption of k-nearest neighbour and support vector machine in classifying EEG signals of mental tasks
K Mohanchandra, S Saha, KS Murthy, GM Lingaraju
International Journal of Intelligent Engineering Informatics 3 (4), 313-329, 2015
Early prediction of LBW cases via minimum error rate classifier: A statistical machine learning approach
AR Yarlapati, SR Dey, S Saha
2017 IEEE International Conference on Smart Computing (SMARTCOMP), 1-6, 2017
An efficient interference aware partially overlapping channel assignment and routing in wireless mesh networks
V Sarasvathi, NCSN Iyengar, S Saha
International Journal of Communication Networks and Information Security …, 2014
A novel adaptive learning rate scheduler for deep neural networks
R Yedida, S Saha
arXiv preprint arXiv:1902.07399, 2019
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