Dharmashankar Subramanian

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 44

Top Topics

Top Venues

Publications

Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers. CoRR (2024)
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)
Xiao Shou, Dharmashankar Subramanian, Debarun Bhattacharjya, Tian Gao, Kristin P. Bennett
Self-Supervised Contrastive Pre-Training for Multivariate Point Processes. CoRR (2024)
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 (2024)
Xiao Shou, Tian Gao, Dharmashankar Subramanian, Debarun Bhattacharjya, Kristin P. Bennett
Influence-Aware Attention for Multivariate Temporal Point Processes. CLeaR (2023)
Xiao Shou, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Oktie Hassanzadeh, Kristin P. Bennett
Probabilistic Attention-to-Influence Neural Models for Event Sequences. ICML (2023)
Xiao Shou, Tian Gao, Dharmashankar Subramanian, Debarun Bhattacharjya, Kristin P. Bennett
Concurrent Multi-Label Prediction in Event Streams. AAAI (2023)
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)
Weiqin Chen, Dharmashankar Subramanian, Santiago Paternain
Probabilistic Constraint for Safety-Critical Reinforcement Learning. CoRR (2023)
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 (2023)
Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian
The Information Pathways Hypothesis: Transformers are Dynamic Self-Ensembles. CoRR (2023)
Xiao Shou, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Oktie Hassanzadeh, Kristin P. Bennett
Pairwise Causality Guided Transformers for Event Sequences. NeurIPS (2023)
Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian
The Information Pathways Hypothesis: Transformers are Dynamic Self-Ensembles. KDD (2023)
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)
Elita Lobo, Oktie Hassanzadeh, Nhan Pham, Nandana Mihindukulasooriya, Dharmashankar Subramanian, Horst Samulowitz
Matching Table Metadata with Business Glossaries Using Large Language Models. CoRR (2023)
Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Xiao Shou
Score-Based Learning of Graphical Event Models with Background Knowledge Augmentation. AAAI (2023)
Elita Lobo, Oktie Hassanzadeh, Nhan Pham, Nandana Mihindukulasooriya, Dharmashankar Subramanian, Horst Samulowitz
Matching table metadata with business glossaries using large language models. OM@ISWC (2023)
Weiqin Chen, Dharmashankar Subramanian, Santiago Paternain
Policy Gradients for Probabilistic Constrained Reinforcement Learning. CISS (2023)
Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian
Global Self-Attention as a Replacement for Graph Convolution. KDD (2022)
Yuan-Chi Chang, Dharmashankar Subramanian, Raju Pavuluri, Timothy Dinger
Time Series Representation Learning with Contrastive Triplet Selection. COMAD/CODS (2022)
Karan Samel, Zelin Zhao, Binghong Chen, Shuang Li, Dharmashankar Subramanian, Irfan Essa, Le Song
Learning Temporal Rules from Noisy Timeseries Data. CoRR (2022)
Weiqin Chen, Dharmashankar Subramanian, Santiago Paternain
Policy Gradients for Probabilistic Constrained Reinforcement Learning. CoRR (2022)
Debarun Bhattacharjya, Karthikeyan Shanmugam, Tian Gao, Dharmashankar Subramanian
Process Independence Testing in Proximal Graphical Event Models. CLeaR (2022)
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) (2022)
Pavithra Harsha, Ramesh Natarajan, Dharmashankar Subramanian
A Prescriptive Machine-Learning Framework to the Price-Setting Newsvendor Problem. INFORMS J. Optim. 3 (3) (2021)
Tian Gao, Dharmashankar Subramanian, Debarun Bhattacharjya, Xiao Shou, Nicholas Mattei, Kristin P. Bennett
Causal Inference for Event Pairs in Multivariate Point Processes. NeurIPS (2021)
Victoria Kusherbaeva, Nianjun Zhou, Dharmashankar Subramanian
Interpretable Multi-Step Production Optimization Utilizing IoT Sensor Data. WF-IoT (2021)
Md. Shamim Hussain, Mohammed J. Zaki, Dharmashankar Subramanian
Edge-augmented Graph Transformers: Global Self-attention is Enough for Graphs. CoRR (2021)
Xiao Shou, Tian Gao, Dharmashankar Subramanian, Kristin P. Bennett
Match2: hybrid self-organizing map and deep learning strategies for treatment effect estimation. BCB (2021)
Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian
Ordinal Historical Dependence in Graphical Event Models with Tree Representations. AAAI (2021)
Debarun Bhattacharjya, Tian Gao, Nicholas Mattei, Dharmashankar Subramanian
Cause-Effect Association between Event Pairs in Event Datasets. IJCAI (2020)
Tian Gao, Dharmashankar Subramanian, Karthikeyan Shanmugam, Debarun Bhattacharjya, Nicholas Mattei
A Multi-Channel Neural Graphical Event Model with Negative Evidence. AAAI (2020)
Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian
Order-Dependent Event Models for Agent Interactions. IJCAI (2020)
Xiufan Yu, Karthikeyan Shanmugam, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Lingzhou Xue
Hawkesian Graphical Event Models. PGM (2020)
Tian Gao, Dharmashankar Subramanian, Karthikeyan Shanmugam, Debarun Bhattacharjya, Nicholas Mattei
A Multi-Channel Neural Graphical Event Model with Negative Evidence. CoRR (2020)
Mengyang Gu, Debarun Bhattacharjya, Dharmashankar Subramanian
GaSPing for Utility. AAAI (2020)
Debarun Bhattacharjya, Dharmashankar Subramanian, Tian Gao
State Variable Effects in Graphical Event Models. IJCAI (2020)
Debarun Bhattacharjya, Karthikeyan Shanmugam, Tian Gao, Nicholas Mattei, Kush R. Varshney, Dharmashankar Subramanian
Event-Driven Continuous Time Bayesian Networks. AAAI (2020)
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)
Debarun Bhattacharjya, Dharmashankar Subramanian, Tian Gao
Proximal Graphical Event Models. NeurIPS (2018)
Dharmashankar Subramanian, Debarun Bhattacharjya, Lav R. Varshney
Generalization across Contexts in Unsupervised Computational Creativity. ICCC (2018)
Dharmashankar Subramanian, Lucia L. Titus
A generative stochastic graphical model for simulating social protest. WSC (2017)
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)
Dan Andrei Iancu, Marek Petrik, Dharmashankar Subramanian
Tight Approximations of Dynamic Risk Measures. Math. Oper. Res. 40 (3) (2015)
Marek Petrik, Dharmashankar Subramanian
RAAM: The Benefits of Robustness in Approximating Aggregated MDPs in Reinforcement Learning. NIPS (2014)
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)
Marek Petrik, Dharmashankar Subramanian, Janusz Marecki
Solution Methods for Constrained Markov Decision Process with Continuous Probability Modulation. UAI (2013)
Marek Petrik, Dharmashankar Subramanian, Janusz Marecki
Solution Methods for Constrained Markov Decision Process with Continuous Probability Modulation. CoRR (2013)
Ban Kawas, Mark S. Squillante, Dharmashankar Subramanian, Kush R. Varshney
Prescriptive Analytics for Allocating Sales Teams to Opportunities. ICDM Workshops (2013)
Pu Huang, Dharmashankar Subramanian
Iterative estimation maximization for stochastic linear programs with conditional value-at-risk constraints. Comput. Manag. Sci. 9 (4) (2012)
Marek Petrik, Dharmashankar Subramanian
An Approximate Solution Method for Large Risk-Averse Markov Decision Processes. UAI (2012)
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) (2012)
Marek Petrik, Dharmashankar Subramanian
An Approximate Solution Method for Large Risk-Averse Markov Decision Processes CoRR (2012)
Pu Huang, Dharmashankar Subramanian, Jie Xu
An importance sampling method for portfolio CVaR estimation with Gaussian copula models. WSC (2010)
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) (2010)
Dharmashankar Subramanian, Lianjun An
Optimal Resource Action Planning Analytics for Services Delivery Using Hiring, Contracting & Cross-Training of Various Skills. IEEE SCC (1) (2008)
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) (2007)
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) (2007)
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)
Dharmashankar Subramanian, Nitin Lamba
A nonlinear model predictive control solution for a hybrid dynamic system: NASA life support system. ACC (2005)
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)
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) (2003)