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2020 – today
- 2024
[c208]Shubham Sharma, Alan H. Gee, Jette Henderson, Joydeep Ghosh:
FASTER-CE: Fast, Sparse, Transparent, and Robust Counterfactual Explanations. AIAI (4) 2024: 183-196- [c207]Hsing-Huan Chung, Shravan Chaudhari, Yoav Wald, Xing Han, Joydeep Ghosh:
Novel Node Category Detection Under Subpopulation Shift. ECML/PKDD (4) 2024: 196-212 - [i57]Disha Makhija, Joydeep Ghosh, Yejin Kim:
Federated Learning for Estimating Heterogeneous Treatment Effects. CoRR abs/2402.17705 (2024) - [i56]Song Wang, Yiliang Zhou, Ziqiang Han, Cui Tao, Yunyu Xiao, Ying Ding, Joydeep Ghosh, Yifan Peng:
Uncovering Misattributed Suicide Causes through Annotation Inconsistency Detection in Death Investigation Notes. CoRR abs/2403.19432 (2024) - [i55]Hsing-Huan Chung, Shravan Chaudhari, Yoav Wald, Xing Han, Joydeep Ghosh:
Novel Node Category Detection Under Subpopulation Shift. CoRR abs/2404.01216 (2024) - [i54]Avinab Saha, Shashank Gupta, Sravan Kumar Ankireddy, Karl Chahine, Joydeep Ghosh:
Exploring Explainability in Video Action Recognition. CoRR abs/2404.09067 (2024) - [i53]Vijay Lingam, Atula Tejaswi, Aditya Vavre, Aneesh Shetty, Gautham Krishna Gudur, Joydeep Ghosh, Alex Dimakis, Eunsol Choi, Aleksandar Bojchevski, Sujay Sanghavi:
SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors. CoRR abs/2405.19597 (2024) - [i52]Disha Makhija, Xing Han, Joydeep Ghosh, Yejin Kim:
Achieving Fairness Across Local and Global Models in Federated Learning. CoRR abs/2406.17102 (2024) - 2023
- [c206]Hsing-Huan Chung, Joydeep Ghosh:
Incremental Unsupervised Domain Adaptation on Evolving Graphs. CoLLAs 2023: 683-702 - [c205]Shubham Sharma, Jette Henderson, Joydeep Ghosh:
FEAMOE: Fair, Explainable and Adaptive Mixture of Experts. IJCAI 2023: 492-500 - [c204]Xing Han, Jing Hu, Joydeep Ghosh:
A Novel Control-Variates Approach for Performative Gradient-Based Learners with Missing Data. IJCNN 2023: 1-8 - [c203]Xing Han, Tongzheng Ren, Tan Nguyen, Khai Nguyen, Joydeep Ghosh, Nhat Ho:
Designing Robust Transformers using Robust Kernel Density Estimation. NeurIPS 2023 - [i51]Disha Makhija, Joydeep Ghosh, Nhat Ho:
Privacy Preserving Bayesian Federated Learning in Heterogeneous Settings. CoRR abs/2306.07959 (2023) - 2022
- [j86]Md Meftahul Ferdaus
, Bangjian Zhou, Ji Wei Yoon, Kain Lu Low, Jieming Pan, Joydeep Ghosh, Min Wu, Xiaoli Li, Aaron Voon-Yew Thean, J. Senthilnath:
Significance of activation functions in developing an online classifier for semiconductor defect detection. Knowl. Based Syst. 248: 108818 (2022) - [c202]Diego García-Olano, Yasumasa Onoe, Joydeep Ghosh, Byron C. Wallace:
Intermediate Entity-based Sparse Interpretable Representation Learning. BlackboxNLP@EMNLP 2022: 210-224 - [c201]Xing Han, Jing Hu, Joydeep Ghosh:
Dynamic Combination of Heterogeneous Models for Hierarchical Time Series. ICDM (Workshops) 2022: 1207-1216 - [c200]Disha Makhija, Xing Han, Nhat Ho, Joydeep Ghosh:
Architecture Agnostic Federated Learning for Neural Networks. ICML 2022: 14860-14870 - [c199]Diego García-Olano, Yasumasa Onoe, Joydeep Ghosh:
Improving and Diagnosing Knowledge-Based Visual Question Answering via Entity Enhanced Knowledge Injection. WWW (Companion Volume) 2022: 705-715 - [i50]Disha Makhija, Xing Han, Nhat Ho, Joydeep Ghosh:
Architecture Agnostic Federated Learning for Neural Networks. CoRR abs/2202.07757 (2022) - [i49]Disha Makhija, Nhat Ho, Joydeep Ghosh:
Federated Self-supervised Learning for Heterogeneous Clients. CoRR abs/2205.12493 (2022) - [i48]Xing Han, Tongzheng Ren, Jing Hu, Joydeep Ghosh, Nhat Ho:
Efficient Forecasting of Large Scale Hierarchical Time Series via Multilevel Clustering. CoRR abs/2205.14104 (2022) - [i47]Xing Han, Ziyang Tang, Joydeep Ghosh, Qiang Liu:
Split Localized Conformal Prediction. CoRR abs/2206.13092 (2022) - [i46]Shubham Sharma, Jette Henderson, Joydeep Ghosh:
FEAMOE: Fair, Explainable and Adaptive Mixture of Experts. CoRR abs/2210.04995 (2022) - [i45]Xing Han, Tongzheng Ren, Tan Minh Nguyen, Khai Nguyen, Joydeep Ghosh, Nhat Ho:
Robustify Transformers with Robust Kernel Density Estimation. CoRR abs/2210.05794 (2022) - [i44]Shubham Sharma, Alan H. Gee, Jette Henderson, Joydeep Ghosh:
FASTER-CE: Fast, Sparse, Transparent, and Robust Counterfactual Explanations. CoRR abs/2210.06578 (2022) - [i43]Diego García-Olano, Yasumasa Onoe, Joydeep Ghosh, Byron C. Wallace:
Intermediate Entity-based Sparse Interpretable Representation Learning. CoRR abs/2212.01641 (2022) - 2021
- [c198]Diego García-Olano, Yasumasa Onoe, Ioana Baldini, Joydeep Ghosh, Byron C. Wallace, Kush R. Varshney:
Biomedical Interpretable Entity Representations. ACL/IJCNLP (Findings) 2021: 3547-3561 - [c197]Shubham Sharma, Alan H. Gee, David Paydarfar, Joydeep Ghosh:
FaiR-N: Fair and Robust Neural Networks for Structured Data. AIES 2021: 946-955 - [c196]Xing Han, Sambarta Dasgupta, Joydeep Ghosh:
Simultaneously Reconciled Quantile Forecasting of Hierarchically Related Time Series. AISTATS 2021: 190-198 - [c195]Xing Han, Joydeep Ghosh:
Model-Agnostic Explanations using Minimal Forcing Subsets. IJCNN 2021: 1-8 - [i42]Xing Han, Sambarta Dasgupta, Joydeep Ghosh:
Simultaneously Reconciled Quantile Forecasting of Hierarchically Related Time Series. CoRR abs/2102.12612 (2021) - [i41]Diego García-Olano, Yasumasa Onoe, Ioana Baldini, Joydeep Ghosh, Byron C. Wallace, Kush R. Varshney:
Biomedical Interpretable Entity Representations. CoRR abs/2106.09502 (2021) - [i40]Diego García-Olano, Yasumasa Onoe, Joydeep Ghosh:
Improving and Diagnosing Knowledge-Based Visual Question Answering via Entity Enhanced Knowledge Injection. CoRR abs/2112.06888 (2021) - [i39]Xing Han, Jing Hu, Joydeep Ghosh:
MECATS: Mixture-of-Experts for Quantile Forecasts of Aggregated Time Series. CoRR abs/2112.11669 (2021) - 2020
- [c194]Shubham Sharma, Jette Henderson, Joydeep Ghosh:
CERTIFAI: A Common Framework to Provide Explanations and Analyse the Fairness and Robustness of Black-box Models. AIES 2020: 166-172 - [c193]Neil Gupta, Joydeep Ghosh, Gunjan Gupta, Sheshank Shankar, Alex Tarasar:
Detection and Visualization of Dense Subgroups at Multiple Resolutions in Large Social Networks. ASONAM 2020: 73-80 - [c192]Umang Bhatt, Alice Xiang, Shubham Sharma, Adrian Weller, Ankur Taly, Yunhan Jia, Joydeep Ghosh, Ruchir Puri, José M. F. Moura, Peter Eckersley:
Explainable machine learning in deployment. FAT* 2020: 648-657 - [c191]Jette Henderson, Shubham Sharma, Alan H. Gee, Valeri Alexiev, Steve Draper, Carlos Marin, Yessel Hinojosa, Christine Draper, Michael Perng, Luis Aguirre, Michael Li, Sara Rouhani, Shorya Consul, Susan Michalski, Akarsh Prasad, Mayank Chutani, Aditya Kumar, Shahzad Alam, Prajna Kandarpa, Binnu Jesudasan, Colton Lee, Michael Criscolo, Sinead Williamson, Matt Sanchez, Joydeep Ghosh:
Certifai: A Toolkit for Building Trust in AI Systems. IJCAI 2020: 5249-5251 - [i38]Shubham Sharma, Alan H. Gee, David Paydarfar, Joydeep Ghosh:
FaiR-N: Fair and Robust Neural Networks for Structured Data. CoRR abs/2010.06113 (2020) - [i37]Aditya Jain, Manish Ravula, Joydeep Ghosh:
Biased Models Have Biased Explanations. CoRR abs/2012.10986 (2020)
2010 – 2019
- 2019
- [j85]Dean Teffer, Ravi Srinivasan, Joydeep Ghosh:
AdaHash: hashing-based scalable, adaptive hierarchical clustering of streaming data on Mapreduce frameworks. Int. J. Data Sci. Anal. 8(3): 257-267 (2019) - [j84]Luiz F. S. Coletta, Moacir Ponti, Eduardo R. Hruschka, Ayan Acharya, Joydeep Ghosh:
Combining clustering and active learning for the detection and learning of new image classes. Neurocomputing 358: 150-165 (2019) - [c190]Rajiv Khanna, Been Kim, Joydeep Ghosh, Sanmi Koyejo:
Interpreting Black Box Predictions using Fisher Kernels. AISTATS 2019: 3382-3390 - [c189]Michael Motro, Joydeep Ghosh:
Scaling Data Association for Hypothesis-Oriented MHT. FUSION 2019: 1-8 - [c188]Alan H. Gee, Diego García-Olano, Joydeep Ghosh, David Paydarfar:
Explaining Deep Classification of Time-Series Data with Learned Prototypes. KDH@IJCAI 2019: 15-22 - [c187]Taewan Kim, Joydeep Ghosh:
On Single Source Robustness in Deep Fusion Models. NeurIPS 2019: 4815-4826 - [c186]Jette Henderson, Bradley A. Malin, Joshua C. Denny, Abel N. Kho, Jimeng Sun, Joydeep Ghosh, Joyce C. Ho:
CP Tensor Decomposition with Cannot-Link Intermode Constraints. SDM 2019: 711-719 - [c185]Dany Haddad, Joydeep Ghosh:
Learning More From Less: Towards Strengthening Weak Supervision for Ad-Hoc Retrieval. SIGIR 2019: 857-860 - [i36]Alan H. Gee, Diego García-Olano, Joydeep Ghosh, David Paydarfar:
Explaining Deep Classification of Time-Series Data with Learned Prototypes. CoRR abs/1904.08935 (2019) - [i35]Shubham Sharma, Jette Henderson, Joydeep Ghosh:
CERTIFAI: Counterfactual Explanations for Robustness, Transparency, Interpretability, and Fairness of Artificial Intelligence models. CoRR abs/1905.07857 (2019) - [i34]Taewan Kim, Joydeep Ghosh:
On Single Source Robustness in Deep Fusion Models. CoRR abs/1906.04691 (2019) - [i33]Dany Haddad, Joydeep Ghosh:
Learning More From Less: Towards Strengthening Weak Supervision for Ad-Hoc Retrieval. CoRR abs/1907.08657 (2019) - [i32]Shalmali Joshi, Oluwasanmi Koyejo, Warut Vijitbenjaronk, Been Kim, Joydeep Ghosh:
Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems. CoRR abs/1907.09615 (2019) - [i31]Michael Motro, Joydeep Ghosh:
Vehicular Multi-object Tracking with Persistent Detector Failures. CoRR abs/1907.11306 (2019) - [i30]Umang Bhatt, Alice Xiang, Shubham Sharma, Adrian Weller, Ankur Taly, Yunhan Jia, Joydeep Ghosh, Ruchir Puri, José M. F. Moura, Peter Eckersley:
Explainable Machine Learning in Deployment. CoRR abs/1909.06342 (2019) - 2018
- [c184]Francesco Locatello, Rajiv Khanna, Joydeep Ghosh, Gunnar Rätsch:
Boosting Variational Inference: an Optimization Perspective. AISTATS 2018: 464-472 - [c183]Rahi Kalantari, Joydeep Ghosh, Mingyuan Zhou:
Nonparametric Bayesian sparse graph linear dynamical systems. AISTATS 2018: 1952-1960 - [c182]Jette Henderson, Huan He, Bradley A. Malin, Joshua C. Denny, Abel N. Kho, Joydeep Ghosh, Joyce C. Ho:
Phenotyping through Semi-Supervised Tensor Factorization (PSST). AMIA 2018 - [c181]Alan H. Gee, Joshua Chang, Joydeep Ghosh, David Paydarfar:
Bayesian Online Changepoint Detection Of Physiological Transitions. EMBC 2018: 45-48 - [c180]Michael Motro, Joydeep Ghosh:
Measurement-Wise Occlusion in Multi-Object Tracking. FUSION 2018: 2384-2391 - [c179]Woody Austin, Dylan Anderson, Joydeep Ghosh:
Fully Supervised Non-Negative Matrix Factorization for Feature Extraction. IGARSS 2018: 5772-5775 - [c178]Dean Teffer, Joydeep Ghosh:
Non-parametric Discovery of Topics and Communities in Distributed and Streaming Environments. INISTA 2018: 1-7 - [c177]Taewan Kim, Michael Motro, Patricia Lavieri, Saharsh Samir Oza, Joydeep Ghosh, Chandra R. Bhat:
Pedestrian Detection with Simplified Depth Prediction. ITSC 2018: 2712-2717 - [c176]Ayan Acharya, Joydeep Ghosh, Mingyuan Zhou:
A Dual Markov Chain Topic Model for Dynamic Environments. KDD 2018: 1099-1108 - [c175]Shalmali Joshi, Rajiv Khanna, Joydeep Ghosh:
Co-regularized Monotone Retargeting for Semi-supervised LeTOR. SDM 2018: 432-440 - [i29]Michael Motro, Joydeep Ghosh:
Measurement-wise Occlusion in Multi-object Tracking. CoRR abs/1805.08324 (2018) - [i28]Shalmali Joshi, Oluwasanmi Koyejo, Been Kim, Joydeep Ghosh:
xGEMs: Generating Examplars to Explain Black-Box Models. CoRR abs/1806.08867 (2018) - [i27]Jette Henderson, Bradley A. Malin, Joyce C. Ho, Joydeep Ghosh:
PIVETed-Granite: Computational Phenotypes through Constrained Tensor Factorization. CoRR abs/1808.02602 (2018) - [i26]Rajiv Khanna, Been Kim, Joydeep Ghosh, Oluwasanmi Koyejo:
Interpreting Black Box Predictions using Fisher Kernels. CoRR abs/1810.10118 (2018) - 2017
- [j83]Meghana Deodhar, Joydeep Ghosh, Maytal Saar-Tsechansky, Vineet Keshari:
Active Learning with Multiple Localized Regression Models. INFORMS J. Comput. 29(3): 503-522 (2017) - [c174]Avradeep Bhowmik, Joydeep Ghosh, Oluwasanmi Koyejo:
Frequency Domain Predictive Modelling with Aggregated Data. AISTATS 2017: 971-980 - [c173]Rajiv Khanna, Joydeep Ghosh, Russell A. Poldrack, Oluwasanmi Koyejo:
Information Projection and Approximate Inference for Structured Sparse Variables. AISTATS 2017: 1358-1366 - [c172]Rajiv Khanna, Ethan R. Elenberg, Alexandros G. Dimakis, Sahand N. Negahban, Joydeep Ghosh:
Scalable Greedy Feature Selection via Weak Submodularity. AISTATS 2017: 1560-1568 - [c171]Jimeng Sun, Bradley A. Malin, Abel N. Kho, Mark W. Craven, Joydeep Ghosh:
Computational Phenotyping on Diverse Data Sources. AMIA 2017 - [c170]Jette Henderson, Ryan Bridges, Joyce C. Ho, Byron C. Wallace, Joydeep Ghosh:
PheKnow-Cloud: A Tool for Evaluating High-Throughput Phenotype Candidates using Online Medical Literature. CRI 2017 - [c169]Janice Pan, Robert Shaffer, Zeina Sinno, Marcus Tyler, Joydeep Ghosh:
The obesity paradox in ICU patients. EMBC 2017: 3360-3364 - [c168]Jette Henderson, Joyce C. Ho, Joydeep Ghosh:
gamAID: Greedy CP tensor decomposition for supervised EHR-based disease trajectory differentiation. EMBC 2017: 3644-3647 - [c167]Jette Henderson, Joyce C. Ho, Abel N. Kho, Joshua C. Denny, Bradley A. Malin, Jimeng Sun, Joydeep Ghosh:
Granite: Diversified, Sparse Tensor Factorization for Electronic Health Record-Based Phenotyping. ICHI 2017: 214-223 - [c166]Rajiv Khanna, Ethan R. Elenberg, Alexandros G. Dimakis, Joydeep Ghosh, Sahand N. Negahban:
On Approximation Guarantees for Greedy Low Rank Optimization. ICML 2017: 1837-1846 - [c165]Michael Motro, Joydeep Ghosh, Chandra R. Bhat:
Optimal alarms for vehicular collision detection. Intelligent Vehicles Symposium 2017: 277-282 - [c164]Rajiv Khanna, Joydeep Ghosh, Russell A. Poldrack, Oluwasanmi Koyejo:
A Deflation Method for Structured Probabilistic PCA. SDM 2017: 534-542 - [c163]Avradeep Bhowmik, Joydeep Ghosh:
LETOR Methods for Unsupervised Rank Aggregation. WWW 2017: 1331-1340 - [i25]Rajiv Khanna, Ethan R. Elenberg, Alexandros G. Dimakis, Sahand N. Negahban, Joydeep Ghosh:
Scalable Greedy Feature Selection via Weak Submodularity. CoRR abs/1703.02723 (2017) - [i24]Francesco Locatello, Rajiv Khanna, Joydeep Ghosh, Gunnar Rätsch:
Boosting Variational Inference: an Optimization Perspective. CoRR abs/1708.01733 (2017) - [i23]Michael Motro, Joydeep Ghosh, Chandra R. Bhat:
Optimal Alarms for Vehicular Collision Detection. CoRR abs/1708.04922 (2017) - [i22]Taewan Kim, Joydeep Ghosh:
Semi-Supervised Active Clustering with Weak Oracles. CoRR abs/1709.03202 (2017) - [i21]Taewan Kim, Joydeep Ghosh:
Relaxed Oracles for Semi-Supervised Clustering. CoRR abs/1711.07433 (2017) - 2016
- [j82]Thiago F. Covoes, Eduardo Raul Hruschka, Joydeep Ghosh:
Evolving Gaussian Mixture Models with Splitting and Merging Mutation Operators. Evol. Comput. 24(2): 293-317 (2016) - [j81]Shalmali Joshi, Joydeep Ghosh, Mark Reid, Oluwasanmi Koyejo:
Rényi divergence minimization based co-regularized multiview clustering. Mach. Learn. 104(2-3): 411-439 (2016) - [c162]Matias I. Hurtado, Jette Henderson, Joydeep Ghosh:
Evaluating Differences Between MIMIC II and III Critical Care Databases. AMIA 2016 - [c161]Ryan Bridges, Jette Henderson, Joyce C. Ho, Byron C. Wallace, Joydeep Ghosh:
Automated Verification of Phenotypes using PubMed. BCB 2016: 595-602 - [c160]Avradeep Bhowmik, Joydeep Ghosh, Oluwasanmi Koyejo:
Sparse Parameter Recovery from Aggregated Data. ICML 2016: 1090-1099 - [c159]Taewan Kim, Joydeep Ghosh:
Robust detection of non-motorized road users using deep learning on optical and LIDAR data. ITSC 2016: 271-276 - [c158]Rahi Kalantari, Michael Motro, Joydeep Ghosh, Chandra R. Bhat:
A distributed, collective intelligence framework for collision-free navigation through busy intersections. ITSC 2016: 1378-1383 - [c157]Shalmali Joshi, Suriya Gunasekar, David A. Sontag, Joydeep Ghosh:
Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization. MLHC 2016: 17-41 - [c156]Suriya Gunasekar, Oluwasanmi Koyejo, Joydeep Ghosh:
Preference Completion from Partial Rankings. NIPS 2016: 1370-1378 - [i20]Avradeep Bhowmik, Joydeep Ghosh:
Monotone Retargeting for Unsupervised Rank Aggregation with Object Features. CoRR abs/1605.04465 (2016) - [i19]Avradeep Bhowmik, Joydeep Ghosh, Oluwasanmi Koyejo:
Generalized Linear Models for Aggregated Data. CoRR abs/1605.04466 (2016) - [i18]Yubin Park, Joyce C. Ho, Joydeep Ghosh:
ACDC: $α$-Carving Decision Chain for Risk Stratification. CoRR abs/1606.05325 (2016) - [i17]Rajiv Khanna, Joydeep Ghosh, Russell A. Poldrack, Oluwasanmi Koyejo:
Information Projection and Approximate Inference for Structured Sparse Variables. CoRR abs/1607.03204 (2016) - [i16]Shalmali Joshi, Suriya Gunasekar, David A. Sontag, Joydeep Ghosh:
Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization. CoRR abs/1608.00704 (2016) - [i15]Suriya Gunasekar, Oluwasanmi Koyejo, Joydeep Ghosh:
Preference Completion from Partial Rankings. CoRR abs/1611.04218 (2016) - [i14]Ashish Bora, Sugato Basu, Joydeep Ghosh:
Graphical RNN Models. CoRR abs/1612.05054 (2016) - 2015
- [j80]Luiz F. S. Coletta, Eduardo R. Hruschka, Ayan Acharya, Joydeep Ghosh:
Using metaheuristics to optimize the combination of classifier and cluster ensembles. Integr. Comput. Aided Eng. 22(3): 229-242 (2015) - [j79]Luiz F. S. Coletta, Eduardo Raul Hruschka, Ayan Acharya, Joydeep Ghosh:
A differential evolution algorithm to optimise the combination of classifier and cluster ensembles. Int. J. Bio Inspired Comput. 7(2): 111-124 (2015) - [j78]You Chen, Joydeep Ghosh, Cosmin Adrian Bejan, Carl A. Gunter, Siddharth Gupta, Abel N. Kho, David M. Liebovitz, Jimeng Sun, Joshua C. Denny, Bradley A. Malin:
Building bridges across electronic health record systems through inferred phenotypic topics. J. Biomed. Informatics 55: 82-93 (2015) - [c155]Ayan Acharya, Joydeep Ghosh, Mingyuan Zhou:
Nonparametric Bayesian Factor Analysis for Dynamic Count Matrices. AISTATS 2015 - [c154]Sreangsu Acharyya, Joydeep Ghosh:
Parameter Estimation of Generalized Linear Models without Assuming their Link Function. AISTATS 2015 - [c153]Avradeep Bhowmik, Joydeep Ghosh, Oluwasanmi Koyejo:
Generalized Linear Models for Aggregated Data. AISTATS 2015 - [c152]Rajiv Khanna, Joydeep Ghosh, Russell A. Poldrack, Oluwasanmi Koyejo:
Sparse Submodular Probabilistic PCA. AISTATS 2015 - [c151]Avijit Saha, Ayan Acharya, Balaraman Ravindran, Joydeep Ghosh:
Nonparametric Poisson Factorization Machine. ICDM 2015: 967-972 - [c150]Shalmali Joshi, Oluwasanmi Koyejo, Kristine Resurreccion, Joydeep Ghosh:
Simultaneous Prognosis and Exploratory Analysis of Multiple Chronic Conditions Using Clinical Notes. ICHI 2015: 243-252 - [c149]Shalmali Joshi, Oluwasanmi Koyejo, Joydeep Ghosh:
Simultaneous Prognosis of Multiple Chronic Conditions from Heterogeneous EHR Data. ICHI 2015: 497 - [c148]Yichen Wang, Robert Chen, Joydeep Ghosh, Joshua C. Denny, Abel N. Kho, You Chen, Bradley A. Malin, Jimeng Sun:
Rubik: Knowledge Guided Tensor Factorization and Completion for Health Data Analytics. KDD 2015: 1265-1274 - [c147]Joydeep Ghosh, Dmitry Osintsev, Viktor Sverdlov, Josef Weinbub, Siegfried Selberherr:
Evaluation of Spin Lifetime in Thin-Body FETs: A High Performance Computing Approach. LSSC 2015: 285-292 - [c146]Suriya Gunasekar, Arindam Banerjee, Joydeep Ghosh:
Unified View of Matrix Completion under General Structural Constraints. NIPS 2015: 1180-1188 - [c145]Ayan Acharya, Dean Teffer, Jette Henderson, Marcus Tyler, Mingyuan Zhou, Joydeep Ghosh:
Gamma Process Poisson Factorization for Joint Modeling of Network and Documents. ECML/PKDD (1) 2015: 283-299 - [p4]Yubin Park, Joydeep Ghosh:
Privacy-Preserving Data Publishing Methods in Healthcare. Healthcare Data Analytics 2015: 507-529 - [i13]Suriya Gunasekar, Pradeep Ravikumar, Joydeep Ghosh:
Exponential Family Matrix Completion under Structural Constraints. CoRR abs/1509.04397 (2015) - 2014
- [j77]Joyce C. Ho, Joydeep Ghosh, Steven R. Steinhubl, Walter F. Stewart, Joshua C. Denny, Bradley A. Malin, Jimeng Sun:
Limestone: High-throughput candidate phenotype generation via tensor factorization. J. Biomed. Informatics 52: 199-211 (2014) - [j76]Oluwasanmi Koyejo, Cheng H. Lee, Joydeep Ghosh:
A constrained matrix-variate Gaussian process for transposable data. Mach. Learn. 97(1-2): 103-127 (2014) - [j75]Yubin Park, Joydeep Ghosh:
PeGS: Perturbed Gibbs Samplers that Generate Privacy-Compliant Synthetic Data. Trans. Data Priv. 7(3): 253-282 (2014) - [j74]Suriya Gunasekar, Joydeep Ghosh, Alan C. Bovik:
Face Detection on Distorted Images Augmented by Perceptual Quality-Aware Features. IEEE Trans. Inf. Forensics Secur. 9(12): 2119-2131 (2014) - [j73]Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh, Sreangsu Acharyya:
An Optimization Framework for Combining Ensembles of Classifiers and Clusterers with Applications to Nontransductive Semisupervised Learning and Transfer Learning. ACM Trans. Knowl. Discov. Data 9(1): 1:1-1:35 (2014) - [j72]Yubin Park, Joydeep Ghosh:
Ensembles of (α)-Trees for Imbalanced Classification Problems. IEEE Trans. Knowl. Data Eng. 26(1): 131-143 (2014) - [j71]Joyce C. Ho, Cheng H. Lee, Joydeep Ghosh:
Septic Shock Prediction for Patients with Missing Data. ACM Trans. Manag. Inf. Syst. 5(1): 1:1-1:15 (2014) - [c144]Yubin Park, Carlos Carvalho, Joydeep Ghosh:
LAMORE: A Stable, Scalable Approach to Latent Vector Autoregressive Modeling of Categorical Time Series. AISTATS 2014: 733-742 - [c143]Joyce C. Ho, Joydeep Ghosh, Jimeng Sun:
Extracting Phenotypes from Patient Claim Records Using Nonnegative Tensor Factorization. Brain Informatics and Health 2014: 142-151 - [c142]Yubin Park, Joydeep Ghosh:
A Hierarchical Ensemble of α-Trees for Predicting Expensive Hospital Visits. Brain Informatics and Health 2014: 178-187 - [c141]Suriya Gunasekar, Joydeep Ghosh, Alan C. Bovik:
Face detection on distorted images using perceptual quality-aware features. Human Vision and Electronic Imaging 2014: 90141E - [c140]Yubin Park, Mallikarjun Shankar, Byung-Hoon Park, Joydeep Ghosh:
Graph databases for large-scale healthcare systems: A framework for efficient data management and data services. ICDE Workshops 2014: 12-19 - [c139]Suriya Gunasekar, Pradeep Ravikumar, Joydeep Ghosh:
Exponential Family Matrix Completion under Structural Constraints. ICML 2014: 1917-1925 - [c138]Yubin Park, Joydeep Ghosh:
LUDIA: an aggregate-constrained low-rank reconstruction algorithm to leverage publicly released health data. KDD 2014: 55-64 - [c137]Joyce C. Ho, Joydeep Ghosh, Jimeng Sun:
Marble: high-throughput phenotyping from electronic health records via sparse nonnegative tensor factorization. KDD 2014: 115-124 - [c136]Oluwasanmi Koyejo, Rajiv Khanna, Joydeep Ghosh, Russell A. Poldrack:
On Prior Distributions and Approximate Inference for Structured Variables. NIPS 2014: 676-684 - [c135]Ayan Acharya, Raymond J. Mooney, Joydeep Ghosh:
Active Multitask Learning Using Both Latent and Supervised Shared Topics. SDM 2014: 190-198 - [c134]Sreangsu Acharyya, Joydeep Ghosh:
MEMR: A Margin Equipped Monotone Retargeting Framework for Ranking. UAI 2014: 2-11 - [i12]Duo Ding, Bei Yu, Joydeep Ghosh, David Z. Pan:
EPIC: Efficient prediction of IC manufacturing hotspots with a unified meta-classification formulation. CoRR abs/1402.2904 (2014) - [i11]Oluwasanmi Koyejo, Cheng H. Lee, Joydeep Ghosh:
A Constrained Matrix-Variate Gaussian Process for Transposable Data. CoRR abs/1404.6702 (2014) - 2013
- [j70]Thiago F. Covoes, Eduardo R. Hruschka, Joydeep Ghosh:
A study of K-Means-based algorithms for constrained clustering. Intell. Data Anal. 17(3): 485-505 (2013) - [j69]Goo Jun, Joydeep Ghosh:
Semisupervised Learning of Hyperspectral Data With Unknown Land-Cover Classes. IEEE Trans. Geosci. Remote. Sens. 51(1): 273-282 (2013) - [j68]Yubin Park, Joydeep Ghosh:
CUDIA: Probabilistic cross-level imputation using individual auxiliary information. ACM Trans. Intell. Syst. Technol. 4(4): 66:1-66:24 (2013) - [j67]Thiago F. Covoes, Eduardo R. Hruschka, Joydeep Ghosh:
Competitive Learning With Pairwise Constraints. IEEE Trans. Neural Networks Learn. Syst. 24(1): 164-169 (2013) - [c133]Joyce C. Ho, Yubin Park, Carlos Carvalho, Joydeep Ghosh:
DYNACARE: Dynamic Cardiac Arrest Risk Estimation. AISTATS 2013: 333-341 - [c132]Mijung Park, Oluwasanmi Koyejo, Joydeep Ghosh, Russell A. Poldrack, Jonathan W. Pillow:
Bayesian Structure Learning for Functional Neuroimaging. AISTATS 2013: 489-497 - [c131]Yubin Park, Joyce C. Ho, Joydeep Ghosh:
Multivariate temporal symptomatic characterization of cardiac arrest. EMBC 2013: 3222-3225 - [c130]Cheng H. Lee, Oluwasanmi Koyejo, Joydeep Ghosh:
Identifying candidate disease genes using a trace norm constrained bipartite raking model. EMBC 2013: 3459-3462 - [c129]Anish Mittal, Rajiv Soundararajan, Gautam S. Muralidhar, Alan C. Bovik, Joydeep Ghosh:
Blind image quality assessment without training on human opinion scores. Human Vision and Electronic Imaging 2013: 86510T - [c128]Oluwasanmi Koyejo, Cheng H. Lee, Joydeep Ghosh:
Constrained Gaussian Process Regression for Gene-Disease Association. ICDM Workshops 2013: 72-79 - [c127]Joyce C. Ho, Joydeep Ghosh, K. P. Unnikrishnan:
Risk Prediction of a Multiple Sclerosis Diagnosis. ICHI 2013: 175-183 - [c126]Yubin Park, Joydeep Ghosh, Mallikarjun Shankar:
Perturbed Gibbs Samplers for Generating Large-Scale Privacy-Safe Synthetic Health Data. ICHI 2013: 493-498 - [c125]Suriya Gunasekar, Ayan Acharya, Neeraj Gaur, Joydeep Ghosh:
Noisy Matrix Completion Using Alternating Minimization. ECML/PKDD (2) 2013: 194-209 - [c124]Oluwasanmi Koyejo, Priyank Patel, Joydeep Ghosh, Russell A. Poldrack:
Learning Predictive Cognitive Structure from fMRI Using Supervised Topic Models. PRNI 2013: 9-12 - [c123]Oluwasanmi Koyejo, Sreangsu Acharyya, Joydeep Ghosh:
Retargeted matrix factorization for collaborative filtering. RecSys 2013: 49-56 - [c122]Ayan Acharya, Joydeep Ghosh, Eduardo R. Hruschka, Jean-David Ruvini, Badrul Sarwar:
Probabilistic Combination of Classifier and Cluster Ensembles for Non-transductive Learning. SDM 2013: 288-296 - [c121]Oluwasanmi Koyejo, Joydeep Ghosh:
Constrained Bayesian Inference for Low Rank Multitask Learning. UAI 2013 - [p3]Joydeep Ghosh, Ayan Acharya:
Cluster Ensembles: Theory and Applications. Data Clustering: Algorithms and Applications 2013: 551-570 - [i10]Oluwasanmi Koyejo, Cheng H. Lee, Joydeep Ghosh:
The trace norm constrained matrix-variate Gaussian process for multitask bipartite ranking. CoRR abs/1302.2576 (2013) - [i9]Oluwasanmi Koyejo, Joydeep Ghosh:
Constrained Bayesian Inference for Low Rank Multitask Learning. CoRR abs/1309.6840 (2013) - 2012
- [j66]Anish Mittal, Gautam S. Muralidhar, Joydeep Ghosh, Alan C. Bovik:
Blind Image Quality Assessment Without Human Training Using Latent Quality Factors. IEEE Signal Process. Lett. 19(2): 75-78 (2012) - [j65]Joydeep Ghosh, Padhraic Smyth, Andrew Tomkins, Rich Caruana:
Special issue on best of SIGKDD 2011. ACM Trans. Knowl. Discov. Data 6(4): 14:1-14:2 (2012) - [c120]Duo Ding, Bei Yu, Joydeep Ghosh, David Z. Pan:
EPIC: Efficient prediction of IC manufacturing hotspots with a unified meta-classification formulation. ASP-DAC 2012: 263-270 - [c119]Yong Jae Lee, Joydeep Ghosh, Kristen Grauman:
Discovering important people and objects for egocentric video summarization. CVPR 2012: 1346-1353 - [c118]Yubin Park, Joydeep Ghosh:
A probabilistic imputation framework for predictive analysis using variably aggregated, multi-source healthcare data. IHI 2012: 445-454 - [c117]Sindhu Raghavan, Suriya Gunasekar, Joydeep Ghosh:
Review quality aware collaborative filtering. RecSys 2012: 123-130 - [c116]Sreangsu Acharyya, Oluwasanmi Koyejo, Joydeep Ghosh:
Learning to Rank With Bregman Divergences and Monotone Retargeting. UAI 2012: 15-25 - [c115]Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh, Sreangsu Acharyya:
Transfer Learning with Cluster Ensembles. ICML Unsupervised and Transfer Learning 2012: 123-132 - [i8]Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh:
A Privacy-Aware Bayesian Approach for Combining Classifier and Cluster Ensembles. CoRR abs/1204.4521 (2012) - [i7]Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh, Sreangsu Acharyya:
An Optimization Framework for Semi-Supervised and Transfer Learning using Multiple Classifiers and Clusterers. CoRR abs/1206.0994 (2012) - [i6]Sreangsu Acharyya, Oluwasanmi Koyejo, Joydeep Ghosh:
Learning to Rank With Bregman Divergences and Monotone Retargeting. CoRR abs/1210.4851 (2012) - [i5]Abhimanu Kumar, Jason Baldridge, Matthew Lease, Joydeep Ghosh:
Dating Texts without Explicit Temporal Cues. CoRR abs/1211.2290 (2012) - [i4]Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh, Badrul Sarwar, Jean-David Ruvini:
Probabilistic Combination of Classifier and Cluster Ensembles for Non-transductive Learning. CoRR abs/1211.2304 (2012) - 2011
- [j64]Goo Jun, Joydeep Ghosh:
Spatially adaptive semi-supervised learning with Gaussian processes for hyperspectral data analysis. Stat. Anal. Data Min. 4(4): 358-371 (2011) - [j63]Goo Jun, Joydeep Ghosh:
Spatially Adaptive Classification of Land Cover With Remote Sensing Data. IEEE Trans. Geosci. Remote. Sens. 49(7): 2662-2673 (2011) - [j62]Joydeep Ghosh, Ayan Acharya:
Cluster ensembles. WIREs Data Mining Knowl. Discov. 1(4): 305-315 (2011) - [c114]Dean Teffer, Amanda Hutton, Joydeep Ghosh:
Temporal Distributed Learning with Heterogeneous Data Using Gaussian Mixtures. ICDM Workshops 2011: 196-203 - [c113]Aayush Sharma, Meghana Deodhar, Joydeep Ghosh:
Prediction of New Customer-Product Affinities from Rich Dyadic Data using Localized Models. ICDM (Workshops) 2011: 103-112 - [c112]Yubin Park, Joydeep Ghosh:
Compact Ensemble Trees for Imbalanced Data. MCS 2011: 86-95 - [c111]Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh, Sreangsu Acharyya:
C 3E: A Framework for Combining Ensembles of Classifiers and Clusterers. MCS 2011: 269-278 - [c110]Oluwasanmi Koyejo, Joydeep Ghosh:
A kernel-based approach to exploiting interaction-networks in heterogeneous information sources for improved recommender systems. HetRec@RecSys 2011: 9-16 - [c109]Clinton Jones, Joydeep Ghosh, Aayush Sharma:
Learning multiple models for exploiting predictive heterogeneity in recommender systems. HetRec@RecSys 2011: 17-24 - [c108]Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh:
A Privacy-Aware Bayesian Approach for Combining Classifier and Cluster Ensembles. SocialCom/PASSAT 2011: 1169-1172 - [e2]Chid Apté, Joydeep Ghosh, Padhraic Smyth:
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego, CA, USA, August 21-24, 2011. ACM 2011, ISBN 978-1-4503-0813-7 [contents] - 2010
- [j61]Gunjan Gupta, Alexander Liu, Joydeep Ghosh:
Automated Hierarchical Density Shaving: A Robust Automated Clustering and Visualization Framework for Large Biological Data Sets. IEEE ACM Trans. Comput. Biol. Bioinform. 7(2): 223-237 (2010) - [j60]Meghana Deodhar, Joydeep Ghosh:
SCOAL: A framework for simultaneous co-clustering and learning from complex data. ACM Trans. Knowl. Discov. Data 4(3): 11:1-11:31 (2010) - [c107]Goo Jun, Joydeep Ghosh:
Spatially Adaptive Semi-supervised Learning with Gaussian Processes for Hyperspectral Data Analysis. CIDU 2010: 27-38 - [c106]Meghana Deodhar, Joydeep Ghosh:
A Decoupled Approach for Modeling Heterogeneous Dyadic Data with Covariates. GrC 2010: 143-148 - [c105]Meghana Deodhar, Clinton Jones, Joydeep Ghosh:
Parallel Simultaneous Co-clustering and Learning with Map-Reduce. GrC 2010: 149-154 - [c104]Joydeep Ghosh, Aayush Sharma:
Actionable Mining of Large, Multi-relational Data Using Localized Predictive Models. IC3K 2010: 3-22 - [c103]Joydeep Ghosh:
Actionable Mining of Large, Multi-relational Data using Localized Predictive Models. KDIR 2010: 09-010 - [c102]Goo Jun, Joydeep Ghosh, Vladan Radosavljevic, Zoran Obradovic:
Predicting Ground-based Aerosol Optical Depth with Satellite Images Via Gaussian Processes. KDIR 2010: 370-375 - [c101]Srivatsava Daruru, Sankari Dhandapani, Gunjan Gupta, Ilian Iliev, Weijia Xu, Paul A. Navrátil, Nena M. Marin, Joydeep Ghosh:
Distributed, Scalable Clustering for Detecting Halos in Terascale Astronomy Datasets. ICDM Workshops 2010: 138-147 - [c100]Goo Jun, Joydeep Ghosh:
Nearest-Manifold Classification with Gaussian Processes. ICPR 2010: 914-917 - [p2]Alexander Liu, Cheryl Martin, Brian La Cour, Joydeep Ghosh:
Effects of Oversampling Versus Cost-Sensitive Learning for Bayesian and SVM Classifiers. Data Mining 2010: 159-192
2000 – 2009
- 2009
- [j59]Alexander Liu, Goo Jun, Joydeep Ghosh:
A self-training approach to cost sensitive uncertainty sampling. Mach. Learn. 76(2-3): 257-270 (2009) - [c99]Oluwasanmi Koyejo, Joydeep Ghosh:
MiPPS: A Generative Model for Multi-Manifold Clustering. AAAI Fall Symposium: Manifold Learning and Its Applications 2009 - [c98]Goo Jun, Ranga Raju Vatsavai, Joydeep Ghosh:
Spatially Adaptive Classification and Active Learning of Multispectral Data with Gaussian Processes. ICDM Workshops 2009: 597-603 - [c97]Meghana Deodhar, Gunjan Gupta, Joydeep Ghosh, Hyuk Cho, Inderjit S. Dhillon:
A scalable framework for discovering coherent co-clusters in noisy data. ICML 2009: 241-248 - [c96]Alexander Liu, Goo Jun, Joydeep Ghosh:
Active Learning of Hyperspectral Data with Spatially Dependent Label Acquisition Costs. IGARSS (5) 2009: 256-259 - [c95]Goo Jun, Joydeep Ghosh:
Spatially Adaptive Classification of Hyperspectral Data with Gaussian Processes. IGARSS (2) 2009: 290-293 - [c94]Meghana Deodhar, Joydeep Ghosh:
Mining for the most certain predictions from dyadic data. KDD 2009: 249-258 - [c93]Srivatsava Daruru, Nena M. Marin, Matt Walker, Joydeep Ghosh:
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data. KDD 2009: 1115-1124 - [c92]Goo Jun, Joydeep Ghosh:
Multi-class Boosting with Class Hierarchies. MCS 2009: 32-41 - [c91]Goo Jun, Joydeep Ghosh:
Hybrid Hierarchical Classifiers for Hyperspectral Data Analysis. MCS 2009: 42-51 - [c90]Alexander Liu, Goo Jun, Joydeep Ghosh:
A Self-training Approach to Cost Sensitive Uncertainty Sampling. ECML/PKDD (1) 2009: 10 - [c89]Alexander Liu, Goo Jun, Joydeep Ghosh:
Spatially Cost-Sensitive Active Learning. SDM 2009: 814-825 - 2008
- [j58]Kunal Punera, Joydeep Ghosh:
Consensus-Based Ensembles of Soft Clusterings. Appl. Artif. Intell. 22(7&8): 780-810 (2008) - [j57]Yue Luo, Ajay Joshi, Aashish Phansalkar, Lizy Kurian John, Joydeep Ghosh:
Analysing and improving clustering based sampling for microprocessor simulation. Int. J. High Perform. Comput. Netw. 5(4): 200-214 (2008) - [j56]Xindong Wu, Vipin Kumar, J. Ross Quinlan, Joydeep Ghosh, Qiang Yang, Hiroshi Motoda, Geoffrey J. McLachlan, Angus F. M. Ng, Bing Liu, Philip S. Yu, Zhi-Hua Zhou, Michael S. Steinbach, David J. Hand, Dan Steinberg:
Top 10 algorithms in data mining. Knowl. Inf. Syst. 14(1): 1-37 (2008) - [j55]Suju Rajan, Joydeep Ghosh, Melba M. Crawford:
An Active Learning Approach to Hyperspectral Data Classification. IEEE Trans. Geosci. Remote. Sens. 46(4): 1231-1242 (2008) - [j54]Gunjan Gupta, Joydeep Ghosh:
Bregman bubble clustering: A robust framework for mining dense clusters. ACM Trans. Knowl. Discov. Data 2(2): 8:1-8:49 (2008) - [c88]Sreangsu Acharyya, Joydeep Ghosh:
A spam resistant family of concavo-convex ranks for link analysis. CIKM 2008: 1505-1506 - [c87]Meghana Deodhar, Joydeep Ghosh, Gunjan Gupta, Hyuk Cho, Inderjit S. Dhillon:
Hunting for Coherent Co-clusters in High Dimensional and Noisy Datasets. ICDM Workshops 2008: 654-663 - [c86]Meghana Deodhar, Joydeep Ghosh:
Simultaneous Co-segmentation and Predictive Modeling for Large, Temporal Marketing Data. ICDM Workshops 2008: 806-815 - [c85]Goo Jun, Joydeep Ghosh:
An Efficient Active Learning Algorithm with Knowledge Transfer for Hyperspectral Data Analysis. IGARSS (1) 2008: 52-55 - [c84]Wonkook Kim, Melba M. Crawford, Joydeep Ghosh:
Spatially Adapted Manifold Learning for Classification of Hyperspectral Imagery with Insufficient Labeled Data. IGARSS (1) 2008: 213-216 - [c83]Joydeep Ghosh:
Probabilistic frameworks for privacy-aware data mining. ISI 2008 - [c82]Matthew Riley, Eric Heinen, Joydeep Ghosh:
A Text Retrieval Approach to Content-Based Audio Hashing. ISMIR 2008: 295-300 - [c81]Kunal Punera, Joydeep Ghosh:
Enhanced hierarchical classification via isotonic smoothing. WWW 2008: 151-160 - 2007
- [j53]Joydeep Ghosh:
Data Mining Technical Committee. IEEE Comput. Intell. Mag. 2(2): 74 (2007) - [j52]Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu, Dharmendra S. Modha:
A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation. J. Mach. Learn. Res. 8: 1919-1986 (2007) - [c80]Chase Krumpelman, Joydeep Ghosh:
Matching and Visualization of Multiple Overlapping Clusterings of Microarray Data. CIBCB 2007: 121-126 - [c79]Yangchi Chen, Melba M. Crawford, Joydeep Ghosh:
Knowledge Based Stacking of Hyperspectral Data for Land Cover Classification. CIDM 2007: 316-322 - [c78]Alexander Liu, Joydeep Ghosh, Cheryl Martin:
Generative Oversampling for Mining Imbalanced Datasets. DMIN 2007: 66-72 - [c77]Wonkook Kim, Yangchi Chen, Melba M. Crawford, James C. Tilton, Joydeep Ghosh:
Multiresolution manifold learning for classification of hyperspectral data. IGARSS 2007: 3785-3788 - [c76]Meghana Deodhar, Joydeep Ghosh:
Simultaneous Co-clustering and Modeling of Market Data. ICDM (Posters and Workshops) 2007: 73-82 - [c75]Meghana Deodhar, Joydeep Ghosh:
A framework for simultaneous co-clustering and learning from complex data. KDD 2007: 250-259 - [c74]Kunal Punera, Joydeep Ghosh:
Consensus Based Ensembles of Soft Clusterings. MLMTA 2007: 3-9 - 2006
- [j51]Arindam Banerjee, Joydeep Ghosh:
Scalable Clustering Algorithms with Balancing Constraints. Data Min. Knowl. Discov. 13(3): 365-395 (2006) - [j50]Suju Rajan, Joydeep Ghosh, Melba M. Crawford:
Exploiting Class Hierarchies for Knowledge Transfer in Hyperspectral Data. IEEE Trans. Geosci. Remote. Sens. 44(11-2): 3408-3417 (2006) - [c73]Kunal Punera, Suju Rajan, Joydeep Ghosh:
Automatic Construction of N-ary Tree Based Taxonomies. ICDM Workshops 2006: 75-79 - [c72]Gunjan Gupta, Alexander Liu, Joydeep Ghosh:
Hierarchical Density Shaving: A clustering and visualization framework for large biological datasets. ICDM Workshops 2006: 89-93 - [c71]Meghana Deodhar, Joydeep Ghosh:
Consensus Clustering for Detection of Overlapping Clusters in Microarray Data. ICDM Workshops 2006: 104-108 - [c70]Gunjan Gupta, Joydeep Ghosh:
Bregman Bubble Clustering: A Robust, Scalable Framework for Locating Multiple, Dense Regions in Data. ICDM 2006: 232-243 - [c69]Suju Raj, Joydeep Ghosh, Melba M. Crawford:
An Active Learning Approach to Knowledge Transfer for Hyperspectral Data Analysis. IGARSS 2006: 541-544 - [c68]Yangchi Chen, Melba M. Crawford, Joydeep Ghosh:
Improved Nonlinear Manifold Learning for Land Cover Classification via Intelligent Landmark Selection. IGARSS 2006: 545-548 - [p1]Joydeep Ghosh, Alexander Strehl:
Similarity-Based Text Clustering: A Comparative Study. Grouping Multidimensional Data 2006: 73-97 - [e1]Joydeep Ghosh, Diane Lambert, David B. Skillicorn, Jaideep Srivastava:
Proceedings of the Sixth SIAM International Conference on Data Mining, April 20-22, 2006, Bethesda, MD, USA. SIAM 2006, ISBN 978-0-89871-611-5 [contents] - 2005
- [j49]Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Suvrit Sra:
Clustering on the Unit Hypersphere using von Mises-Fisher Distributions. J. Mach. Learn. Res. 6: 1345-1382 (2005) - [j48]Arindam Banerjee, Srujana Merugu, Inderjit S. Dhillon, Joydeep Ghosh:
Clustering with Bregman Divergences. J. Mach. Learn. Res. 6: 1705-1749 (2005) - [j47]Shi Zhong, Joydeep Ghosh:
Generative model-based document clustering: a comparative study. Knowl. Inf. Syst. 8(3): 374-384 (2005) - [j46]Srujana Merugu, Joydeep Ghosh:
A privacy-sensitive approach to distributed clustering. Pattern Recognit. Lett. 26(4): 399-410 (2005) - [j45]Jisoo Ham, Yangchi Chen, Melba M. Crawford, Joydeep Ghosh:
Investigation of the random forest framework for classification of hyperspectral data. IEEE Trans. Geosci. Remote. Sens. 43(3): 492-501 (2005) - [c67]Suju Rajan, Kunal Punera, Joydeep Ghosh:
A Maximum Likelihood Framework for Integrating Taxonomies. AAAI 2005: 856-861 - [c66]Kuiyu Chang, Joydeep Ghosh:
Probabilistic Principal Surface Classifier. FSKD (2) 2005: 1236-1244 - [c65]Kunal Punera, Joydeep Ghosh:
CLUMP: A Scalable and Robust Framework for Structure Discovery. ICDM 2005: 757-760 - [c64]Gunjan Gupta, Joydeep Ghosh:
Robust one-class clustering using hybrid global and local search. ICML 2005: 273-280 - [c63]Yangchi Chen, Melba M. Crawford, Joydeep Ghosh:
Applying nonlinear manifold learning to hyperspectral data for land cover classification. IGARSS 2005: 4311-4314 - [c62]Srujana Merugu, Joydeep Ghosh:
A distributed learning framework for heterogeneous data sources. KDD 2005: 208-217 - [c61]Arindam Banerjee, Chase Krumpelman, Joydeep Ghosh, Sugato Basu, Raymond J. Mooney:
Model-based overlapping clustering. KDD 2005: 532-537 - [c60]Suju Rajan, Joydeep Ghosh:
Exploiting Class Hierarchies for Knowledge Transfer in Hyperspectral Data. Multiple Classifier Systems 2005: 417-427 - [c59]Yue Luo, Ajay Joshi, Aashish Phansalkar, Lizy Kurian John, Joydeep Ghosh:
Analyzing and Improving Clustering Based Sampling for Microprocessor Simulation. SBAC-PAD 2005: 193-200 - [c58]Kunal Punera, Suju Rajan, Joydeep Ghosh:
Automatically learning document taxonomies for hierarchical classification. WWW (Special interest tracks and posters) 2005: 1010-1011 - 2004
- [j44]Joseph T. Morgan, Jisoo Ham, Melba M. Crawford, Alex Henneguelle, Joydeep Ghosh:
Adaptive Feature Spaces For Land Cover Classification With Limited Ground Truth Data. Int. J. Pattern Recognit. Artif. Intell. 18(5): 777-799 (2004) - [j43]Arindam Banerjee, Joydeep Ghosh:
Frequency-sensitive competitive learning for scalable balanced clustering on high-dimensional hyperspheres. IEEE Trans. Neural Networks 15(3): 702-719 (2004) - [c57]Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu:
An information theoretic analysis of maximum likelihood mixture estimation for exponential families. ICML 2004 - [c56]Yangchi Chen, Melba M. Crawford, Joydeep Ghosh:
Integrating support vector machines in a hierarchical output space decomposition framework. IGARSS 2004: 949-952 - [c55]Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Srujana Merugu, Dharmendra S. Modha:
A generalized maximum entropy approach to bregman co-clustering and matrix approximation. KDD 2004: 509-514 - [c54]Suju Rajan, Joydeep Ghosh:
An Empirical Comparison of Hierarchical vs. Two-Level Approaches to Multiclass Problems. Multiple Classifier Systems 2004: 283-292 - [c53]Arindam Banerjee, Srujana Merugu, Inderjit S. Dhillon, Joydeep Ghosh:
Clustering with Bregman Divergences. SDM 2004: 234-245 - [c52]Sreangsu Acharyya, Joydeep Ghosh:
Outlink estimation for pagerank computation under missing data. WWW (Alternate Track Papers & Posters) 2004: 486-487 - 2003
- [j42]Alexander Strehl, Joydeep Ghosh:
Relationship-Based Clustering and Visualization for High-Dimensional Data Mining. INFORMS J. Comput. 15(2): 208-230 (2003) - [j41]Shi Zhong, Joydeep Ghosh:
A Unified Framework for Model-based Clustering. J. Mach. Learn. Res. 4: 1001-1037 (2003) - [c51]Srujana Merugu, Joydeep Ghosh:
Privacy-preserving Distributed Clustering using Generative Models. ICDM 2003: 211-218 - [c50]Donna Korycinski, Melba M. Crawford, J. W. Barnes, Joydeep Ghosh:
Adaptive feature selection for hyperspectral data analysis using a binary hierarchical classifier and tabu search. IGARSS 2003: 297-299 - [c49]Alex Henneguelle, Joydeep Ghosh, Melba M. Crawford:
Polyline Feature Extraction for Land Cover Classification using Hyperspectral Data. IICAI 2003: 256-269 - [c48]Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Suvrit Sra:
Generative model-based clustering of directional data. KDD 2003: 19-28 - [c47]Shi Zhong, Joydeep Ghosh:
Scalable, Balanced Model-based Clustering. SDM 2003: 71-82 - 2002
- [j40]Alexander Strehl, Joydeep Ghosh:
Cluster Ensembles --- A Knowledge Reuse Framework for Combining Multiple Partitions. J. Mach. Learn. Res. 3: 583-617 (2002) - [j39]Kagan Tumer, Joydeep Ghosh:
Robust Combining of Disparate Classifiers through Order Statistics. Pattern Anal. Appl. 5(2): 189-200 (2002) - [j38]Shailesh Kumar, Joydeep Ghosh, Melba M. Crawford:
Hierarchical Fusion of Multiple Classifiers for Hyperspectral Data Analysis. Pattern Anal. Appl. 5(2): 210-220 (2002) - [c46]Alexander Strehl, Joydeep Ghosh:
Cluster Ensembles A Knowledge Reuse Framework for Combining Partitionings. AAAI/IAAI 2002: 93-99 - [c45]Joseph T. Morgan, Alex Henneguelle, Melba M. Crawford, Joydeep Ghosh, Amy L. Neuenschwander:
Best bases Bayesian hierarchical classifier for hyperspectral data analysis. IGARSS 2002: 1434-1437 - [c44]Joydeep Ghosh:
Multiclassifier Systems: Back to the Future. Multiple Classifier Systems 2002: 1-15 - [c43]Joseph T. Morgan, Alex Henneguelle, Melba M. Crawford, Joydeep Ghosh, Amy Neuenschwander:
Adaptive Feature Spaces for Land Cover Classification with Limited Ground Truth Data. Multiple Classifier Systems 2002: 189-200 - [c42]Arindam Banerjee, Joydeep Ghosh:
On Scaling Up Balanced Clustering Algorithms. SDM 2002: 333-349 - 2001
- [j37]Kuiyu Chang, Joydeep Ghosh:
A Unified Model for Probabilistic Principal Surfaces. IEEE Trans. Pattern Anal. Mach. Intell. 23(1): 22-41 (2001) - [j36]Shailesh Kumar, Joydeep Ghosh, Melba M. Crawford:
Best-bases feature extraction algorithms for classification of hyperspectral data. IEEE Trans. Geosci. Remote. Sens. 39(7): 1368-1379 (2001) - [c41]Gunjan Gupta, Joydeep Ghosh:
Value-balanced agglomerative connectivity clustering. Data Mining and Knowledge Discovery: Theory, Tools, and Technology 2001: 6-15 - [c40]Sugato Basu, Raymond J. Mooney, Krupakar V. Pasupuleti, Joydeep Ghosh:
Evaluating the novelty of text-mined rules using lexical knowledge. KDD 2001: 233-238 - [c39]Gunjan Gupta, Joydeep Ghosh:
Detecting Seasonal Trends and Cluster Motion Visualization for Very High Dimensional Transactional Data. SDM 2001: 1-17 - 2000
- [j35]Hillol Kargupta, Joydeep Ghosh, Vipin Kumar, Zoran Obradovic:
Report from the Workshop on Distributed and Parallel Knowledge Discovery, ACM SIGKDD-2000. SIGKDD Explor. 2(2): 108-109 (2000) - [c38]Alexander Strehl, Joydeep Ghosh:
Value-based customer grouping from large retail data sets. Data Mining and Knowledge Discovery: Theory, Tools, and Technology 2000: 33-42 - [c37]Alexander Strehl, Joydeep Ghosh:
A Scalable Approach to Balanced, High-Dimensional Clustering of Market-Baskets. HiPC 2000: 525-536 - [c36]Adrian K. Agogino, Joydeep Ghosh, Stavros J. Perantonis, Vassilis Virvilis, Sergios Petridis, Paulo J. G. Lisboa:
The Role of Multiple, Linear-Projection Based Visualization Techniques in RBF-Based Classification of High Dimensional Data. IJCNN (3) 2000: 47-52 - [c35]Shailesh Kumar, Joydeep Ghosh, Melba M. Crawford:
A Hierarchical Multiclassifier System for Hyperspectral Data Analysis. Multiple Classifier Systems 2000: 270-279 - [c34]Wade Schwartzkopf, Thomas E. Milner, Joydeep Ghosh, Brian L. Evans, Alan C. Bovik:
Two-Dimensional Phase Unwrapping Using Neural Networks. SSIAI 2000: 274-277
1990 – 1999
- 1999
- [j34]Kurt D. Bollacker, Joydeep Ghosh:
Effective supra-classifiers for knowledge base construction. Pattern Recognit. Lett. 20(11-13): 1347-1352 (1999) - [j33]Ismail A. Taha, Joydeep Ghosh:
Symbolic Interpretation of Artificial Neural Networks. IEEE Trans. Knowl. Data Eng. 11(3): 448-463 (1999) - [j32]Viswanath Ramamurti, Joydeep Ghosh:
Structurally adaptive modular networks for nonstationary environments. IEEE Trans. Neural Networks 10(1): 152-160 (1999) - [j31]T. Kyuel, Wilson S. Geisler, Joydeep Ghosh:
Retinally reconstructed images: digital images having a resolution match with the human eye. IEEE Trans. Syst. Man Cybern. Part A 29(2): 235-243 (1999) - [j30]Turker Kuyel, Wilson S. Geisler, Joydeep Ghosh:
Fast image classification using a sequence of visual fixations. IEEE Trans. Syst. Man Cybern. Part B 29(2): 304-308 (1999) - [c33]Kyu-Yu Chang, Joydeep Ghosh:
Probabilistic principal surfaces. IJCNN 1999: 1107-1112 - [c32]Adrian K. Agogino, Joydeep Ghosh, Cheryl E. Martin:
Visualization of radial basis function networks. IJCNN 1999: 1199-1202 - [c31]Ian R. Fasel, Kurt D. Bollacker, Joydeep Ghosh:
A neural network based classifier and biofeedback device for improving clarinet tone-quality. IJCNN 1999: 1924-1928 - [c30]Shailesh Kumar, Melba M. Crawford, Joydeep Ghosh:
A versatile framework for labelling imagery with a large number of classes. IJCNN 1999: 2829-2833 - [i3]Kagan Tumer, Joydeep Ghosh:
Robust Combining of Disparate Classifiers through Order Statistics. CoRR cs.LG/9905013 (1999) - [i2]Kagan Tumer, Nirmala Ramanujam, Joydeep Ghosh, Rebecca R. Richards-Kortum:
Ensembles of Radial Basis Function Networks for Spectroscopic Detection of Cervical Pre-Cancer. CoRR cs.NE/9905011 (1999) - [i1]Kagan Tumer, Joydeep Ghosh:
Linear and Order Statistics Combiners for Pattern Classification. CoRR cs.NE/9905012 (1999) - 1998
- [j29]Kagan Tumer, Nirmala Ramanujam, Joydeep Ghosh, Rebecca R. Richards-Kortum:
Ensembles of radial basis function networks for spectroscopic detection of cervical precancer. IEEE Trans. Biomed. Eng. 45(8): 953-961 (1998) - [c29]Turker Kuyel, Wilson S. Geisler, Joydeep Ghosh:
Retinally reconstructed images (RRIs): digital images having a resolution match with the human eye. Human Vision and Electronic Imaging 1998: 603-614 - [c28]Kurt D. Bollacker, Joydeep Ghosh:
A Supra-Classifier Architecture for Scalable Knowledge Reuse. ICML 1998: 64-72 - 1997
- [j28]V. Srinivasa Chakravarthy, Joydeep Ghosh:
On Hebbian-like adaptation in heart muscle: a proposal for 'cardiac memory'. Biol. Cybern. 76(3): 207-215 (1997) - [j27]Bryan W. Stiles, Joydeep Ghosh:
Habituation based neural networks for spatio-temporal classification. Neurocomputing 15(3-4): 273-307 (1997) - [j26]V. Srinivasa Chakravarthy, Joydeep Ghosh:
Function Emulation Using Radial Basis Function Networks. Neural Networks 10(3): 459-478 (1997) - [j25]Kurt D. Bollacker, Joydeep Ghosh:
Knowledge reuse in multiple classifier systems. Pattern Recognit. Lett. 18(11-13): 1385-1390 (1997) - [j24]Bryan W. Stiles, Irwin W. Sandberg, Joydeep Ghosh:
Complete memory structures for approximating nonlinear discrete-time mappings. IEEE Trans. Neural Networks 8(6): 1397-1409 (1997) - [j23]Wassim S. Chaer, Robert H. Bishop, Joydeep Ghosh:
A mixture-of-experts framework for adaptive Kalman filtering. IEEE Trans. Syst. Man Cybern. Part B 27(3): 452-464 (1997) - [c27]Shishir Shah, J. K. Aggarwal, Jayakrishnan Eledath, Joydeep Ghosh:
Multisensor Integration for Scene Classifiction: An Experiment in Human Form Detection. ICIP (2) 1997: 199-202 - [c26]Viswanath Ramamurti, Joydeep Ghosh:
Regularization and error bars for the mixture of experts network. ICNN 1997: 221-225 - [c25]Ismail A. Taha, Joydeep Ghosh:
Evaluation and ordering of rules extracted from feedforward networks. ICNN 1997: 408-413 - [c24]Kurt D. Bollacker, Joydeep Ghosh:
A scalable method for classifier knowledge reuse. ICNN 1997: 1474-1478 - 1996
- [j22]V. Srinivasa Chakravarthy, Joydeep Ghosh:
A complex-valued associative memory for storing patterns as oscillatory states. Biol. Cybern. 75(3): 229-238 (1996) - [j21]Kagan Tumer, Joydeep Ghosh:
Error Correlation and Error Reduction in Ensemble Classifiers. Connect. Sci. 8(3): 385-404 (1996) - [j20]Kagan Tumer, Joydeep Ghosh:
Analysis of decision boundaries in linearly combined neural classifiers. Pattern Recognit. 29(2): 341-348 (1996) - [j19]V. Srinivasa Chakravarthy, Joydeep Ghosh:
Scale-based clustering using the radial basis function network. IEEE Trans. Neural Networks 7(5): 1250-1261 (1996) - [j18]José N. Amaral, Joydeep Ghosh:
A Concurrent Architecture for Serializable Production Systems. IEEE Trans. Parallel Distributed Syst. 7(12): 1265-1280 (1996) - [c23]Viswanath Ramamurti, Joydeep Ghosh:
Advances in using hierarchical mixture of experts for signal classification. ICASSP 1996: 3569-3572 - [c22]Kurt D. Bollacker, Joydeep Ghosh:
Mutual information feature extractors for neural classifiers. ICNN 1996: 1528-1533 - [c21]Kagan Tumer, Joydeep Ghosh:
Estimating the Bayes error rate through classifier combining. ICPR 1996: 695-699 - [c20]Viswanath Ramamurti, Joydeep Ghosh:
Structural adaptation in mixture of experts. ICPR 1996: 704-708 - [c19]Kurt D. Bollacker, Joydeep Ghosh:
Linear feature extractors based on mutual information. ICPR 1996: 720-724 - [c18]Kagan Tumer, Nirmala Ramanujam, Rebecca R. Richards-Kortum, Joydeep Ghosh:
Spectroscopic Detection of Cervical Pre-Cancer through Radial Basis Function Networks. NIPS 1996: 981-987 - 1995
- [j17]Song Chong, San-qi Li, Joydeep Ghosh:
Predictive Dynamic Bandwidth Allocation for Efficient Transport of Real-Time VBR Video over ATM. IEEE J. Sel. Areas Commun. 13(1): 12-23 (1995) - [j16]Yoan Shin, Joydeep Ghosh:
Ridge polynomial networks. IEEE Trans. Neural Networks 6(3): 610-622 (1995) - [j15]José Nelson Amaral, Kagan Tumer, Joydeep Ghosh:
Designing genetic algorithms for the state assignment problem. IEEE Trans. Syst. Man Cybern. 25(4): 687-694 (1995) - [c17]Bryan W. Stiles, Joydeep Ghosh:
Habituation based neural classifiers for spatio-temporal signals. ICASSP 1995: 3407-3410 - [c16]José N. Amaral, Joydeep Ghosh:
Performance measurements of a concurrent production system architecture without global synchronization. IPPS 1995: 790-797 - 1994
- [j14]Jeffrey T. Draper, Joydeep Ghosh:
A Comprehensive Analytical Model for Wormhole Routng in Multicomputer Systems. J. Parallel Distributed Comput. 23(2): 202-214 (1994) - [j13]Jeffrey T. Draper, Joydeep Ghosh:
The M-Cache: A Message-Handling Mechanism for Multicomputer Systems. Parallel Comput. 20(9): 1269-1288 (1994) - [j12]Vijay K. Garg, Joydeep Ghosh:
Repeated Computation of Global Functions in a Distributed Environment. IEEE Trans. Parallel Distributed Syst. 5(8): 823-834 (1994) - [j11]Joydeep Ghosh, Sajal K. Das, Ajita John:
Concurrent Processing of Linearly Ordered Data Structures on Hypercube Multicomputers. IEEE Trans. Parallel Distributed Syst. 5(9): 898-911 (1994) - [j10]Joydeep Ghosh, Anujan Varma, Naveen Krishnamurthy:
Distributed control schemes for fast arbitration in large crossbar networks. IEEE Trans. Very Large Scale Integr. Syst. 2(1): 54-67 (1994) - [c15]Kagan Tumer, Joydeep Ghosh:
Sequence Recognition by Input Anticipation. IEA/AIE 1994: 77-86 - [c14]Song Chong, San-qi Li, Joydeep Ghosh:
Dynamic Bandwidth Allocation for Efficient Transport of Real-Time VBR Video over ATM. INFOCOM 1994: 81-90 - [c13]Joydeep Ghosh, Patrick LaCour, Spence Jackson:
OTA Based Neural Network Architectures with On-Chip Tuning of Synapses. VLSI Design 1994: 71-76 - 1993
- [j9]Hung-Jen Chang, Joydeep Ghosh:
Pattern association and retrieval in a continuous neural system. Biol. Cybern. 69(1): 77-86 (1993) - [j8]Joydeep Ghosh, Kelvin D. Goveas, Jeffrey T. Draper:
Performance Evaluation of a Parallel I/O Subsystem for Hypercube Multicomputers. J. Parallel Distributed Comput. 17(1-2): 90-106 (1993) - [c12]Joydeep Ghosh, Shaoyun Wang:
A temporal memory network with state-dependent thresholds. ICNN 1993: 359-364 - [c11]Kunio Iwata, Joydeep Ghosh, Yoan Shin:
Time optimal control using pi-sigma networks. ICNN 1993: 546-551 - [c10]Joydeep Ghosh, Nari Krishnamurthy:
Fault-Tolerant Arbitration in Multichip Crossbar Switches. VLSI Design 1993: 351-356 - 1992
- [j7]Sajal K. Das, Joydeep Ghosh, Narsingh Deo:
Stirling Networks: A Versatile Combinatorial Topology for Multiprocessor Systems. Discret. Appl. Math. 37/38: 119-146 (1992) - [j6]Hung-Jen Chang, Joydeep Ghosh, Kadir Liano:
A Macroscopic Model of Neural Ensembles: Learning-Induced Oscillations in a Cell Assembly. Int. J. Neural Syst. 3(2): 179-198 (1992) - [j5]Joydeep Ghosh, Yoan Shin:
Efficient Higher-Order Neural Networks for Classification and Function Approximation. Int. J. Neural Syst. 3(4): 323-350 (1992) - [c9]Jeffrey T. Draper, Joydeep Ghosh:
Multipath E-Cube Algorithms (MECA) for Adaptive Wormhole Routing and Broadcasting in itk-ary itn-Cubes. IPPS 1992: 407-410 - 1991
- [c8]Joydeep Ghosh, Bipul Agarwal:
Parallel I/O Subsystems for Distributed-Memory Multicomputers. IPPS 1991: 381-384 - [c7]Jeffrey T. Draper, Joydeep Ghosh, William C. Athas:
The M-cache: a message-retrieving mechanism for multicomputer systems. SPDP 1991: 258-265 - 1990
- [j4]Anujan Varma, Joydeep Ghosh, Christos J. Georgiou:
Rearrangeable operation of large crosspoint switching networks. IEEE Trans. Commun. 38(9): 1616-1624 (1990) - [c6]Joydeep Ghosh, Anujan Varma:
Reliable design of multichip nonblocking crossbars. ICCD 1990: 70-73 - [c5]Vijay K. Garg, Joydeep Ghosh:
Symmetry in Spite of Hierarchy. ICDCS 1990: 4-11 - [c4]Joydeep Ghosh, Richard L. Holmberg:
Multisensor fusion using neural networks. SPDP 1990: 812-815
1980 – 1989
- 1989
- [j3]Joydeep Ghosh, Kai Hwang:
Mapping Neural Networks onto Message-Passing Multicomputers. J. Parallel Distributed Comput. 6(2): 291-330 (1989) - 1988
- [c3]Anujan Varma, Joydeep Ghosh, Christos J. Georgiou:
Reliable design of large crosspoint switching networks. FTCS 1988: 320-325 - [c2]Joydeep Ghosh, Kai Hwang:
Critical Issues in Mapping Neural Networks on Message-Passing Multicomputers. ISCA 1988: 3-11 - 1987
- [j2]Kai Hwang, Joydeep Ghosh, Raymond Chowkwanyun:
Computer Architectures for Artificial Intelligence Processing. Computer 20(1): 19-27 (1987) - [j1]Kai Hwang, Joydeep Ghosh:
Hypernet: A Communication-Efficient Architecture for Constructing Massively Parallel Computers. IEEE Trans. Computers 36(12): 1450-1466 (1987) - [c1]Kai Hwang, Joydeep Ghosh:
Hypernet Architectures for Parallel Processing. ICPP 1987: 810-819
Coauthor Index
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