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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]