Snehasis Mukhopadhyay

Mansurul Bhuiyan, Snehasis Mukhopadhyay, Mohammad Al Hasan: Interactive pattern mining on hidden data: a sampling-based solution. CIKM 2012: 95-104

Omkar J. Tilak, Snehasis Mukhopadhyay: Partially decentralized reinforcement learning in finite, multi-agent Markov decision processes. AI Commun. 24(4): 293-309 (2011)

Omkar J. Tilak, Andrew Hoblitzell, Snehasis Mukhopadhyay, Qian You, Shiaofen Fang, Yuni Xia, Joseph Bidwell: Multilevel text mining for bone biology. Concurrency and Computation: Practice and Experience 23(17): 2355-2364 (2011)

Omkar J. Tilak, Ryan Martin, Snehasis Mukhopadhyay: Decentralized Indirect Methods for Learning Automata Games. IEEE Transactions on Systems, Man, and Cybernetics, Part B 41(5): 1213-1223 (2011)

Omkar J. Tilak, Meghna Babbar-Sebens, Snehasis Mukhopadhyay: Decentralized and partially decentralized reinforcement learning for designing a distributed wetland system in watersheds. SMC 2011: 271-276

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. Artificial Intelligence in Medicine 49(3): 145-154 (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: 310-324

Andrew Hoblitzell, Snehasis Mukhopadhyay, Qian You, Shiaofen Fang, Yuni Xia, Joseph Bidwell: Text mining for bone biology. HPDC 2010: 522-530

Omkar J. Tilak, Snehasis Mukhopadhyay: Decentralized and Partially Decentralized Reinforcement Learning for Distributed Combinatorial Optimization Problems. ICMLA 2010: 389-394

Omkar J. Tilak, Snehasis Mukhopadhyay, Mihran Tuceryan, Rajeev R. Raje: A novel reinforcement learning framework for sensor subset selection. ICNSC 2010: 95-100

Harsha Gopal Goud Vaka, Snehasis Mukhopadhyay: Knowledge Extraction and Extrapolation Using Ancient and Modern Biomedical Literature. AINA Workshops 2009: 996-1001

Bi-Hua Cheng, Harsha Gopal Goud Vaka, Snehasis Mukhopadhyay: A Genetic Association Study between Breast Cancer and Osteoporosis Using Transitive Text Mining. BIBM 2009: 411-414

Harsha Gopal Goud Vaka, Snehasis Mukhopadhyay: Hypotheses Generation Pertaining to Ayurveda Using Automated Vocabulary Generation and Transitive Text Mining. NBiS 2009: 200-205

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: 304-309

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: 185-188

Meghna Babbar-Sebens, Snehasis Mukhopadhyay: Reinforcement Learning for Human-Machine Collaborative Optimization: Application in Ground Water Monitoring. SMC 2009: 3563-3568

Snehasis Mukhopadhyay, Niranjan Jayadevaprakash: Automated Metadata Generation and its Application to Biological Association Extraction. AINA Workshops 2008: 708-713

Snehasis Mukhopadhyay, Mathew J. Palakal, Kalyan Maddu: Multi-way Association Extraction from Biological Text Documents Using Hyper-Graphs. BIBM 2008: 257-262

Snehasis Mukhopadhyay, Shengquan Peng, Rajeev R. Raje, Javed Mostafa, Mathew J. Palakal: Distributed multi-agent information filtering - A comparative study. JASIST 56(8): 834-842 (2005)

Niranjan Jayadevaprakash, Snehasis Mukhopadhyay, Mathew J. Palakal: Generating association graphs of non-cooccurring text objects using transitive methods. SAC 2005: 141-145

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. Cluster Computing 7(4): 373-389 (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: 121-127

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. Automatica 39(7): 1313-1315 (2003)

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): 199-223 (2003)

Snehasis Mukhopadhyay, Shengquan Peng, Rajeev R. Raje, Mathew J. Palakal, Javed Mostafa: Multi-agent information classification using dynamic acquaintance lists. JASIST 54(10): 966-975 (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. Bioinformatics and Computational Biology 1(2): 307-342 (2003)

Snehasis Mukhopadhyay, Changhong Tang, Jeffrey Huang, Mathew J. Palakal: Genetic Sequence Classification and its Application to Cross-Species Homology Detection. VLSI Signal Processing 35(3): 273-285 (2003)

Mathew J. Palakal, Snehasis Mukhopadhyay, Javed Mostafa, Rajeev R. Raje, Mathias N'Cho, Santosh Mishra: An intelligent biological information management system. Bioinformatics 18(10): 1283-1288 (2002)

Rajeev R. Raje, Mingyong Qiao, Snehasis Mukhopadhyay, Mathew J. Palakal, Shengquan Peng, Javed Mostafa: Homogeneous Agent-Based Distributed Information Filtering. Cluster Computing 5(4): 377-388 (2002)

Haiying Wang, Snehasis Mukhopadhyay, Shiaofen Fang: Feature Decomposition Architectures for Neural Networks: Algorithms, Error Bounds, and Applications. Int. J. Neural Syst. 12(1): 69-81 (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: 97-108

Mathew J. Palakal, Snehasis Mukhopadhyay, Javed Mostafa: An intelligent biological information management system. SAC 2002: 159-163

Yueyu Fu, Travis Bauer, Javed Mostafa, Mathew J. Palakal, Snehasis Mukhopadhyay: Concept extraction and association from cancer literature. WIDM 2002: 100-103

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: 90

Matthew J. Stephens, Mathew J. Palakal, Snehasis Mukhopadhyay, Rajeev R. Raje, Javed Mostafa: Detecting Gene Relations from MEDLINE Abstracts. Pacific Symposium on Biocomputing 2001: 483-496

Rajeev R. Raje, Mingyong Qiao, Snehasis Mukhopadhyay: SIFTER-II: a heterogeneous agent society for information filtering. SAC 2001: 121-123

Snehasis Mukhopadhyay, Joby Varghese: Multi-agent Adaptive Dynamic Programming. MICAI 2000: 574-585

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 Computing: Practice and Experience 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): 155-165 (1998)

Kumpati S. Narendra, Snehasis Mukhopadhyay: Adaptive control using neural networks and approximate models. IEEE Trans. Neural Netw. Learning Syst. 8(3): 475-485 (1997)

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): 368-399 (1997)

Wai Lam, Snehasis Mukhopadhyay: A Two-Level Approach to Learning in Nonstationary Environments. Canadian Conference on AI 1996: 271-283

Wai Lam, Snehasis Mukhopadhyay, Javed Mostafa, Mathew J. Palakal: Detection of Shifts in User Interests for Personalized Information Filtering. SIGIR 1996: 317-325

Kumpati S. Narendra, Snehasis Mukhopadhyay: Adaptive control of nonlinear multivariable systems using neural networks. Neural Networks 7(5): 737-752 (1994)