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2020 – today
- 2024
[j38]Swarnali Banik
, Sougata Sen, Snehanshu Saha, Surjya Ghosh:
Towards Reducing Continuous Emotion Annotation Effort During Video Consumption: A Physiological Response Profiling Approach. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 8(3): 91:1-91:32 (2024)- [j37]Vihaan Misra, Shivashankar S. Menon, Snehanshu Saha, Archana Mathur, Haoxiang Yu, Vaskar Raychoudhury:
AdaGen: Adaptive Generalized Knowledge Transfer Framework for Sensor-Based Surface Classification for Wheelchair Routing. SN Comput. Sci. 5(7): 820 (2024) - [j36]Snehanshu Saha, Jyotirmoy Sarkar, Soma S. Dhavala, Preyank Mota, Santonu Sarkar:
quantile-Long Short Term Memory: A Robust, Time Series Anomaly Detection Method. IEEE Trans. Artif. Intell. 5(8): 3939-3950 (2024) - [j35]Aditi Seetha, Satyendra Singh Chouhan, Emmanuel S. Pilli, Vaskar Raychoudhury, Snehanshu Saha:
DiEvD-SF: Disruptive Event Detection Using Continual Machine Learning With Selective Forgetting. IEEE Trans. Comput. Soc. Syst. 11(3): 4189-4201 (2024) - [c34]Ashman Mehra, Snehanshu Saha, Vaskar Raychoudhury, Archana Mathur:
DeliverAI: Reinforcement Learning Based Distributed Path-Sharing Network for Food Deliveries. IJCNN 2024: 1-9 - [c33]Alfiya M. Shaikh, Hrithik Nambiar, Kshitish Ghate, Swarnali Banik, Sougata Sen, Surjya Ghosh, Vaskar Raychoudhury, Niloy Ganguly, Snehanshu Saha:
Self-SLAM: A Self-supervised Learning Based Annotation Method to Reduce Labeling Overhead. ECML/PKDD (9) 2024: 123-140 - [i43]Rahul Yedida, Snehanshu Saha:
Strong convexity-guided hyper-parameter optimization for flatter losses. CoRR abs/2402.05025 (2024) - [i42]Santonu Sarkar, Shanay Mehta, Nicole Fernandes, Jyotirmoy Sarkar, Snehanshu Saha:
Can Tree Based Approaches Surpass Deep Learning in Anomaly Detection? A Benchmarking Study. CoRR abs/2402.07281 (2024) - [i41]Aditya Challa, Sravan Danda, Laurent Najman, Snehanshu Saha:
Quantile Activation: departing from single point estimation for better generalization across distortions. CoRR abs/2405.11573 (2024) - 2023
- [j34]Jyotirmoy Sarkar, Snehanshu Saha, Santonu Sarkar:
Efficient anomaly identification in temporal and non-temporal industrial data using tree based approaches. Appl. Intell. 53(8): 8562-8595 (2023) - [j33]Yash Gondhalekar, Margarita Safonova, Snehanshu Saha:
β-SGP: Scaled Gradient Projection with β-divergence for astronomical image restoration. Astron. Comput. 44: 100739 (2023) - [j32]Sumana Sinha, Snehanshu Saha:
An improved communication strategy in vehicular ad hoc networks: adaptive game theoretic modelling approach. Int. J. Mob. Commun. 21(2): 273-293 (2023) - [j31]Prajwal Melath, Ayush Raj, Sougata Sen, Snehanshu Saha, Surjya Ghosh:
Towards Efficient Emotion Self-report Collection Using Human-AI Collaboration: A Case Study on Smartphone Keyboard Interaction. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 7(2): 68:1-68:23 (2023) - [j30]Sudeepa Roy Dey, Archana Mathur, B. S. Dayasagar, Snehanshu Saha:
ALIS: A novel metric in lineage-independent evaluation of scholars. J. Inf. Sci. 49(4): 1007-1030 (2023) - [j29]Haoxiang Yu, Vaskar Raychoudhury, Snehanshu Saha, Janick Edinger, Roger O. Smith, Md. Osman Gani:
Automated Surface Classification System Using Vibration Patterns - A Case Study With Wheelchairs. IEEE Trans. Artif. Intell. 4(4): 884-895 (2023) - [j28]Nikhilanand Arya, Archana Mathur, Snehanshu Saha, Sriparna Saha:
Proposal of SVM Utility Kernel for Breast Cancer Survival Estimation. IEEE ACM Trans. Comput. Biol. Bioinform. 20(2): 1372-1383 (2023) - [j27]Gargi Alavani, Jineet Desai, Snehanshu Saha, Santonu Sarkar:
Program Analysis and Machine Learning-based Approach to Predict Power Consumption of CUDA Kernel. ACM Trans. Model. Perform. Evaluation Comput. Syst. 8(4): 10:1-10:24 (2023) - [i40]Snehanshu Saha, Jyotirmoy Sarkar, Soma S. Dhavala, Santonu Sarkar, Preyank Mota:
Quantile LSTM: A Robust LSTM for Anomaly Detection In Time Series Data. CoRR abs/2302.08712 (2023) - [i39]Pronoma Banerjee, Manasi V. Gude, Rajvi J. Sampat, Sharvari M. Hedaoo, Soma S. Dhavala, Snehanshu Saha:
Correcting Model Misspecification via Generative Adversarial Networks. CoRR abs/2304.03805 (2023) - [i38]Aditya Challa, Snehanshu Saha, Soma S. Dhavala:
Decoupling Quantile Representations from Loss Functions. CoRR abs/2304.12766 (2023) - [i37]Rajan Sahu, Shivam Chadha, Nithin Nagaraj, Archana Mathur, Snehanshu Saha:
To prune or not to prune : A chaos-causality approach to principled pruning of dense neural networks. CoRR abs/2308.09955 (2023) - [i36]Ashman Mehra, Snehanshu Saha, Vaskar Raychoudhury, Archana Mathur:
DeliverAI: Reinforcement Learning Based Distributed Path-Sharing Network for Food Deliveries. CoRR abs/2311.02017 (2023) - [i35]Sourabh Patil, Archana Mathur, Raviprasad Aduri, Snehanshu Saha:
A novel RNA pseudouridine site prediction model using Utility Kernel and data-driven parameters. CoRR abs/2311.16132 (2023) - 2022
- [j26]Anuj Tambwekar, Anirudh Maiya, Soma S. Dhavala, Snehanshu Saha:
Estimation and Applications of Quantiles in Deep Binary Classification. IEEE Trans. Artif. Intell. 3(2): 275-286 (2022) - [j25]Tejas Prashanth, Snehanshu Saha, Sumedh Basarkod, Suraj Aralihalli, Soma S. Dhavala, Sriparna Saha, Raviprasad Aduri:
LipGene: Lipschitz Continuity Guided Adaptive Learning Rates for Fast Convergence on Microarray Expression Data Sets. IEEE ACM Trans. Comput. Biol. Bioinform. 19(6): 3553-3563 (2022) - [j24]Rohan Mohapatra, Snehanshu Saha, Carlos A. Coello Coello, Anwesh Bhattacharya, Soma S. Dhavala, Sriparna Saha:
AdaSwarm: Augmenting Gradient-Based Optimizers in Deep Learning With Swarm Intelligence. IEEE Trans. Emerg. Top. Comput. Intell. 6(2): 329-340 (2022) - [j23]Aishwarya Manjunath, Vaskar Raychoudhury, Snehanshu Saha, Saibal Kar, Anusha Kamath:
CARE-Share: A Cooperative and Adaptive Strategy for Distributed Taxi Ride Sharing. IEEE Trans. Intell. Transp. Syst. 23(7): 7028-7044 (2022) - [c32]Snigdha Sen, Snehanshu Saha, Pavan Chakraborty, Krishna Pratap Singh:
A Fast and Robust Photometric Redshift Forecasting Method Using Lipschitz Adaptive Learning Rate. ICONIP (5) 2022: 123-135 - [c31]Omatharv Bharat Vaidya, Rithvik Terence DSouza, Soma S. Dhavala, Snehanshu Saha, Swagatam Das:
HMC-PSO: A Hamiltonian Monte Carlo and Particle Swarm Optimization-Based Optimizer. ICONIP (1) 2022: 212-223 - [c30]Abhijeet Swain, Vaibhav Ganatra, Snehanshu Saha, Archana Mathur, Rekha Phadke:
P-LSTM: A Novel LSTM Architecture for Glucose Level Prediction Problem. ICONIP (7) 2022: 369-380 - [c29]Anwesh Bhattacharya, Snehanshu Saha, Nithin Nagaraj:
Fairly Constricted Multi-objective Particle Swarm Optimization. ICONIP (4) 2022: 610-621 - [c28]John Hata, Haoxiang Yu, Vaskar Raychoudhury, Snehanshu Saha, Huy Tran Quang:
Study of Heterogeneous User Behavior in Crowd Evacuation in Presence of Wheelchair Users. PAAMS 2022: 229-241 - [i34]Aryaman Jeendgar, Aditya Pola, Soma S. Dhavala, Snehanshu Saha:
LogGENE: A smooth alternative to check loss for Deep Healthcare Inference Tasks. CoRR abs/2206.09333 (2022) - [i33]Omatharv Bharat Vaidya, Rithvik Terence DSouza, Snehanshu Saha, Soma S. Dhavala, Swagatam Das:
Hamiltonian Monte Carlo Particle Swarm Optimizer. CoRR abs/2206.14134 (2022) - [i32]Shashank Sanjay Bhat, Prabu Thiagaraj, Ben Stappers, Atul Ghalame, Snehanshu Saha, T. S. B. Sudarshan, Zafiirah Hosenie:
Investigation of a Machine learning methodology for the SKA pulsar search pipeline. CoRR abs/2209.04430 (2022) - 2021
- [j22]Rahul Yedida, Snehanshu Saha, Tejas Prashanth:
LipschitzLR: Using theoretically computed adaptive learning rates for fast convergence. Appl. Intell. 51(3): 1460-1478 (2021) - [c27]Pragnya Sridhar, Deepika Karanji, Gambhire Swati Sampatrao, Sravan Danda, Snehanshu Saha:
Semantic Influence Score: Tracing Beautiful Minds Through Knowledge Diffusion and Derivative Works. DEXA Workshops 2021: 106-115 - [c26]Patnala Prudhvi Raj, Snehanshu Saha, Gowri Srinivasa:
Solving the N-Queens and Golomb Ruler Problems Using DQN and an Approximation of the Convergence. ICONIP (6) 2021: 545-553 - [c25]Jyotirmoy Sarkar, Santonu Sarkar, Snehanshu Saha, Swagatam Das:
d-BTAI: The Dynamic-Binary Tree Based Anomaly Identification Algorithm for Industrial Systems. IEA/AIE (2) 2021: 519-532 - [c24]Snigdha Sen, Snehanshu Saha, Pavan Chakraborty, Krishna Pratap Singh:
Implementation of Neural Network Regression Model for Faster Redshift Analysis on Cloud-Based Spark Platform. IEA/AIE (2) 2021: 591-602 - [c23]Kanchan Jha, Sriparna Saha, Snehanshu Saha:
Prediction of Protein-Protein Interactions using Deep Multi-Modal Representations. IJCNN 2021: 1-8 - [c22]Urvil Nileshbhai Jivani, Omatharv Bharat Vaidya, Anwesh Bhattacharya, Snehanshu Saha:
A Swarm Variant for the Schrödinger Solver. IJCNN 2021: 1-8 - [c21]Ishita Mediratta, Snehanshu Saha, Shubhad Mathur:
LipARELU: ARELU Networks aided by Lipschitz Acceleration. IJCNN 2021: 1-8 - [c20]Snehanshu Saha, Archana Mathur, Aditya Pandey, Harshith Arun Kumar:
DiffAct: A Unifying Framework for Activation Functions. IJCNN 2021: 1-8 - [c19]Haoxiang Yu, Vaskar Raychoudhury, Snehanshu Saha:
Dynamic Taxi Ride-Sharing Through Adaptive Request Propagation Using Regional Taxi Demand and Supply. MobiQuitous 2021: 40-56 - [i31]Anuj Tambwekar, Anirudh Maiya, Soma S. Dhavala, Snehanshu Saha:
Estimation and Applications of Quantiles in Deep Binary Classification. CoRR abs/2102.06575 (2021) - [i30]Urvil Nileshbhai Jivani, Omatharv Bharat Vaidya, Anwesh Bhattacharya, Snehanshu Saha:
A Swarm Variant for the Schrödinger Solver. CoRR abs/2104.04795 (2021) - [i29]Anwesh Bhattacharya, Snehanshu Saha:
Fairly Constricted Particle Swarm Optimization. CoRR abs/2104.10040 (2021) - [i28]Jyotirmoy Sarkar, Kartik Bhatia, Snehanshu Saha, Margarita Safonova, Santonu Sarkar:
Postulating Exoplanetary Habitability via a Novel Anomaly Detection Method. CoRR abs/2109.02273 (2021) - 2020
- [j21]Suryoday Basak, Snehanshu Saha, Archana Mathur, Kakoli Bora, Simran Makhija, Margarita Safonova, Surbhi Agrawal:
CEESA meets machine learning: A Constant Elasticity Earth Similarity Approach to habitability and classification of exoplanets. Astron. Comput. 30: 100335 (2020) - [j20]Ankush Mishra, Snehanshu Saha, Simran Makhija, Sumana Sinha, Vaskar Raychoudhury, Sobin C. C.:
Empirical study of dynamics of amoebiasis transmission in mobile ad hoc networks (MANETs). Int. J. Commun. Syst. 33(2) (2020) - [c18]Aishwarya Manjunath, Vaskar Raychoudhury, Snehanshu Saha:
Ant-Taxi to Pie-Passenger: Optimizing Routes and Time for Distributed Taxi Ride Sharing. COMSNETS 2020: 736-741 - [c17]Snehanshu Saha, Tejas Prashanth, Suraj Aralihalli, Sumedh Basarkod, T. S. B. Sudarshan, Soma S. Dhavala:
LALR: Theoretical and Experimental validation of Lipschitz Adaptive Learning Rate in Regression and Neural Networks. IJCNN 2020: 1-8 - [c16]Shailesh Sridhar, Snehanshu Saha, Azhar Shaikh, Rahul Yedida, Sriparna Saha:
Parsimonious Computing: A Minority Training Regime for Effective Prediction in Large Microarray Expression Data Sets. IJCNN 2020: 1-8 - [c15]Shrawani Silwal, Vaskar Raychoudhury, Snehanshu Saha, Md. Osman Gani:
A Dynamic Taxi Ride Sharing System Using Particle Swarm Optimization. MASS 2020: 112-120 - [i27]Shailesh Sridhar, Snehanshu Saha, Azhar Shaikh, Rahul Yedida, Sriparna Saha:
Parsimonious Computing: A Minority Training Regime for Effective Prediction in Large Microarray Expression Data Sets. CoRR abs/2005.08442 (2020) - [i26]Rohan Mohapatra, Snehanshu Saha, Soma S. Dhavala:
AdaSwarm: A Novel PSO optimization Method for the Mathematical Equivalence of Error Gradients. CoRR abs/2006.09875 (2020) - [i25]Snehanshu Saha, Tejas Prashanth, Suraj Aralihalli, Sumedh Basarkod, T. S. B. Sudarshan, Soma S. Dhavala:
LALR: Theoretical and Experimental validation of Lipschitz Adaptive Learning Rate in Regression and Neural Networks. CoRR abs/2006.13307 (2020) - [i24]Anwesh Bhattacharya, Snehanshu Saha, Mousumi Das:
Detection of Double-Nuclei Galaxies in SDSS. CoRR abs/2011.12177 (2020)
2010 – 2019
- 2019
- [j19]Simran Makhija, Snehanshu Saha, Suryoday Basak, M. Das:
Separating stars from quasars: Machine learning investigation using photometric data. Astron. Comput. 29: 100313 (2019) - [j18]Archana Mathur, Snehanshu Saha, Poulami Sarkar, Saibal Kar, Suryoday Basak:
Time Reversed Delay Differential Equation Based Modeling of Journal Influence in An Emerging Area. J. Integr. Des. Process. Sci. 23(3): 43-71 (2019) - [j17]Snehanshu Saha, Saibal Kar:
Special Issue on Machine Learning in Scientometrics. J. Sci. Res. 8(2s): s1 (2019) - [j16]Archana Mathur, Snehanshu Saha, Saibal Kar, Gouri Ginde, Ankit Sinha:
SES-RREF: The Machine Learning Approach to Credible Metrics of Scholastic Evidence via Recursive Referencing. J. Sci. Res. 8(2s): s44-s73 (2019) - [j15]Bidisha Goswami, Jyotirmoy Sarkar, Snehanshu Saha, Saibal Kar, Poulami Sarkar:
ALVEC: Auto-scaling by Lotka Volterra elastic cloud: A QoS aware non linear dynamical allocation model. Simul. Model. Pract. Theory 93: 262-292 (2019) - [c14]Sumana Sinha, Snehanshu Saha, Sudeepta Mishra:
COR-HR: an efficient hybrid routing approach using coefficient of restitution in MANET. ICDCN 2019: 455-459 - [i23]Rahul Yedida, Snehanshu Saha:
A novel adaptive learning rate scheduler for deep neural networks. CoRR abs/1902.07399 (2019) - [i22]Snehanshu Saha, Nithin Nagaraj, Archana Mathur, Rahul Yedida:
Evolution of Novel Activation Functions in Neural Network Training with Applications to Classification of Exoplanets. CoRR abs/1906.01975 (2019) - [i21]Harikrishnan Nellippallil Balakrishnan, Aditi Kathpalia, Snehanshu Saha, Nithin Nagaraj:
ChaosNet: A Chaos based Artificial Neural Network Architecture for Classification. CoRR abs/1910.02423 (2019) - 2018
- [j14]Snehanshu Saha, Suryoday Basak, Margarita Safonova, Kakoli Bora, Surbhi Agrawal, Poulami Sarkar, Jayant Murthy:
Theoretical validation of potential habitability via analytical and boosted tree methods: An optimistic study on recently discovered exoplanets. Astron. Comput. 23: 141-150 (2018) - [j13]Jyotirmoy Sarkar, Bidisha Goswami, Snehanshu Saha, Saibal Kar:
CD-SFA: stochastic frontier analysis approach to revenue modelling in large cloud data centres. Int. J. Commun. Networks Distributed Syst. 21(3): 315-345 (2018) - [j12]Sobin C. C., Vaskar Raychoudhury, Snehanshu Saha:
Addressing space-constraint driven selfishness in smart opportunistic environment. Int. J. Commun. Syst. 31(14) (2018) - [j11]Snehanshu Saha, Poulami Sarkar, Archana Mathur, Suryoday Basak:
Model Visualization in Understanding Rapid Growth of a Journal in an Emerging Area. J. Sci. Res. 7(1): 48-53 (2018) - [j10]Gouri Ginde, Snehanshu Saha, Archana Mathur, Harsha Vamsi, Sudeepa Roy Dey, Swati Sampatrao Gambhire:
Use of NoSQL Database and Visualization Techniques to Analyze Massive Scholarly Article Data from Journals. J. Sci. Res. 7(2): 114-119 (2018) - [j9]Sandra Anil, Abu Kurian, Sudeepa Roy Dey, Snehanshu Saha, Ankit Sinha:
Genealogy Tree: Understanding Academic Lineage of Authors via Algorithmic and Visual Analysis. J. Sci. Res. 7(2): 120-124 (2018) - [c13]Snehanshu Saha, Archana Mathur, Kakoli Bora, Suryoday Basak, Surbhi Agrawal:
A New Activation Function for Artificial Neural Net Based Habitability Classification. ICACCI 2018: 1781-1786 - [c12]Manikandan. R, Krishna Madgula, Snehanshu Saha:
TeamDL at SemEval-2018 Task 8: Cybersecurity Text Analysis using Convolutional Neural Network and Conditional Random Fields. SemEval@NAACL-HLT 2018: 868-873 - [c11]Abhijit Theophilus, Snehanshu Saha, Suryoday Basak, Jayant Murthy:
A Novel Exoplanetary Habitability Score via Particle Swarm Optimization of CES Production Functions. SSCI 2018: 2139-2147 - [i20]Sandra Anil, Abu Kurian, Sudeepa Roy Dey, Snehanshu Saha, Ankit Sinha:
Genealogy tree: understanding academic lineage of authors via algorithmic and visual analysis. CoRR abs/1803.02352 (2018) - [i19]Snehanshu Saha, Poulami Sarkar, Archana Mathur, Suryoday Basak:
Model Visualization in understanding rapid growth of a journal in an emerging area. CoRR abs/1803.04644 (2018) - [i18]Mohammed Viquar, Suryoday Basak, Ariruna Dasgupta, Surbhi Agrawal, Snehanshu Saha:
Machine Learning in Astronomy: A Case Study in Quasar-Star Classification. CoRR abs/1804.05051 (2018) - [i17]Gouri Ginde, Snehanshu Saha, Archana Mathur, Harsha Vamsi, Sudeepa Roy Dey, Swati Sampatrao Gambhire:
Use of NoSQL database and visualization techniques to analyze massive scholarly article data from journals. CoRR abs/1805.00390 (2018) - [i16]Poulami Sarkar, Snehanshu Saha, Archana Mathur, Rahul Aedula, Saibal Kar, Surbhi Agrawal, Kakoli Bora:
Time Reversed Delay Differential Equation Based Modeling Of Journal Influence In An Emerging Area. CoRR abs/1805.03558 (2018) - [i15]Bidisha Goswami, Jyotirmoy Sarkar, Snehanshu Saha, Saibal Kar, Poulami Sarkar:
ALVEC: Auto-scaling by Lotka Volterra Elastic Cloud: A QoS aware Non Linear Dynamical Allocation Model. CoRR abs/1805.07356 (2018) - [i14]Snehanshu Saha, Archana Mathur, Kakoli Bora, Surbhi Agrawal, Suryoday Basak:
SBAF: A New Activation Function for Artificial Neural Net based Habitability Classification. CoRR abs/1806.01844 (2018) - 2017
- [j8]Sobin C. C., Vaskar Raychoudhury, Snehanshu Saha:
An Incentive-Based Scheme for Mitigating Node Selfishness in Smart Opportunistic Mobile Networks. Wirel. Pers. Commun. 96(3): 3533-3551 (2017) - [c10]Sobin C. C., Vaskar Raychoudhury, Snehanshu Saha:
An Energy-efficient and Buffer-aware Routing Protocol for Opportunistic Smart Traffic Management. ICDCN 2017: 25 - [c9]Gambhire Swati Sampatrao, Sudeepa Roy Dey, Bidisha Goswami, Sai Prasanna M. S, Snehanshu Saha:
A study of revenue cost dynamics in large data centers: a factorial design approach. ICC 2017: 155:1-155:14 - [c8]Anisha R. Yarlapati, Sudeepa Roy Dey, Snehanshu Saha:
Early Prediction of LBW Cases via Minimum Error Rate Classifier: A Statistical Machine Learning Approach. SMARTCOMP 2017: 1-6 - 2016
- [j7]Kakoli Bora, Snehanshu Saha, Surbhi Agrawal, Margarita Safonova, Swati Routh, Anand M. Narasimhamurthy:
CD-HPF: New habitability score via data analytic modeling. Astron. Comput. 17: 129-143 (2016) - [j6]Snehanshu Saha, Jyotirmoy Sarkar, Avantika Dwivedi, Nandita Dwivedi, Anand M. Narasimhamurthy, Ranjan Roy:
A novel revenue optimization model to address the operation and maintenance cost of a data center. J. Cloud Comput. 5: 1 (2016) - [j5]Snehanshu Saha, Jyotirmoy Sarkar, Avantika Dwivedi, Nandita Dwivedi, Anand M. Narasimhamurthy, Ranjan Roy, Shrisha Rao:
Erratum to: A novel revenue optimization model to address the operation and maintenance cost of a data center. J. Cloud Comput. 5: 13 (2016) - [j4]Gouri Ginde, Snehanshu Saha, Archana Mathur, Sukrit Venkatagiri, Sujith Vadakkepat, Anand M. Narasimhamurthy, B. S. Daya Sagar:
ScientoBASE: a framework and model for computing scholastic indicators of non-local influence of journals via native data acquisition algorithms. Scientometrics 108(3): 1479-1529 (2016) - [c7]Bhoomika Agarwal, Abhiram Ravikumar, Snehanshu Saha:
A Novel Approach to Big Data Veracity using Crowdsourcing Techniques and Bayesian Predictors. COMPUTE 2016: 153-160 - [c6]Bhoomika Agarwal, Abhiram Ravikumar, Snehanshu Saha:
A Novel Approach to Big Data Veracity Using Crowdsourcing Techniques and Bayesian Predictors. ICMLA 2016: 1020-1023 - [p2]Kusuma Mohanchandra, Snehanshu Saha, K. Srikanta Murthy:
Evidence of Chaos in EEG Signals: An Application to BCI. Advances in Chaos Theory and Intelligent Control 2016: 609-625 - [i13]Snehanshu Saha, Neelam Jangid, Archana Mathur, M. N. Anand:
DSRS: Estimation and Forecasting of Journal Influence in the Science and Technology Domain via a Lightweight Quantitative Approach. CoRR abs/1604.03215 (2016) - [i12]Luckyson Khaidem, Snehanshu Saha, Sudeepa Roy Dey:
Predicting the direction of stock market prices using random forest. CoRR abs/1605.00003 (2016) - [i11]Gouri Ginde, Snehanshu Saha, Archana Mathur, Sukrit Venkatagiri, Sujith Vadakkepat, Anand M. Narasimhamurthy, B. S. Daya Sagar:
ScientoBASE: A Framework and Model for Computing Scholastic Indicators of non-local influence of Journals via Native Data Acquisition algorithms. CoRR abs/1605.01821 (2016) - [i10]Sobin C. C., Snehanshu Saha, Vaskar Raychoudhury, Hategekimana Fidele, Sumana Sinha:
CISER: An Amoebiasis inspired Model for Epidemic Message Propagation in DTN. CoRR abs/1608.07670 (2016) - [i9]Gambhire Swati Sampatrao, Sudeepa Roy Dey, Bidisha Goswami, Sai Prasanna M. S, Snehanshu Saha:
A Study of Revenue Cost Dynamics in Large Data Centers: A Factorial Design Approach. CoRR abs/1610.00024 (2016) - [i8]Jyotirmoy Sarkar, Bidisha Goswami, Snehanshu Saha, Saibal Kar:
CDSFA Stochastic Frontier Analysis Approach to Revenue Modeling in Large Cloud Data Centers. CoRR abs/1610.00624 (2016) - 2015
- [j3]Sarasvathi V., Snehanshu Saha, N. Ch. S. N. Iyengar, Mahalaxmi Koti:
Coefficient of Restitution based Cross Layer Interference Aware Routing Protocol in Wireless Mesh Networks. Int. J. Commun. Networks Inf. Secur. 7(3) (2015) - [j2]Kusuma Mohanchandra, Snehanshu Saha, K. Srikanta Murthy, G. M. Lingaraju:
Distinct adoption of k-nearest neighbour and support vector machine in classifying EEG signals of mental tasks. Int. J. Intell. Eng. Informatics 3(4): 313-329 (2015) - [c5]Neelam Jangid, Snehanshu Saha, Anand M. Narasimhamurthy, Archana Mathur:
Computing the Prestige of a journal: A Revised Multiple Linear Regression Approach. WCI 2015: 1-4 - [c4]Snehanshu Saha, Bhoomika Agarwal, Priyal Mehta:
Teaching Advanced Algebra to Engineering Majors: Dealing with the classroom challenges. WCI 2015: 155-162 - [p1]Kusuma Mohanchandra, Snehanshu Saha, G. M. Lingaraju:
EEG Based Brain Computer Interface for Speech Communication: Principles and Applications. Brain-Computer Interfaces 2015: 273-293 - [i7]Sarasvathi V., N. Ch. S. N. Iyengar, Snehanshu Saha:
QoS Guaranteed Intelligent Routing Using Hybrid PSO-GA in Wireless Mesh Networks. CoRR abs/1503.03639 (2015) - [i6]G. Arun Kumar, Snehanshu Saha, Aravind Sundaresan, Bidisha Goswami:
A QoS aware Novel Probabilistic strategy for Dynamic Resource Allocation. CoRR abs/1503.07038 (2015) - [i5]Snehanshu Saha, Surbhi Agrawal, Manikandan. R, Kakoli Bora, Swati Routh, Anand M. Narasimhamurthy:
ASTROMLSKIT: A New Statistical Machine Learning Toolkit: A Platform for Data Analytics in Astronomy. CoRR abs/1504.07865 (2015) - [i4]Sarasvathi V., Snehanshu Saha, N. Ch. S. N. Iyengar, Mahalaxmi Koti:
Coefficient of Restitution based Cross Layer Interference Aware Routing Protocol in Wireless Mesh Networks. CoRR abs/1511.04536 (2015) - 2014
- [j1]Sarasvathi V., N. Ch. S. N. Iyengar, Snehanshu Saha:
An Efficient Interference Aware Partially Overlapping Channel Assignment and Routing in Wireless Mesh Networks. Int. J. Commun. Networks Inf. Secur. 6(1) (2014) - [c3]Mushtaque Ahamed A, Snehanshu Saha:
Estimating the number of Prime numbers less than a given positive integer by a novel quadrature method: A study of Accuracy and Convergence. ICACCI 2014: 415-421 - [c2]Roopa T. P, Surbhi Agrawal, Snehanshu Saha:
An enhancement to CloudSim via distributed data storage. ICACCI 2014: 2316-2322 - 2013
- [c1]Kishore Venkateshan, Arvind Shekar, Snehanshu Saha:
Baseball hand tracking from monocular video. ICACCI 2013: 953-961 - [i3]Sarasvathi V., N. Ch. S. N. Iyengar, Snehanshu Saha:
Interference Aware Channel Assignmnet Using Edge Coloring in Multi-Channel Multi-Radio Wireless Mesh Networks. CoRR abs/1305.0866 (2013) - [i2]Snehanshu Saha, Bidisha Goswami, Surbhi Agrawal:
Modeling Vanilla Option prices: A simulation study by an implicit method. CoRR abs/1311.0438 (2013) - [i1]Snehanshu Saha, Bidisha Goswami, Alexander Ngenzi, Aquila Khanam:
A Randomized Generic Lucas Seed Algorithm (RGLSA) with Tail Boosting for Threat Modeling in Virtual Machines. CoRR abs/1311.6566 (2013)
Coauthor Index
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