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ORCIDDharmashankar Subramanian
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2020 – today
- 2025
[i15]Michael R. Glass, Mustafa Eyceoz, Dharmashankar Subramanian, Gaetano Rossiello, Long Vu, Alfio Gliozzo:
Extractive Schema Linking for Text-to-SQL. CoRR abs/2501.17174 (2025)- [i14]Gaetano Rossiello, Nhan Pham, Michael R. Glass, Junkyu Lee, Dharmashankar Subramanian:
Rationalization Models for Text-to-SQL. CoRR abs/2502.06759 (2025) - 2024
- [j11]Weiqin Chen
, Dharmashankar Subramanian, Santiago Paternain:
Probabilistic Constraint for Safety-Critical Reinforcement Learning. IEEE Trans. Autom. Control. 69(10): 6789-6804 (2024) - [c40]Weiqin Chen, James Onyejizu, Long Vu, Lan Hoang, Dharmashankar Subramanian, Koushik Kar, Sandipan Mishra, Santiago Paternain:
Adaptive Primal-Dual Method for Safe Reinforcement Learning. AAMAS 2024: 326-334 - [c39]Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian:
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers. ICML 2024 - [i13]Weiqin Chen, James Onyejizu, Long Vu, Lan Hoang, Dharmashankar Subramanian, Koushik Kar, Sandipan Mishra, Santiago Paternain:
Adaptive Primal-Dual Method for Safe Reinforcement Learning. CoRR abs/2402.00355 (2024) - [i12]Xiao Shou, Dharmashankar Subramanian, Debarun Bhattacharjya, Tian Gao, Kristin P. Bennett:
Self-Supervised Contrastive Pre-Training for Multivariate Point Processes. CoRR abs/2402.00987 (2024) - [i11]Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian:
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers. CoRR abs/2402.04538 (2024) - 2023
- [c38]Xiao Shou, Tian Gao, Dharmashankar Subramanian, Debarun Bhattacharjya, Kristin P. Bennett:
Concurrent Multi-Label Prediction in Event Streams. AAAI 2023: 9820-9828 - [c37]Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Xiao Shou:
Score-Based Learning of Graphical Event Models with Background Knowledge Augmentation. AAAI 2023: 12189-12197 - [c36]Weiqin Chen, Dharmashankar Subramanian, Santiago Paternain:
Policy Gradients for Probabilistic Constrained Reinforcement Learning. CISS 2023: 1-6 - [c35]Xiao Shou, Tian Gao, Dharmashankar Subramanian, Debarun Bhattacharjya, Kristin P. Bennett:
Influence-Aware Attention for Multivariate Temporal Point Processes. CLeaR 2023: 499-517 - [c34]Xiao Shou, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Oktie Hassanzadeh, Kristin P. Bennett:
Probabilistic Attention-to-Influence Neural Models for Event Sequences. ICML 2023: 31657-31674 - [c33]Daniel Karl I. Weidele, Shazia Afzal, Abel N. Valente, Cole Makuch, Owen Cornec, Long Vu, Dharmashankar Subramanian, Werner Geyer, Rahul Nair, Inge Vejsbjerg, Radu Marinescu, Paulito P. Palmes, Elizabeth M. Daly, Loraine Franke, Daniel Haehn:
AutoDOViz: Human-Centered Automation for Decision Optimization. IUI 2023: 664-680 - [c32]Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian:
The Information Pathways Hypothesis: Transformers are Dynamic Self-Ensembles. KDD 2023: 810-821 - [c31]Xiao Shou, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Oktie Hassanzadeh, Kristin P. Bennett:
Pairwise Causality Guided Transformers for Event Sequences. NeurIPS 2023 - [c30]Elita A. Lobo, Oktie Hassanzadeh, Nhan Pham, Nandana Mihindukulasooriya, Dharmashankar Subramanian, Horst Samulowitz:
Matching table metadata with business glossaries using large language models. OM@ISWC 2023: 25-36 - [c29]Nandana Mihindukulasooriya, Sarthak Dash, Sugato Bagchi, Md. Faisal Mahbub Chowdhury, Alfio Massimiliano Gliozzo, Ariel Farkash, Michael R. Glass, Igor Gokhman, Oktie Hassanzadeh, Nhan Pham, Gaetano Rossiello, Boris Rozenberg, Yehoshua Sagron, Dharmashankar Subramanian, Toshihiro Takahashi, Takaaki Tateishi, Long Vu:
Unleashing the Potential of Data Lakes with Semantic Enrichment Using Foundation Models. ISWC (Posters/Demos/Industry) 2023 - [i10]Daniel Karl I. Weidele, Shazia Afzal, Abel N. Valente, Cole Makuch, Owen Cornec, Long Vu, Dharmashankar Subramanian, Werner Geyer, Rahul Nair, Inge Vejsbjerg, Radu Marinescu, Paulito P. Palmes, Elizabeth M. Daly, Loraine Franke, Daniel Haehn:
AutoDOViz: Human-Centered Automation for Decision Optimization. CoRR abs/2302.09688 (2023) - [i9]Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian:
The Information Pathways Hypothesis: Transformers are Dynamic Self-Ensembles. CoRR abs/2306.01705 (2023) - [i8]Weiqin Chen, Dharmashankar Subramanian, Santiago Paternain:
Probabilistic Constraint for Safety-Critical Reinforcement Learning. CoRR abs/2306.17279 (2023) - [i7]Elita A. Lobo, Oktie Hassanzadeh, Nhan Pham, Nandana Mihindukulasooriya, Dharmashankar Subramanian, Horst Samulowitz:
Matching Table Metadata with Business Glossaries Using Large Language Models. CoRR abs/2309.11506 (2023) - 2022
- [j10]Jayant Kalagnanam, Dzung T. Phan, Pavankumar Murali, Lam M. Nguyen, Nianjun Zhou, Dharmashankar Subramanian, Raju Pavuluri, Xiang Ma, Crystal Lui, Giovane Cesar Da Silva:
AI-Based Real-Time Site-Wide Optimization for Process Manufacturing. INFORMS J. Appl. Anal. 52(4): 363-378 (2022) - [c28]Debarun Bhattacharjya, Karthikeyan Shanmugam, Tian Gao, Dharmashankar Subramanian:
Process Independence Testing in Proximal Graphical Event Models. CLeaR 2022: 144-161 - [c27]Yuan-Chi Chang, Dharmashankar Subramanian, Raju Pavuluri, Timothy Dinger:
Time Series Representation Learning with Contrastive Triplet Selection. COMAD/CODS 2022: 46-53 - [c26]Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian:
Global Self-Attention as a Replacement for Graph Convolution. KDD 2022: 655-665 - [i6]Karan Samel, Zelin Zhao, Binghong Chen, Shuang Li, Dharmashankar Subramanian, Irfan Essa, Le Song:
Learning Temporal Rules from Noisy Timeseries Data. CoRR abs/2202.05403 (2022) - [i5]Weiqin Chen, Dharmashankar Subramanian, Santiago Paternain:
Policy Gradients for Probabilistic Constrained Reinforcement Learning. CoRR abs/2210.00596 (2022) - 2021
- [j9]Pavithra Harsha, Ramesh Natarajan, Dharmashankar Subramanian:
A Prescriptive Machine-Learning Framework to the Price-Setting Newsvendor Problem. INFORMS J. Optim. 3(3): 227-253 (2021) - [c25]Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian:
Ordinal Historical Dependence in Graphical Event Models with Tree Representations. AAAI 2021: 6759-6767 - [c24]Xiao Shou, Tian Gao, Dharmashankar Subramanian, Kristin P. Bennett:
Match2: hybrid self-organizing map and deep learning strategies for treatment effect estimation. BCB 2021: 46:1-46:10 - [c23]Tian Gao, Dharmashankar Subramanian, Debarun Bhattacharjya, Xiao Shou, Nicholas Mattei, Kristin P. Bennett:
Causal Inference for Event Pairs in Multivariate Point Processes. NeurIPS 2021: 17311-17324 - [c22]Victoria Kusherbaeva, Nianjun Zhou, Dharmashankar Subramanian:
Interpretable Multi-Step Production Optimization Utilizing IoT Sensor Data. WF-IoT 2021: 118-123 - [i4]Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian:
Edge-augmented Graph Transformers: Global Self-attention is Enough for Graphs. CoRR abs/2108.03348 (2021) - 2020
- [c21]Mengyang Gu, Debarun Bhattacharjya, Dharmashankar Subramanian:
GaSPing for Utility. AAAI 2020: 2637-2644 - [c20]Debarun Bhattacharjya, Karthikeyan Shanmugam, Tian Gao, Nicholas Mattei, Kush R. Varshney, Dharmashankar Subramanian:
Event-Driven Continuous Time Bayesian Networks. AAAI 2020: 3259-3266 - [c19]Tian Gao, Dharmashankar Subramanian, Karthikeyan Shanmugam, Debarun Bhattacharjya, Nicholas Mattei:
A Multi-Channel Neural Graphical Event Model with Negative Evidence. AAAI 2020: 3946-3953 - [c18]Debarun Bhattacharjya, Tian Gao, Nicholas Mattei, Dharmashankar Subramanian:
Cause-Effect Association between Event Pairs in Event Datasets. IJCAI 2020: 1202-1208 - [c17]Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian:
Order-Dependent Event Models for Agent Interactions. IJCAI 2020: 1977-1983 - [c16]Debarun Bhattacharjya, Dharmashankar Subramanian, Tian Gao:
State Variable Effects in Graphical Event Models. IJCAI 2020: 4291-4297 - [c15]Xiufan Yu, Karthikeyan Shanmugam, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Lingzhou Xue:
Hawkesian Graphical Event Models. PGM 2020: 569-580 - [i3]Tian Gao, Dharmashankar Subramanian, Karthikeyan Shanmugam, Debarun Bhattacharjya, Nicholas Mattei:
A Multi-Channel Neural Graphical Event Model with Negative Evidence. CoRR abs/2002.09575 (2020)
2010 – 2019
- 2019
- [c14]Dharmashankar Subramanian, Pavankumar Murali, Nianjun Zhou, Xiang Ma, Giovane Cesar Da Silva, Raju Pavuluri, Jayant Kalagnanam:
A Prediction-Optimization Framework for Site-Wide Process Optimization. ICIOT 2019: 125-132 - 2018
- [c13]Dharmashankar Subramanian, Debarun Bhattacharjya, Lav R. Varshney:
Generalization across Contexts in Unsupervised Computational Creativity. ICCC 2018: 40-47 - [c12]Debarun Bhattacharjya, Dharmashankar Subramanian, Tian Gao:
Proximal Graphical Event Models. NeurIPS 2018: 8147-8156 - 2017
- [c11]Dharmashankar Subramanian, Debarun Bhattacharjya, Ruben Rodriguez Torrado, Jeffrey O. Kephart, Vijil Chenthamarakshan, Jesus Rios:
A cognitive assistant for risk identification and modeling. IEEE BigData 2017: 1570-1579 - [c10]Dharmashankar Subramanian, Lucia L. Titus:
A generative stochastic graphical model for simulating social protest. WSC 2017: 4396-4407 - 2015
- [j8]Dan Andrei Iancu, Marek Petrik, Dharmashankar Subramanian:
Tight Approximations of Dynamic Risk Measures. Math. Oper. Res. 40(3): 655-682 (2015) - 2014
- [j7]Jesus Rios, Konstantin Anikeev, M. J. Richard, Shubir Kapoor, Bonnie K. Ray, Christian Toft-Nielsen, Dharmashankar Subramanian, Chen Jiang, Youssef Drissi, Jing Fu:
A framework for strategic financial risk management. IBM J. Res. Dev. 58(4) (2014) - [c9]Marek Petrik, Dharmashankar Subramanian:
RAAM: The Benefits of Robustness in Approximating Aggregated MDPs in Reinforcement Learning. NIPS 2014: 1979-1987 - 2013
- [c8]Ban Kawas, Mark S. Squillante, Dharmashankar Subramanian, Kush R. Varshney:
Prescriptive Analytics for Allocating Sales Teams to Opportunities. ICDM Workshops 2013: 211-218 - [c7]Marek Petrik, Dharmashankar Subramanian, Janusz Marecki:
Solution Methods for Constrained Markov Decision Process with Continuous Probability Modulation. UAI 2013 - [i2]Marek Petrik, Dharmashankar Subramanian, Janusz Marecki:
Solution Methods for Constrained Markov Decision Process with Continuous Probability Modulation. CoRR abs/1309.6857 (2013) - 2012
- [j6]Pu Huang, Dharmashankar Subramanian:
Iterative estimation maximization for stochastic linear programs with conditional value-at-risk constraints. Comput. Manag. Sci. 9(4): 441-458 (2012) - [j5]Shubir Kapoor, Bonnie K. Ray, Christian Toft-Nielsen, Kolja Dobrindt, Konstantin Anikeev, Dharmashankar Subramanian, Youssef Drissi, Chen Jiang, Jing Fu:
Enterprise transformation: An analytics-based approach to strategic planning. IBM J. Res. Dev. 56(6): 9 (2012) - [c6]Marek Petrik, Dharmashankar Subramanian:
An Approximate Solution Method for Large Risk-Averse Markov Decision Processes. UAI 2012: 805-814 - [i1]Marek Petrik, Dharmashankar Subramanian:
An Approximate Solution Method for Large Risk-Averse Markov Decision Processes. CoRR abs/1210.4901 (2012) - 2010
- [j4]Dharmashankar Subramanian, Pu Huang, C. Pulavarthi, Jie Xu, H. Sekhar, S. Zhan, S. Tripathi, S. Kumar:
Risk-adjusted approach to optimize investments in product development portfolios. IBM J. Res. Dev. 54(3): 9 (2010) - [c5]Pu Huang, Dharmashankar Subramanian, Jie Xu:
An importance sampling method for portfolio CVaR estimation with Gaussian copula models. WSC 2010: 2790-2800
2000 – 2009
- 2008
- [c4]Dharmashankar Subramanian, Lianjun An:
Optimal Resource Action Planning Analytics for Services Delivery Using Hiring, Contracting & Cross-Training of Various Skills. IEEE SCC (1) 2008: 433-440 - 2007
- [j3]Naoki Abe, Rama Akkiraju, Stephen J. Buckley, Markus Ettl, Pu Huang, Dharmashankar Subramanian, Fateh Tipu:
On optimizing the selection of business transformation projects. IBM Syst. J. 46(4): 777-795 (2007) - [j2]Sonja Glavaski, Dharmashankar Subramanian, Kartik B. Ariyur, Ranjana Ghosh, Nitin Lamba, Antonis Papachristodoulou:
A Nonlinear Hybrid Life Support System: Dynamic Modeling, Control Design, and Safety Verification. IEEE Trans. Control. Syst. Technol. 15(6): 1003-1017 (2007) - 2006
- [c3]Francesco Borrelli, Dharmashankar Subramanian, Arvind U. Raghunathan, Lorenz T. Biegler:
MILP and NLP Techniques for centralized trajectory planning of multiple unmanned air vehicles. ACC 2006: 1-6 - 2005
- [c2]Dharmashankar Subramanian, Nitin Lamba:
A nonlinear model predictive control solution for a hybrid dynamic system: NASA life support system. ACC 2005: 2781-2786 - 2004
- [c1]Dharmashankar Subramanian, Kartik B. Ariyur, Nitin Lamba, Ranjana Deshpande, Sonja Glavaski:
Control Design for a Hybrid Dynamic System: A NASA Life Support System. HSCC 2004: 570-584 - 2003
- [j1]Vishal A. Varma, Joseph F. Pekny, Gintaras V. Reklaitis, Dharmashankar Subramanian:
An XML-based language for the Research & Development pipeline management problem. Comput. Chem. Eng. 27(10): 1361-1379 (2003)
Coauthor Index
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