Snehasis Mukhopadhyay

Publication Activity (10 Years)

Years Active: 1989-2023
Publications (10 Years): 22

Top Topics

Spatially Invariant

Reinforcement Learning

Top Venues

Publications

Sabrina Chowdhury, Snehasis Mukhopadhyay, Kumpati S. Narendra
Mutual Learning Algorithm for Kidney Cyst, Kidney Tumor and Kidney Stone Diagnosis. FedCSIS (2023)
Sabrina Tarin Chowdhury, Snehasis Mukhopadhyay, Kumpati S. Narendra
Mutual Learning for Pattern Recognition. SMC (2023)
Karen D'Souza, Lin Zhu, Pratibha Varma-Nelson, Shiaofen Fang, Snehasis Mukhopadhyay
AI-Augmented Peer Led Team Learning for STEM Education. SACI (2023)
Karen D'Souza, Pratibha Varma-Nelson, Shiaofen Fang, Snehasis Mukhopadhyay
Monitoring Cyber Peer-Led Team Learning: A Multimodal Human-in-the-loop Approach. HITLAML (2023)
Kumpati S. Narendra, Snehasis Mukhopadhyay, Kasra Esfandiari
Mutual Learning in Optimization. SMC (2022)
Hao Wang, Snehasis Mukhopadhyay, Yunyu Xiao, Shiaofen Fang
An Interactive Approach to Bias Mitigation in Machine Learning. ICCI*CC (2021)
Cameron Reid, Snehasis Mukhopadhyay
Mutual Reinforcement Learning with Heterogenous Agents. SMARTCOMP (2021)
Kumpati S. Narendra, Snehasis Mukhopadhyay
Mutual Learning: Part II -Reinforcement Learning. ACC (2020)
Meghna Babbar-Sebens, Kenneth R. Cannady-Shultz, Snehasis Mukhopadhyay
Interactive Watershed Optimization in the Presence of Spatially-varying and Uncertain Stakeholder Preferences. ICHMS (2020)
Kumpati S. Narendra, Snehasis Mukhopadhyay
Mutual Learning: Part I - Learning Automata. ACC (2019)
Andrew Hoblitzell, Meghna Babbar-Sebens, Snehasis Mukhopadhyay
Non-Stationary Reinforcement-Learning Based Dimensionality Reduction for Multi-objective Optimization of Wetland Design. ICRAI (2019)
Thanh Nguyen, Snehasis Mukhopadhyay, Meghna Babbar-Sebens
Why the 'selfish' optimizing agents could solve the decentralized reinforcement learning problems. AI Commun. 32 (2) (2019)
Snehasis Mukhopadhyay, Omkar J. Tilak, Subir Chakrabarti
Reinforcement Learning Algorithms for Uncertain, Dynamic, Zero-Sum Games. ICMLA (2018)
Huang Li, Shiaofen Fang, Snehasis Mukhopadhyay, Andrew J. Saykin, Li Shen
Interactive Machine Learning by Visualization: A Small Data Solution. IEEE BigData (2018)
Andrew Hoblitzell, Meghna Babbar-Sebens, Snehasis Mukhopadhyay
Uncertainty-Based Deep Learning Networks for Limited Data Wetland User Models. AIVR (2018)
Andrew Hoblitzell, Meghna Babbar-Sebens, Snehasis Mukhopadhyay
Machine Learning with Small Data for User Modeling of Watershed Stakeholders Engaged in Interactive Optimization. CSAI/ICIMT (2018)
Thanh Nguyen, Snehasis Mukhopadhyay
Two-phase selective decentralization to improve reinforcement learning systems with MDP. AI Commun. 31 (4) (2018)
Thanh Nguyen, Snehasis Mukhopadhyay
Selectively decentralized Q-learning. SMC (2017)
Thanh Nguyen, Snehasis Mukhopadhyay
Multidisciplinary Optimization in Decentralized Reinforcement Learning. ICMLA (2017)
Kumpati S. Narendra, Yu Wang, Snehasis Mukhopadhyay
Fast Reinforcement Learning using multiple models. CDC (2016)
Andrew Hoblitzell, Meghna Babbar-Sebens, Snehasis Mukhopadhyay
Fuzzy and deep learning approaches for user modeling in wetland design. SMC (2016)
Thanh Nguyen, Snehasis Mukhopadhyay
Identification and optimal control of large-scale systems using selective decentralization. SMC (2016)
Meghna Babbar-Sebens, Snehasis Mukhopadhyay, Vidya Bhushan Singh, Adriana Debora Piemonti
A web-based software tool for participatory optimization of conservation practices in watersheds. Environ. Model. Softw. 69 (2015)
Snehasis Mukhopadhyay, Vidya Bhushan Singh, Meghna Babbar-Sebens
User modeling with limited data: Application to stakeholder-driven watershed design. SMC (2014)
Vidya Bhushan Singh, Snehasis Mukhopadhyay, Meghna Babbar-Sebens
User Modelling for Interactive Optimization Using Neural Network. SMC (2013)
Mansurul Bhuiyan, Snehasis Mukhopadhyay, Mohammad Al Hasan
Interactive pattern mining on hidden data: a sampling-based solution. CIKM (2012)
Vidya Bhushan Singh, Snehasis Mukhopadhyay, Meghna Babbar-Sebens
Decentralized pursuit learning automata in batch mode. SCIS&ISIS (2012)
Omkar J. Tilak, Meghna Babbar-Sebens, Snehasis Mukhopadhyay
Decentralized and partially decentralized reinforcement learning for designing a distributed wetland system in watersheds. SMC (2011)
Omkar J. Tilak, Ryan Martin, Snehasis Mukhopadhyay
Decentralized Indirect Methods for Learning Automata Games. IEEE Trans. Syst. Man Cybern. Part B 41 (5) (2011)
Omkar J. Tilak, Andrew Hoblitzell, Snehasis Mukhopadhyay, Qian You, Shiaofen Fang, Yuni Xia, Joseph Bidwell
Multilevel text mining for bone biology. Concurr. Comput. Pract. Exp. 23 (17) (2011)
Omkar J. Tilak, Snehasis Mukhopadhyay
Partially decentralized reinforcement learning in finite, multi-agent Markov decision processes. AI Commun. 24 (4) (2011)
Omkar J. Tilak, Snehasis Mukhopadhyay
Decentralized and Partially Decentralized Reinforcement Learning for Distributed Combinatorial Optimization Problems. ICMLA (2010)
Kumpati S. Narendra, Snehasis Mukhopadhyay
To communicate or not to communicate: A decision-theoretic approach to decentralized adaptive control. ACC (2010)
Rajeev R. Raje, Snehasis Mukhopadhyay, Sucheta Phatak, Rashmi Shastri, Lahiru S. Gallege
Software Service Selection by Multi-level Matching and Reinforcement Learning. BIONETICS (2010)
Snehasis Mukhopadhyay, Mathew J. Palakal, Kalyan Maddu
Multi-way association extraction and visualization from biological text documents using hyper-graphs: Applications to genetic association studies for diseases. Artif. Intell. Medicine 49 (3) (2010)
Andrew Hoblitzell, Snehasis Mukhopadhyay, Qian You, Shiaofen Fang, Yuni Xia, Joseph Bidwell
Text mining for bone biology. HPDC (2010)
Omkar J. Tilak, Snehasis Mukhopadhyay, Mihran Tuceryan, Rajeev R. Raje
A novel reinforcement learning framework for sensor subset selection. ICNSC (2010)
Bi-Hua Cheng, Harsha Gopal Goud Vaka, Snehasis Mukhopadhyay
A Genetic Association Study between Breast Cancer and Osteoporosis Using Transitive Text Mining. BIBM (2009)
Meghna Babbar-Sebens, Snehasis Mukhopadhyay
Reinforcement Learning for Human-Machine Collaborative Optimization: Application in Ground Water Monitoring. SMC (2009)
Qian You, Shiaofen Fang, Snehasis Mukhopadhyay, Harsha Gopal Goud Vaka, Jake Yue Chen
Visualizing a Correlative Multi-level Graph of Biology Entity Interactions. NBiS (2009)
Snehasis Mukhopadhyay, Shengquan Peng, Rajeev R. Raje, Mathew J. Palakal, Javed Mostafa
Comparison of Some Single-agent and Multi-agent Information Filtering Systems on a Benchmark Text Data Set. SEKE (2009)
Harsha Gopal Goud Vaka, Snehasis Mukhopadhyay
Knowledge Extraction and Extrapolation Using Ancient and Modern Biomedical Literature. AINA Workshops (2009)
Harsha Gopal Goud Vaka, Snehasis Mukhopadhyay
Hypotheses Generation Pertaining to Ayurveda Using Automated Vocabulary Generation and Transitive Text Mining. NBiS (2009)
Snehasis Mukhopadhyay, Niranjan Jayadevaprakash
Automated Metadata Generation and its Application to Biological Association Extraction. AINA Workshops (2008)
Snehasis Mukhopadhyay, Mathew J. Palakal, Kalyan Maddu
Multi-way Association Extraction from Biological Text Documents Using Hyper-Graphs. BIBM (2008)
Niranjan Jayadevaprakash, Snehasis Mukhopadhyay, Mathew J. Palakal
Generating association graphs of non-cooccurring text objects using transitive methods. SAC (2005)
Snehasis Mukhopadhyay, Shengquan Peng, Rajeev R. Raje, Javed Mostafa, Mathew J. Palakal
Distributed multi-agent information filtering - A comparative study. J. Assoc. Inf. Sci. Technol. 56 (8) (2005)
Pooja Bajracharya, Snehasis Mukhopadhyay
A learning approach to the database selection problem in the presence of dynamic user interests and database contents. ASIST (2004)
Kamal Kumar, Mathew J. Palakal, Snehasis Mukhopadhyay, Matthew J. Stephens, Huian Li
BioMap: toward the development of a knowledge base of biomedical literature. SAC (2004)
Rajeev R. Raje, Daocheng Zhu, Snehasis Mukhopadhyay, Liying Tang, Mathew J. Palakal, Javed Mostafa
COBioSIFTER - A CORBA-Based Distributed Multi-Agent Biological Information Management System. Clust. Comput. 7 (4) (2004)
Javed Mostafa, Snehasis Mukhopadhyay, Mathew J. Palakal
Simulation Studies of Different Dimensions of Users' Interests and their Impact on User Modeling and Information Filtering. Inf. Retr. 6 (2) (2003)
Snehasis Mukhopadhyay, Changhong Tang, Jeffrey Huang, Mathew J. Palakal
Genetic Sequence Classification and its Application to Cross-Species Homology Detection. J. VLSI Signal Process. 35 (3) (2003)
Mathew J. Palakal, Matthew J. Stephens, Snehasis Mukhopadhyay, Rajeev R. Raje, Simon Rhodes
Identification of Biological Relationships from Text Documentsusing Efficient Computational Methods. J. Bioinform. Comput. Biol. 1 (2) (2003)
Snehasis Mukhopadhyay, Shengquan Peng, Rajeev R. Raje, Mathew J. Palakal, Javed Mostafa
Multi-agent information classification using dynamic acquaintance lists. J. Assoc. Inf. Sci. Technol. 54 (10) (2003)
Snehasis Mukhopadhyay
Neural and adaptive systems: fundamentals through simulations: José C. Principe, Neil R. Euliano and W. Curt Lefebvre; John Wiley & Sons, Inc., USA, 2000, ISBN 0-471-35167-9. Autom. 39 (7) (2003)
Joby Varghese, Snehasis Mukhopadhyay
Automated Web navigation using multiagent adaptive dynamic programming. IEEE Trans. Syst. Man Cybern. Part A 33 (3) (2003)
Haiying Wang, Snehasis Mukhopadhyay, Shiaofen Fang
Feature Decomposition Architectures for Neural Networks: Algorithms, Error Bounds, and Applications. Int. J. Neural Syst. 12 (1) (2002)
Yueyu Fu, Travis Bauer, Javed Mostafa, Mathew J. Palakal, Snehasis Mukhopadhyay
Concept extraction and association from cancer literature. WIDM (2002)
Rajeev R. Raje, Mingyong Qiao, Snehasis Mukhopadhyay, Mathew J. Palakal, Shengquan Peng, Javed Mostafa
Homogeneous Agent-Based Distributed Information Filtering. Clust. Comput. 5 (4) (2002)
Mathew J. Palakal, Snehasis Mukhopadhyay, Javed Mostafa, Rajeev R. Raje, Mathias N'Cho, Santosh Mishra
An intelligent biological information management system. Bioinform. 18 (10) (2002)
Mathew J. Palakal, Snehasis Mukhopadhyay, Javed Mostafa
An intelligent biological information management system. SAC (2002)
Mathew J. Palakal, Matthew J. Stephens, Snehasis Mukhopadhyay, Rajeev R. Raje, Simon Rhodes
A Multi-Level Text Mining Method to Extract Biological Relationships. CSB (2002)
Snehasis Mukhopadhyay, Changhong Tang, Jeffrey Huang, Mulong Yu, Mathew J. Palakal
A comparative study of genetic sequence classification algorithms. NNSP (2002)
Matthew J. Stephens, Mathew J. Palakal, Snehasis Mukhopadhyay, Rajeev R. Raje, Javed Mostafa
Detecting Gene Relations from MEDLINE Abstracts. Pacific Symposium on Biocomputing (2001)
Shengquan Peng, Snehasis Mukhopadhyay, Rajeev R. Raje, Mathew J. Palakal, Javed Mostafa
A Comparison Between Single-agent and Multi-agent Classification of Documents. IPDPS (2001)
Rajeev R. Raje, Mingyong Qiao, Snehasis Mukhopadhyay
SIFTER-II: a heterogeneous agent society for information filtering. SAC (2001)
Snehasis Mukhopadhyay, Joby Varghese
Multi-agent Adaptive Dynamic Programming. MICAI (2000)
Rajeev R. Raje, Snehasis Mukhopadhyay, Michael Boyles, Nila Patel, Artur Papiez
On designing and implementing a collaborative system using the distributed-object model of Java-RMI. Scalable Comput. Pract. Exp. 1 (4) (1998)
Michael Boyles, Javed Mostafa, Snehasis Mukhopadhyay, Mathew J. Palakal, Artur Papiez, Nila Patel, Rajeev R. Raje
A Bidding Mechanism for Web-Based Agents Involved in Information Classification. World Wide Web 1 (3) (1998)
Javed Mostafa, Snehasis Mukhopadhyay, Wai Lam, Mathew J. Palakal
A Multilevel Approach to Intelligent Information Filtering: Model, System, and Evaluation. ACM Trans. Inf. Syst. 15 (4) (1997)
Kumpati S. Narendra, Snehasis Mukhopadhyay
Adaptive control using neural networks and approximate models. IEEE Trans. Neural Networks 8 (3) (1997)
Wai Lam, Snehasis Mukhopadhyay, Javed Mostafa, Mathew J. Palakal
Detection of Shifts in User Interests for Personalized Information Filtering. SIGIR (1996)
Wai Lam, Snehasis Mukhopadhyay
A Two-Level Approach to Learning in Nonstationary Environments. Canadian Conference on AI (1996)
Kumpati S. Narendra, Snehasis Mukhopadhyay
Adaptive control of nonlinear multivariable systems using neural networks. Neural Networks 7 (5) (1994)
Snehasis Mukhopadhyay, Kumpati S. Narendra
Disturbance rejection in nonlinear systems using neural networks. IEEE Trans. Neural Networks 4 (1) (1993)
Kumpati S. Narendra, Snehasis Mukhopadhyay
Associative learning in random environments using neural networks. IEEE Trans. Neural Networks 2 (1) (1991)
Vladimir J. Lumelsky, Snehasis Mukhopadhyay, Kang Sun
Dynamic path planning in sensor-based terrain acquisition. IEEE Trans. Robotics Autom. 6 (4) (1990)
Vladimir J. Lumelsky, Snehasis Mukhopadhyay, Kang Sun
Sensor-Based Terrain Acquisition: a "Seed Spreader" Strategy. IROS (1989)
Snehasis Mukhopadhyay, M. A. L. Thathachar
Associative learning of Boolean functions. IEEE Trans. Syst. Man Cybern. 19 (5) (1989)