S. Mukhopadhyay

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Intelligent Control Using Neural Networks

Snehasis Mukhopadhyay, Kumpati S. Narendra, K. Narendra, 1991, 1991 American Control Conference.

Adaptive control of nonlinear multivariable systems using neural networks

Snehasis Mukhopadhyay, Kumpati S. Narendra, K. Narendra, 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

Mutual Learning: Part I - Learning Automata

Snehasis Mukhopadhyay, Kumpati S. Narendra, K. Narendra, 2019, 2019 American Control Conference (ACC).

Fast Reinforcement Learning using multiple models

Snehasis Mukhopadhyay, Kumpati S. Narendra, Yu Wang, 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

Adaptive control using neural networks and approximate models

Snehasis Mukhopadhyay, Kumpati S. Narendra, K. Narendra, 1997, IEEE Trans. Neural Networks.

Disturbance rejection in nonlinear systems using neural networks

Snehasis Mukhopadhyay, Kumpati S. Narendra, K. Narendra, 1993, IEEE Trans. Neural Networks.

Adaptive control of nonlinear multivariable systems using neural networks

Snehasis Mukhopadhyay, Kumpati S. Narendra, K. Narendra, 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

Adaptive control using neural networks and approximate models

Snehasis Mukhopadhyay, Kumpati S. Narendra, K. Narendra, 1995, Proceedings of 1995 American Control Conference - ACC'95.

MINER FOR HYPERGRAPHS USING OUTPUT SPACE SAMPLING

S. Fang, S. Mukhopadhyay, N. Tirupattur, 2011 .

Multi-agent Markov decision processes with limited agent communication

Snehasis Mukhopadhyay, S. Mukhopadhyay, Bindu Jain, 2001, Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206).

Mining and survey of simple sequence repeats in expressed sequence tags of dicotyledonous species.

Snehasis Mukhopadhyay, S. Mukhopadhyay, S. Kumpatla, 2005, Genome.

TransMiner : Mining Transitive Associations among Biological Objects from Medline

S. Mukhopadhyay, J. Mostafa, M. Palakal, 2003 .

An Interactive Approach to Bias Mitigation in Machine Learning

Hao Wang, S. Fang, S. Mukhopadhyay, 2021, 2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC).

Physical Parameter Estimation of Non-classically Damped Systems from Spatially Incomplete Modal Parameters

S. Mukhopadhyay, D. Ghosh, M. S. Chauhan, 2020 .

Reinforcement Learning Algorithms for Uncertain, Dynamic, Zero-Sum Games

Snehasis Mukhopadhyay, Omkar J. Tilak, Subir Chakrabarti, 2018, 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA).

Partially decentralized reinforcement learning in finite, multi-agent Markov decision processes

Snehasis Mukhopadhyay, Omkar J. Tilak, S. Mukhopadhyay, 2011, AI Commun..

Mutual Q-learning

S. Mukhopadhyay, Cameron Reid, 2020, 2020 3rd International Conference on Control and Robots (ICCR).

Mutual Learning: Part II --Reinforcement Learning

Snehasis Mukhopadhyay, Kumpati S. Narendra, K. Narendra, 2020, 2020 American Control Conference (ACC).

Automated Web navigation using multiagent adaptive dynamic programming

S. Mukhopadhyay, J. Varghese, S. Mukhopadhyay, 2003, IEEE Trans. Syst. Man Cybern. Part A.

Multi-agent Adaptive Dynamic Programming

Snehasis Mukhopadhyay, Joby Varghese, S. Mukhopadhyay, 2000, MICAI.

This is to certify that the thesis/dissertation prepared

Snehasis Mukhopadhyay, Yuni Xia, Andrew Hoblitzell, 2010 .

Generating association graphs of non-cooccurring text objects using transitive methods

Snehasis Mukhopadhyay, Mathew J. Palakal, Niranjan Jayadevaprakash, 2005, SAC '05.

COBioSIFTER – A CORBA-Based Distributed Multi-Agent Biological Information Management System

Javed Mostafa, Snehasis Mukhopadhyay, Mathew J. Palakal, 2004, Cluster Computing.

Identification of Biological Relationships from Text Documents

Snehasis Mukhopadhyay, Mathew J. Palakal, Matthew J. Stephens, 2005 .

BioMap: toward the development of a knowledge base of biomedical literature

Snehasis Mukhopadhyay, Mathew J. Palakal, Huian Li, 2004, SAC '04.

Visualizing a Correlative Multi-level Graph of Biology Entity Interactions

Shiaofen Fang, Snehasis Mukhopadhyay, Qian You, 2009, 2009 International Conference on Network-Based Information Systems.

Text Mining for Neuroscience: A Co-morbidity Case Study

Snehasis Mukhopadhyay, Christopher C. Lapish, Naveen Tirupattur, 2013 .

Interactive Machine Learning by Visualization: A Small Data Solution

Andrew J. Saykin, Huang Li, Shiaofen Fang, 2018, 2018 IEEE International Conference on Big Data (Big Data).

Decentralized and partially decentralized reinforcement learning for designing a distributed wetland system in watersheds

Meghna Babbar-Sebens, Snehasis Mukhopadhyay, Omkar J. Tilak, 2011, 2011 IEEE International Conference on Systems, Man, and Cybernetics.

Selecting an artificial neural network for efficient modeling and accurate simulation of the milling process

Snehasis Mukhopadhyay, Hazim El-Mounayri, Jorge F. Briceno, 2002 .

Intelligent control using neural networks

K.S. Narendra, S. Mukhopadhyay, K. Narendra, 1992, IEEE Control Systems.

Peer Assistant Role Models in a Graduate Computer Science Course

Evava S. Pietri, S. Mukhopadhyay, L. Ashburn-Nardo, 2021, Transactions on Computational Science and Computational Intelligence.

Uncertainty-Based Deep Learning Networks for Limited Data Wetland User Models

Andrew Hoblitzell, S. Mukhopadhyay, M. Babbar‐Sebens, 2018, 2018 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR).

Genetic Sequence Classification and its Application to Cross-Species Homology Detection

Snehasis Mukhopadhyay, Mathew J. Palakal, Jeffrey Huang, 2003, J. VLSI Signal Process..

Simulation Studies of Different Dimensions of Users' Interests and their Impact on User Modeling and Information Filtering

Javed Mostafa, Snehasis Mukhopadhyay, Mathew J. Palakal, 2003, Information Retrieval.

User modeling with limited data: Application to stakeholder-driven watershed design

Meghna Babbar-Sebens, Snehasis Mukhopadhyay, Vidya Bhushan Singh, 2014, 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Observer Design for Lipschitz Nonlinear Systems with State Dependency and Nonlinearity Distribution

R. Perla, S. Mukhopadhyay, S. Mukhopadhyay, 2005, 2005 Annual IEEE India Conference - Indicon.

A multi-level text mining method to extract biological relationships

Snehasis Mukhopadhyay, Mathew J. Palakal, Rajeev R. Raje, 2002, Proceedings. IEEE Computer Society Bioinformatics Conference.

Detecting Gene Relations from MEDLINE Abstracts

Javed Mostafa, Snehasis Mukhopadhyay, Mathew J. Palakal, 2000, Pacific Symposium on Biocomputing.

Interactive pattern mining on hidden data: a sampling-based solution

Snehasis Mukhopadhyay, Mohammad Al Hasan, Mansurul Bhuiyan, 2012, CIKM.

Fuzzy and deep learning approaches for user modeling in wetland design

Meghna Babbar-Sebens, Snehasis Mukhopadhyay, Andrew Hoblitzell, 2016, 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Exploration and Visualization of Patterns Underlying Multistakeholder Preferences in Watershed Conservation Decisions Generated by an Interactive Genetic Algorithm

Snehasis Mukhopadhyay, Mariam Guizani, Adriana Debora Piemonti, 2021, Water Resources Research.

Why the 'selfish' optimizing agents could solve the decentralized reinforcement learning problems

Meghna Babbar-Sebens, Snehasis Mukhopadhyay, Thanh Nguyen, 2019, AI Commun..

Two-phase selective decentralization to improve reinforcement learning systems with MDP

Snehasis Mukhopadhyay, Thanh Nguyen, S. Mukhopadhyay, 2018, AI Commun..

Detection of shifts in user interests for personalized information filtering

Javed Mostafa, Wai Lam, Snehasis Mukhopadhyay, 1996, SIGIR '96.

User Modeling And Personalized Optimization For Stakeholder-Driven Watershed Design

S. Mukhopadhyay, M. Babbar‐Sebens, A. Piemonti, 2014 .

State estimation in electro-hydraulic actuator using proportional integral observer

S. Mukhopadhyay, R. Perla, S. Mukhopadhyay, 2004, Proceedings of the IEEE INDICON 2004. First India Annual Conference, 2004..

TransMiner: Mining Transitive Associations among Biological Objects from Text

Snehasis Mukhopadhyay, Mathew Palakal, Vijay Narayanasamy, 2004, Journal of Biomedical Science.

AI-Augmented Peer Led Team Learning for STEM Education

S. Fang, S. Mukhopadhyay, P. Varma-Nelson, 2023, 2023 IEEE 17th International Symposium on Applied Computational Intelligence and Informatics (SACI).

Distributed multi-agent information filtering - A comparative study

Javed Mostafa, Snehasis Mukhopadhyay, Mathew J. Palakal, 2005, J. Assoc. Inf. Sci. Technol..

Decentralised adaptive control with partial communication

Kumpati S. Narendra, N. Oleng, S. Mukhopadhyay, 2006 .

Interactive genetic algorithm for user‐centered design of distributed conservation practices in a watershed: An examination of user preferences in objective space and user behavior

Meghna Babbar-Sebens, Snehasis Mukhopadhyay, Adriana Debora Piemonti, 2017 .

A bidding mechanism for Web-based agents involved in information classification

Javed Mostafa, Snehasis Mukhopadhyay, Mathew J. Palakal, 1998, World Wide Web.

Homogeneous Agent-Based Distributed Information Filtering

Javed Mostafa, Snehasis Mukhopadhyay, Mathew J. Palakal, 2002, Cluster Computing.

Text mining for bone biology

Shiaofen Fang, Snehasis Mukhopadhyay, Yuni Xia, 2010, HPDC '10.

Identification of Biological Relationships from Text Documentsusing Efficient Computational Methods

Snehasis Mukhopadhyay, Mathew J. Palakal, Rajeev R. Raje, 2003, J. Bioinform. Comput. Biol..

A web-based software tool for participatory optimization of conservation practices in watersheds

Meghna Babbar-Sebens, Snehasis Mukhopadhyay, Vidya Bhushan Singh, 2015, Environ. Model. Softw..

Decentralized Indirect Methods for Learning Automata Games

Snehasis Mukhopadhyay, Omkar J. Tilak, Ryan Martin, 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Reinforcement learning for human-machine collaborative optimization: Application in ground water monitoring

Meghna Babbar-Sebens, Snehasis Mukhopadhyay, S. Mukhopadhyay, 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

Interactive Watershed Optimization in the Presence of Spatially-varying and Uncertain Stakeholder Preferences

Meghna Babbar-Sebens, Snehasis Mukhopadhyay, Kenneth R. Cannady-Shultz, 2020, 2020 IEEE International Conference on Human-Machine Systems (ICHMS).

Multi-agent information classification using dynamic acquaintance lists

Javed Mostafa, Snehasis Mukhopadhyay, Mathew Palakal, 2003, J. Assoc. Inf. Sci. Technol..

A comparison between single-agent and multi-agent classification of documents

Javed Mostafa, Snehasis Mukhopadhyay, Mathew J. Palakal, 2001, Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 2001.

Feature Decomposition Architectures for Neural Networks: Algorithms, Error Bounds, and Applications

Haiying Wang, Shiaofen Fang, Snehasis Mukhopadhyay, 2002, Int. J. Neural Syst..

An intelligent biological information management system

Javed Mostafa, Snehasis Mukhopadhyay, Mathew J. Palakal, 2002, SAC '02.

Neural networks in control systems

Kumpati S. Narendra, S. Mukhopadhyay, K. Narendra, 1992, [1992] Proceedings of the 31st IEEE Conference on Decision and Control.