Karthikeyan Shanmugam

192 papers A* 43A 15B 8Misc 2Journal 105Unranked 19

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Personalized Exercise Assistant using Reinforcement Learning (PEARL): Results from a four-arm Randomized-controlled Trial. CoRR Amy A. Lee, Narayan Hegde, Nina Deliu, Emily Rosenzweig, Arun Suggala, Sriram Lakshminarasimhan, Qian He, John Hernandez, Martin Seneviratne, Rahul Singh, Pradnesh Kalkar, Karthikeyan Shanmugam, Aravindan Raghuveer, Abhimanyu Singh, My Nguyen, James Taylor, Jatin Alla, Sofia S. Villar, Hülya Emir-Farinas
2025	A	`conf`	Bayesian Collaborative Bandits with Thompson Sampling for Improved Outreach in Maternal Health. AAMAS Arpan Dasgupta, Gagan Jain, Arun Suggala, Karthikeyan Shanmugam, Milind Tambe, Aparna Taneja
2025	J	`jnl`	Combinatorial Multi-armed Bandits: Arm Selection via Group Testing. Trans. Mach. Learn. Res. Arpan Mukherjee, Shashanka Ubaru, Keerthiram Murugesan, Karthikeyan Shanmugam, Ali Tajer
2025	A*	`conf`	Does Safety Training of LLMs Generalize to Semantically Related Natural Prompts? ICLR Sravanti Addepalli, Yerram Varun, Arun Suggala, Karthikeyan Shanmugam, Prateek Jain
2025	J	`jnl`	Efficient Approximate Posterior Sampling with Annealed Langevin Monte Carlo. CoRR Advait Parulekar, Litu Rout, Karthikeyan Shanmugam, Sanjay Shakkottai
2025	J	`jnl`	Fine-Tuning Diffusion Models via Intermediate Distribution Shaping. CoRR Gautham Govind Anil, Shaan Ul Haque, Nithish Kannen, Dheeraj Nagaraj, Sanjay Shakkottai, Karthikeyan Shanmugam
2025	A*	`conf`	Glauber Generative Model: Discrete Diffusion Models via Binary Classification. ICLR Harshit Varma, Dheeraj Mysore Nagaraj, Karthikeyan Shanmugam
2025	J	`jnl`	Interleaved Gibbs Diffusion for Constrained Generation. CoRR Gautham Govind Anil, Sachin Yadav, Dheeraj Nagaraj, Karthikeyan Shanmugam, Prateek Jain
2025	J	`jnl`	Learning to Call: A Field Trial of a Collaborative Bandit Algorithm for Improved Message Delivery in Mobile Maternal Health. CoRR Arpan Dasgupta, Mizhaan Maniyar, Awadhesh Srivastava, Sanat Kumar, Amrita Mahale, Aparna Hegde, Arun Sai Suggala, Karthikeyan Shanmugam, Aparna Taneja, Milind Tambe
2025	—	`conf`	Learning to Call: A Field Trial of a Collaborative Bandit Algorithm for Optimizing Call Timing in Mobile Maternal Health. MLHC Arpan Dasgupta, Mizhaan Maniyar, Awadhesh Srivastava, Sanat Kumar, Amrita Mahale, Aparna Hegde, Arun Suggala, Karthikeyan Shanmugam, Milind Tambe, Aparna Taneja
2025	A*	`conf`	Online Bidding under RoS Constraints without Knowing the Value. WWW Sushant Vijayan, Zhe Feng, Swati Padmanabhan, Karthikeyan Shanmugam, Arun Suggala, Di Wang
2025	J	`jnl`	Online Bidding under RoS Constraints without Knowing the Value. CoRR Sushant Vijayan, Zhe Feng, Swati Padmanabhan, Karthikeyan Shanmugam, Arun Suggala, Di Wang
2025	J	`jnl`	Path-specific effects for pulse-oximetry guided decisions in critical care. CoRR Kevin Zhang, Yonghan Jung, Divyat Mahajan, Karthikeyan Shanmugam, Shalmali Joshi
2025	J	`jnl`	Preference-centric Bandits: Optimality of Mixtures and Regret-efficient Algorithms. CoRR Meltem Tatli, Arpan Mukherjee, Prashanth L. A., Karthikeyan Shanmugam, Ali Tajer
2025	J	`jnl`	ROPES: Robotic Pose Estimation via Score-Based Causal Representation Learning. CoRR Pranamya Kulkarni, Puranjay Datta, Burak Varici, Emre Acartürk, Karthikeyan Shanmugam, Ali Tajer
2025	J	`jnl`	Regret minimization in Linear Bandits with offline data via extended D-optimal exploration. CoRR Sushant Vijayan, Arun Suggala, Karthikeyan Shanmugam, Soumyabrata Pal
2025	J	`jnl`	Representation Learning Preserving Ignorability and Covariate Matching for Treatment Effects. CoRR Praharsh Nanavati, Ranjitha Prasad, Karthikeyan Shanmugam
2025	A	`conf`	Risk-sensitive Bandits: Arm Mixture Optimality and Regret-efficient Algorithms. AISTATS Meltem Tatli, Arpan Mukherjee, Prashanth L. A., Karthikeyan Shanmugam, Ali Tajer
2025	J	`jnl`	Risk-sensitive Bandits: Arm Mixture Optimality and Regret-efficient Algorithms. CoRR Meltem Tatli, Arpan Mukherjee, Prashanth L. A., Karthikeyan Shanmugam, Ali Tajer
2025	J	`jnl`	Robust Reward Modeling via Causal Rubrics. CoRR Pragya Srivastava, Harman Singh, Rahul Madhavan, Gandharv Patil, Sravanti Addepalli, Arun Suggala, Rengarajan Aravamudhan, Soumya Sharma, Anirban Laha, Aravindan Raghuveer, Karthikeyan Shanmugam, Doina Precup
2025	J	`jnl`	Score-based Causal Representation Learning: Linear and General Transformations. J. Mach. Learn. Res. Burak Varici, Emre Acartürk, Karthikeyan Shanmugam, Abhishek Kumar, Ali Tajer
2025	J	`jnl`	Segmentation-Aware Latent Diffusion for Satellite Image Super-Resolution: Enabling Smallholder Farm Boundary Delineation. CoRR Aditi Agarwal, Anjali Jain, Nikita Saxena, Ishan Deshpande, Michal Kazmierski, Abigail Annkah, Nadav Sherman, Karthikeyan Shanmugam, Alok Talekar, Vaibhav Rajan
2024	J	`jnl`	A Lyapunov Theory for Finite-Sample Guarantees of Markovian Stochastic Approximation. Oper. Res. Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam
2024	J	`jnl`	A resource-constrained stochastic scheduling algorithm for homeless street outreach and gleaning edible food. CoRR Conor M. Artman, Aditya Mate, Ezinne Nwankwo, Aliza Heching, Tsuyoshi Idé, Jirí Navrátil, Karthikeyan Shanmugam, Wei Sun, Kush R. Varshney, Lauri Goldkind, Gidi Kroch, Jaclyn Sawyer, Ian Watson
2024	J	`jnl`	Attribute Graphs Underlying Molecular Generative Models: Path to Learning with Limited Data. Trans. Mach. Learn. Res. Samuel C. Hoffman, Payel Das, Karthikeyan Shanmugam, Kahini Wadhawan, Prasanna Sattigeri
2024	J	`jnl`	Bandits with Mean Bounds. Trans. Mach. Learn. Res. Nihal Sharma, Soumya Basu, Karthikeyan Shanmugam, Sanjay Shakkottai
2024	J	`jnl`	Bandits with Stochastic Experts: Constant Regret, Empirical Experts and Episodes. ACM Trans. Model. Perform. Evaluation Comput. Syst. Nihal Sharma, Rajat Sen, Soumya Basu, Karthikeyan Shanmugam, Sanjay Shakkottai
2024	J	`jnl`	Bayesian Collaborative Bandits with Thompson Sampling for Improved Outreach in Maternal Health Program. CoRR Arpan Dasgupta, Gagan Jain, Arun Suggala, Karthikeyan Shanmugam, Milind Tambe, Aparna Taneja
2024	J	`jnl`	Combinatorial Multi-armed Bandits: Arm Selection via Group Testing. CoRR Arpan Mukherjee, Shashanka Ubaru, Keerthiram Murugesan, Karthikeyan Shanmugam, Ali Tajer
2024	J	`jnl`	Does Safety Training of LLMs Generalize to Semantically Related Natural Prompts? CoRR Sravanti Addepalli, Yerram Varun, Arun Suggala, Karthikeyan Shanmugam, Prateek Jain
2024	A*	`conf`	Fairness under Covariate Shift: Improving Fairness-Accuracy Tradeoff with Few Unlabeled Test Samples. AAAI Shreyas Havaldar, Jatin Chauhan, Karthikeyan Shanmugam, Jay Nandy, Aravindan Raghuveer
2024	A	`conf`	General Identifiability and Achievability for Causal Representation Learning. AISTATS Burak Varici, Emre Acartürk, Karthikeyan Shanmugam, Ali Tajer
2024	J	`jnl`	Glauber Generative Model: Discrete Diffusion Models via Binary Classification. CoRR Harshit Varma, Dheeraj Nagaraj, Karthikeyan Shanmugam
2024	A	`conf`	Improving Mobile Maternal and Child Health Care Programs: Collaborative Bandits for Time Slot Selection. AAMAS Soumyabrata Pal, Milind Tambe, Arun Suggala, Karthikeyan Shanmugam, Aparna Taneja
2024	A*	`conf`	Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation. ICLR Shreyas Havaldar, Navodita Sharma, Shubhi Sareen, Karthikeyan Shanmugam, Aravindan Raghuveer
2024	A*	`conf`	Learning model uncertainty as variance-minimizing instance weights. ICLR Nishant Jain, Karthikeyan Shanmugam, Pradeep Shenoy
2024	A*	`conf`	Linear Causal Representation Learning from Unknown Multi-node Interventions. NeurIPS Burak Varici, Emre Acartürk, Karthikeyan Shanmugam, Ali Tajer
2024	J	`jnl`	Linear Causal Representation Learning from Unknown Multi-node Interventions. CoRR Burak Varici, Emre Acartürk, Karthikeyan Shanmugam, Ali Tajer
2024	J	`jnl`	Model Agnostic Contrastive Explanations for Classification Models. IEEE J. Emerg. Sel. Topics Circuits Syst. Amit Dhurandhar, Tejaswini Pedapati, Avinash Balakrishnan, Pin-Yu Chen, Karthikeyan Shanmugam, Ruchir Puri
2024	A*	`conf`	Sample Complexity of Interventional Causal Representation Learning. NeurIPS Emre Acartürk, Burak Varici, Karthikeyan Shanmugam, Ali Tajer
2024	J	`jnl`	Score-based Causal Representation Learning: Linear and General Transformations. CoRR Burak Varici, Emre Acartürk, Karthikeyan Shanmugam, Abhishek Kumar, Ali Tajer
2024	A*	`conf`	Time-Reversal Provides Unsupervised Feedback to LLMs. NeurIPS Yerram Varun, Rahul Madhavan, Sravanti Addepalli, Arun Suggala, Karthikeyan Shanmugam, Prateek Jain
2024	J	`jnl`	Time-Reversal Provides Unsupervised Feedback to LLMs. CoRR Yerram Varun, Rahul Madhavan, Sravanti Addepalli, Arun Suggala, Karthikeyan Shanmugam, Prateek Jain
2023	A*	`conf`	Blocked Collaborative Bandits: Online Collaborative Filtering with Per-Item Budget Constraints. NeurIPS Soumyabrata Pal, Arun Sai Suggala, Karthikeyan Shanmugam, Prateek Jain
2023	J	`jnl`	Blocked Collaborative Bandits: Online Collaborative Filtering with Per-Item Budget Constraints. CoRR Soumyabrata Pal, Arun Sai Suggala, Karthikeyan Shanmugam, Prateek Jain
2023	J	`jnl`	Causal Bandits for Linear Structural Equation Models. J. Mach. Learn. Res. Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer
2023	A*	`conf`	Fault Injection Based Interventional Causal Learning for Distributed Applications. AAAI Qing Wang, Jesus Rios, Saurabh Jha, Karthikeyan Shanmugam, Frank Bagehorn, Xi Yang, Robert Filepp, Naoki Abe, Larisa Shwartz
2023	A*	`conf`	Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge. NeurIPS Abhin Shah, Karthikeyan Shanmugam, Murat Kocaoglu
2023	J	`jnl`	Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge. CoRR Abhin Shah, Karthikeyan Shanmugam, Murat Kocaoglu
2023	J	`jnl`	General Identifiability and Achievability for Causal Representation Learning. CoRR Burak Varici, Emre Acartürk, Karthikeyan Shanmugam, Ali Tajer
2023	A*	`conf`	Identifiability Guarantees for Causal Disentanglement from Soft Interventions. NeurIPS Jiaqi Zhang, Kristjan H. Greenewald, Chandler Squires, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler
2023	J	`jnl`	Identifiability Guarantees for Causal Disentanglement from Soft Interventions. CoRR Jiaqi Zhang, Chandler Squires, Kristjan H. Greenewald, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler
2023	J	`jnl`	Improving Fairness-Accuracy tradeoff with few Test Samples under Covariate Shift. CoRR Shreyas Havaldar, Jatin Chauhan, Karthikeyan Shanmugam, Jay Nandy, Aravindan Raghuveer
2023	A*	`conf`	InfoNCE Loss Provably Learns Cluster-Preserving Representations. COLT Advait Parulekar, Liam Collins, Karthikeyan Shanmugam, Aryan Mokhtari, Sanjay Shakkottai
2023	J	`jnl`	InfoNCE Loss Provably Learns Cluster-Preserving Representations. CoRR Advait Parulekar, Liam Collins, Karthikeyan Shanmugam, Aryan Mokhtari, Sanjay Shakkottai
2023	J	`jnl`	Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation. CoRR Shreyas Havaldar, Navodita Sharma, Shubhi Sareen, Karthikeyan Shanmugam, Aravindan Raghuveer
2023	A	`conf`	Optimal Algorithms for Latent Bandits with Cluster Structure. AISTATS Soumyabrata Pal, Arun Sai Suggala, Karthikeyan Shanmugam, Prateek Jain
2023	J	`jnl`	Optimal Algorithms for Latent Bandits with Cluster Structure. CoRR Soumyabrata Pal, Arun Sai Suggala, Karthikeyan Shanmugam, Prateek Jain
2023	J	`jnl`	Optimal Best-Arm Identification in Bandits with Access to Offline Data. CoRR Shubhada Agrawal, Sandeep Juneja, Karthikeyan Shanmugam, Arun Sai Suggala
2023	A*	`conf`	PAC Generalization via Invariant Representations. ICML Advait U. Parulekar, Karthikeyan Shanmugam, Sanjay Shakkottai
2023	J	`jnl`	Score-based Causal Representation Learning with Interventions. CoRR Burak Varici, Emre Acartürk, Karthikeyan Shanmugam, Abhishek Kumar, Ali Tajer
2022	A*	`conf`	AI Explainability 360: Impact and Design. AAAI Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2022	A*	`conf`	Auto-Transfer: Learning to Route Transferable Representations. ICLR Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar
2022	J	`jnl`	Auto-Transfer: Learning to Route Transferrable Representations. CoRR Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar
2022	J	`jnl`	Causal Bandits for Linear Structural Equation Models. CoRR Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer
2022	—	`conf`	Causal Feature Selection for Algorithmic Fairness. SIGMOD Conference Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney
2022	J	`jnl`	Causal Graphs Underlying Generative Models: Path to Learning with Limited Data. CoRR Samuel C. Hoffman, Kahini Wadhawan, Payel Das, Prasanna Sattigeri, Karthikeyan Shanmugam
2022	A	`conf`	Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge. AISTATS Abhin Shah, Karthikeyan Shanmugam, Kartik Ahuja
2022	A*	`conf`	Fourier Representations for Black-Box Optimization over Categorical Variables. AAAI Hamid Dadkhahi, Jesus Rios, Karthikeyan Shanmugam, Payel Das
2022	J	`jnl`	Fourier Representations for Black-Box Optimization over Categorical Variables. CoRR Hamid Dadkhahi, Jesus Rios, Karthikeyan Shanmugam, Payel Das
2022	A	`conf`	Intervention target estimation in the presence of latent variables. UAI Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer
2022	A*	`conf`	Is this the Right Neighborhood? Accurate and Query Efficient Model Agnostic Explanations. NeurIPS Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Karthikeyan Shanmugam
2022	J	`jnl`	PAC Generalization via Invariant Representations. CoRR Advait Parulekar, Karthikeyan Shanmugam, Sanjay Shakkottai
2022	—	`conf`	Process Independence Testing in Proximal Graphical Event Models. CLeaR Debarun Bhattacharjya, Karthikeyan Shanmugam, Tian Gao, Dharmashankar Subramanian
2021	J	`jnl`	A Lyapunov Theory for Finite-Sample Guarantees of Asynchronous Q-Learning and TD-Learning Variants. CoRR Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam
2021	—	`conf`	AI Explainability 360 Toolkit. COMAD/CODS Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2021	J	`jnl`	AI Explainability 360: Impact and Design. CoRR Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2021	A*	`conf`	CoFrNets: Interpretable Neural Architecture Inspired by Continued Fractions. NeurIPS Isha Puri, Amit Dhurandhar, Tejaswini Pedapati, Karthikeyan Shanmugam, Dennis Wei, Kush R. Varshney
2021	A	`conf`	Conditionally independent data generation. UAI Kartik Ahuja, Prasanna Sattigeri, Karthikeyan Shanmugam, Dennis Wei, Karthikeyan Natesan Ramamurthy, Murat Kocaoglu
2021	B	`conf`	Detecting Causal Structure on Cloud Application Microservices Using Granger Causality Models. CLOUD Qing Wang, Larisa Shwartz, Genady Ya. Grabarnik, Vijay Arya, Karthikeyan Shanmugam
2021	J	`jnl`	Efficient Encrypted Inference on Ensembles of Decision Trees. CoRR Kanthi K. Sarpatwar, Karthik Nandakumar, Nalini K. Ratha, James T. Rayfield, Karthikeyan Shanmugam, Sharath Pankanti, Roman Vaculín
2021	A*	`conf`	Empirical or Invariant Risk Minimization? A Sample Complexity Perspective. ICLR Kartik Ahuja, Jun Wang, Amit Dhurandhar, Karthikeyan Shanmugam, Kush R. Varshney
2021	J	`jnl`	Episodic Bandits with Stochastic Experts. CoRR Nihal Sharma, Soumya Basu, Karthikeyan Shanmugam, Sanjay Shakkottai
2021	—	`conf`	Evaluation of Causal Inference Techniques for AIOps. COMAD/CODS Vijay Arya, Karthikeyan Shanmugam, Pooja Aggarwal, Qing Wang, Prateeti Mohapatra, Seema Nagar
2021	J	`jnl`	Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge. CoRR Abhin Shah, Karthikeyan Shanmugam, Kartik Ahuja
2021	A*	`conf`	Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators. NeurIPS Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam
2021	J	`jnl`	Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators. CoRR Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam
2021	A	`conf`	High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation. AISTATS Kristjan H. Greenewald, Karthikeyan Shanmugam, Dmitriy A. Katz
2021	J	`jnl`	Interventional Fairness with Indirect Knowledge of Unobserved Protected Attributes. Entropy Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney
2021	A*	`conf`	Leveraging Latent Features for Local Explanations. KDD Ronny Luss, Pin-Yu Chen, Amit Dhurandhar, Prasanna Sattigeri, Yunfeng Zhang, Karthikeyan Shanmugam, Chun-Chen Tu
2021	A	`conf`	Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions. AISTATS Kartik Ahuja, Karthikeyan Shanmugam, Amit Dhurandhar
2021	A*	`conf`	Scalable Intervention Target Estimation in Linear Models. NeurIPS Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer
2021	J	`jnl`	Scalable Intervention Target Estimation in Linear Models. CoRR Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer
2021	Misc	`conf`	Treatment Effect Estimation Using Invariant Risk Minimization. ICASSP Abhin Shah, Kartik Ahuja, Karthikeyan Shanmugam, Dennis Wei, Kush R. Varshney, Amit Dhurandhar
2021	J	`jnl`	Treatment Effect Estimation using Invariant Risk Minimization. CoRR Abhin Shah, Kartik Ahuja, Karthikeyan Shanmugam, Dennis Wei, Kush R. Varshney, Amit Dhurandhar
2020	A*	`conf`	A Multi-Channel Neural Graphical Event Model with Negative Evidence. AAAI Tian Gao, Dharmashankar Subramanian, Karthikeyan Shanmugam, Debarun Bhattacharjya, Nicholas Mattei
2020	J	`jnl`	A Multi-Channel Neural Graphical Event Model with Negative Evidence. CoRR Tian Gao, Dharmashankar Subramanian, Karthikeyan Shanmugam, Debarun Bhattacharjya, Nicholas Mattei
2020	J	`jnl`	AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models. J. Mach. Learn. Res. Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2020	—	`conf`	AI explainability 360: hands-on tutorial. FAT* Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2020	J	`jnl`	Active Structure Learning of Causal DAGs via Directed Clique Tree. CoRR Chandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam
2020	A*	`conf`	Active Structure Learning of Causal DAGs via Directed Clique Trees. NeurIPS Chandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam
2020	A*	`conf`	Causal Discovery from Soft Interventions with Unknown Targets: Characterization and Learning. NeurIPS Amin Jaber, Murat Kocaoglu, Karthikeyan Shanmugam, Elias Bareinboim
2020	A*	`conf`	Combinatorial Black-Box Optimization with Expert Advice. KDD Hamid Dadkhahi, Karthikeyan Shanmugam, Jesus Rios, Payel Das, Samuel C. Hoffman, Troy David Loeffler, Subramanian Sankaranarayanan
2020	J	`jnl`	Combinatorial Black-Box Optimization with Expert Advice. CoRR Hamid Dadkhahi, Karthikeyan Shanmugam, Jesus Rios, Payel Das, Samuel C. Hoffman, Troy David Loeffler, Subramanian Sankaranarayanan
2020	J	`jnl`	Empirical or Invariant Risk Minimization? A Sample Complexity Perspective. CoRR Kartik Ahuja, Jun Wang, Amit Dhurandhar, Karthikeyan Shanmugam, Kush R. Varshney
2020	A*	`conf`	Enhancing Simple Models by Exploiting What They Already Know. ICML Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss
2020	A*	`conf`	Event-Driven Continuous Time Bayesian Networks. AAAI Debarun Bhattacharjya, Karthikeyan Shanmugam, Tian Gao, Nicholas Mattei, Kush R. Varshney, Dharmashankar Subramanian
2020	J	`jnl`	Fair Data Integration. CoRR Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney
2020	A*	`conf`	Finite-Sample Analysis of Contractive Stochastic Approximation Using Smooth Convex Envelopes. NeurIPS Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam
2020	J	`jnl`	Finite-Sample Analysis of Stochastic Approximation Using Smooth Convex Envelopes. CoRR Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam
2020	—	`conf`	Hawkesian Graphical Event Models. PGM Xiufan Yu, Karthikeyan Shanmugam, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Lingzhou Xue
2020	A*	`conf`	Invariant Risk Minimization Games. ICML Kartik Ahuja, Karthikeyan Shanmugam, Kush R. Varshney, Amit Dhurandhar
2020	J	`jnl`	Invariant Risk Minimization Games. CoRR Kartik Ahuja, Karthikeyan Shanmugam, Kush R. Varshney, Amit Dhurandhar
2020	A*	`conf`	Learning Global Transparent Models consistent with Local Contrastive Explanations. NeurIPS Tejaswini Pedapati, Avinash Balakrishnan, Karthikeyan Shanmugam, Amit Dhurandhar
2020	J	`jnl`	Learning Global Transparent Models from Local Contrastive Explanations. CoRR Tejaswini Pedapati, Avinash Balakrishnan, Karthikeyan Shanmugam, Amit Dhurandhar
2020	J	`jnl`	Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions. CoRR Kartik Ahuja, Karthikeyan Shanmugam, Amit Dhurandhar
2020	A*	`conf`	Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions. NeurIPS Matthew Faw, Rajat Sen, Karthikeyan Shanmugam, Constantine Caramanis, Sanjay Shakkottai
2020	—	`conf`	Privacy Enhanced Decision Tree Inference. CVPR Workshops Kanthi K. Sarpatwar, Nalini K. Ratha, Karthik Nandakumar, Karthikeyan Shanmugam, James T. Rayfield, Sharath Pankanti, Roman Vaculín
2020	J	`jnl`	Stochastic Linear Bandits with Protected Subspace. CoRR Advait Parulekar, Soumya Basu, Aditya Gopalan, Karthikeyan Shanmugam, Sanjay Shakkottai
2020	J	`jnl`	Warm Starting Bandits with Side Information from Confounded Data. CoRR Nihal Sharma, Soumya Basu, Karthikeyan Shanmugam, Sanjay Shakkottai
2019	A	`conf`	ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery. AISTATS Raj Agrawal, Chandler Squires, Karren D. Yang, Karthikeyan Shanmugam, Caroline Uhler
2019	—	`conf`	Blockchain Enabled AI Marketplace: The Price You Pay for Trust. CVPR Workshops Kanthi K. Sarpatwar, Venkata Sitaramagiridharganesh Ganapavarapu, Karthikeyan Shanmugam, Akond Rahman, Roman Vaculín
2019	A*	`conf`	Characterization and Learning of Causal Graphs with Latent Variables from Soft Interventions. NeurIPS Murat Kocaoglu, Amin Jaber, Karthikeyan Shanmugam, Elias Bareinboim
2019	A	`conf`	Confidence Scoring Using Whitebox Meta-models with Linear Classifier Probes. AISTATS Tongfei Chen, Jirí Navrátil, Vijay S. Iyengar, Karthikeyan Shanmugam
2019	A*	`conf`	Differentially Private Distributed Data Summarization under Covariate Shift. NeurIPS Kanthi K. Sarpatwar, Karthikeyan Shanmugam, Venkata Sitaramagiridharganesh Ganapavarapu, Ashish Jagmohan, Roman Vaculín
2019	J	`jnl`	Differentially Private Distributed Data Summarization under Covariate Shift. CoRR Kanthi K. Sarpatwar, Karthikeyan Shanmugam, Venkata Sitaramagiridharganesh Ganapavarapu, Ashish Jagmohan, Roman Vaculín
2019	J	`jnl`	Efficient Algorithms for Coded Multicasting in Heterogeneous Caching Networks. Entropy Giuseppe Vettigli, Mingyue Ji, Karthikeyan Shanmugam, Jaime Llorca, Antonia M. Tulino, Giuseppe Caire
2019	J	`jnl`	Generating Contrastive Explanations with Monotonic Attribute Functions. CoRR Ronny Luss, Pin-Yu Chen, Amit Dhurandhar, Prasanna Sattigeri, Karthikeyan Shanmugam, Chun-Chen Tu
2019	J	`jnl`	Leveraging Simple Model Predictions for Enhancing its Performance. CoRR Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss
2019	J	`jnl`	Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions. CoRR Matthew Faw, Rajat Sen, Karthikeyan Shanmugam, Constantine Caramanis, Sanjay Shakkottai
2019	J	`jnl`	Model Agnostic Contrastive Explanations for Structured Data. CoRR Amit Dhurandhar, Tejaswini Pedapati, Avinash Balakrishnan, Pin-Yu Chen, Karthikeyan Shanmugam, Ruchir Puri
2019	J	`jnl`	One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques. CoRR Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
2019	A*	`conf`	Sample Efficient Active Learning of Causal Trees. NeurIPS Kristjan H. Greenewald, Dmitriy Katz, Karthikeyan Shanmugam, Sara Magliacane, Murat Kocaoglu, Enric Boix Adserà, Guy Bresler
2019	J	`jnl`	Size of Interventional Markov Equivalence Classes in Random DAG Models. CoRR Dmitriy Katz, Karthikeyan Shanmugam, Chandler Squires, Caroline Uhler
2019	A	`conf`	Size of Interventional Markov Equivalence Classes in random DAG models. AISTATS Dmitriy Katz, Karthikeyan Shanmugam, Chandler Squires, Caroline Uhler
2018	J	`jnl`	Confidence Scoring Using Whitebox Meta-models with Linear Classifier Probes. CoRR Tongfei Chen, Jirí Navrátil, Vijay S. Iyengar, Karthikeyan Shanmugam
2018	A	`conf`	Contextual Bandits with Stochastic Experts. AISTATS Rajat Sen, Karthikeyan Shanmugam, Sanjay Shakkottai
2018	J	`jnl`	Contextual Bandits with Stochastic Experts. CoRR Rajat Sen, Karthikeyan Shanmugam, Sanjay Shakkottai
2018	A*	`conf`	Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives. NeurIPS Amit Dhurandhar, Pin-Yu Chen, Ronny Luss, Chun-Chen Tu, Pai-Shun Ting, Karthikeyan Shanmugam, Payel Das
2018	J	`jnl`	Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives. CoRR Amit Dhurandhar, Pin-Yu Chen, Ronny Luss, Chun-Chen Tu, Pai-Shun Ting, Karthikeyan Shanmugam, Payel Das
2018	J	`jnl`	From Centralized to Decentralized Coded Caching. CoRR Yitao Chen, Karthikeyan Shanmugam, Alexandros G. Dimakis
2018	A*	`conf`	Improving Simple Models with Confidence Profiles. NeurIPS Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss, Peder A. Olsen
2018	J	`jnl`	Improving Simple Models with Confidence Profiles. CoRR Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss, Peder A. Olsen
2018	J	`jnl`	Mimic and Classify : A meta-algorithm for Conditional Independence Testing. CoRR Rajat Sen, Karthikeyan Shanmugam, Himanshu Asnani, Arman Rahimzamani, Sreeram Kannan
2018	J	`jnl`	Structure Learning from Time Series with False Discovery Control. CoRR Bernat Guillen Pegueroles, Bhanukiran Vinzamuri, Karthikeyan Shanmugam, Steve Hedden, Jonathan D. Moyer, Kush R. Varshney
2017	J	`jnl`	A Formal Framework to Characterize Interpretability of Procedures. CoRR Amit Dhurandhar, Vijay S. Iyengar, Ronny Luss, Karthikeyan Shanmugam
2017	Misc	`conf`	A unified Ruzsa-Szemerédi framework for finite-length coded caching. ACSSC Karthikeyan Shanmugam, Alexandros G. Dimakis, Jaime Llorca, Antonia M. Tulino
2017	J	`jnl`	Causal Best Intervention Identification via Importance Sampling. CoRR Rajat Sen, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai
2017	J	`jnl`	Coded Caching with Linear Subpacketization is Possible using Ruzsa-Szeméredi Graphs. CoRR Karthikeyan Shanmugam, Antonia M. Tulino, Alexandros G. Dimakis
2017	B	`conf`	Coded caching with linear subpacketization is possible using Ruzsa-Szeméredi graphs. ISIT Karthikeyan Shanmugam, Antonia M. Tulino, Alexandros G. Dimakis
2017	A	`conf`	Contextual Bandits with Latent Confounders: An NMF Approach. AISTATS Rajat Sen, Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sanjay Shakkottai
2017	—	`conf`	Experimental Design for Learning Causal Graphs with Latent Variables. NIPS Murat Kocaoglu, Karthikeyan Shanmugam, Elias Bareinboim
2017	A*	`conf`	Identifying Best Interventions through Online Importance Sampling. ICML Rajat Sen, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai
2017	—	`conf`	Model-Powered Conditional Independence Test. NIPS Rajat Sen, Ananda Theertha Suresh, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai
2017	J	`jnl`	Model-Powered Conditional Independence Test. CoRR Rajat Sen, Ananda Theertha Suresh, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai
2017	J	`jnl`	Sparse Quadratic Logistic Regression in Sub-quadratic Time. CoRR Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sujay Sanghavi
2017	J	`jnl`	TIP: Typifying the Interpretability of Procedures. CoRR Amit Dhurandhar, Vijay S. Iyengar, Ronny Luss, Karthikeyan Shanmugam
2016	A*	`conf`	Distributed Estimation of Graph 4-Profiles. WWW Ethan R. Elenberg, Karthikeyan Shanmugam, Michael Borokhovich, Alexandros G. Dimakis
2016	J	`jnl`	Finite-Length Analysis of Caching-Aided Coded Multicasting. IEEE Trans. Inf. Theory Karthikeyan Shanmugam, Mingyue Ji, Antonia M. Tulino, Jaime Llorca, Alexandros G. Dimakis
2016	J	`jnl`	Latent Contextual Bandits: A Non-Negative Matrix Factorization Approach. CoRR Rajat Sen, Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sanjay Shakkottai
2015	J	`jnl`	An Efficient Multiple-Groupcast Coded Multicasting Scheme for Finite Fractional Caching. CoRR Mingyue Ji, Karthikeyan Shanmugam, Giuseppe Vettigli, Jaime Llorca, Antonia M. Tulino, Giuseppe Caire
2015	—	`conf`	An efficient multiple-groupcast coded multicasting scheme for finite fractional caching. ICC Mingyue Ji, Karthikeyan Shanmugam, Giuseppe Vettigli, Jaime Llorca, Antonia M. Tulino, Giuseppe Caire
2015	A*	`conf`	Beyond Triangles: A Distributed Framework for Estimating 3-profiles of Large Graphs. KDD Ethan R. Elenberg, Karthikeyan Shanmugam, Michael Borokhovich, Alexandros G. Dimakis
2015	J	`jnl`	Beyond Triangles: A Distributed Framework for Estimating 3-profiles of Large Graphs. CoRR Ethan R. Elenberg, Karthikeyan Shanmugam, Michael Borokhovich, Alexandros G. Dimakis
2015	J	`jnl`	Distributed Estimation of Graph 4-Profiles. CoRR Ethan R. Elenberg, Karthikeyan Shanmugam, Michael Borokhovich, Alexandros G. Dimakis
2015	J	`jnl`	Finite Length Analysis of Caching-Aided Coded Multicasting. CoRR Karthikeyan Shanmugam, Mingyue Ji, Antonia M. Tulino, Jaime Llorca, Alexandros G. Dimakis
2015	—	`conf`	Learning Causal Graphs with Small Interventions. NIPS Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath
2015	J	`jnl`	Learning Causal Graphs with Small Interventions. CoRR Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath
2015	J	`jnl`	On Approximating the Sum-Rate for Multiple-Unicasts. CoRR Karthikeyan Shanmugam, Megasthenis Asteris, Alexandros G. Dimakis
2015	B	`conf`	On approximating the sum-rate for multiple-unicasts. ISIT Karthikeyan Shanmugam, Megasthenis Asteris, Alexandros G. Dimakis
2014	J	`jnl`	A Repair Framework for Scalar MDS Codes. IEEE J. Sel. Areas Commun. Karthikeyan Shanmugam, Dimitris S. Papailiopoulos, Alexandros G. Dimakis, Giuseppe Caire
2014	J	`jnl`	A Smoothed Analysis for Learning Sparse Polynomials. CoRR Alexandros G. Dimakis, Adam R. Klivans, Murat Kocaoglu, Karthikeyan Shanmugam
2014	J	`jnl`	Bounding Multiple Unicasts through Index Coding and Locally Repairable Codes. CoRR Karthikeyan Shanmugam, Alexandros G. Dimakis
2014	B	`conf`	Bounding multiple unicasts through index coding and Locally Repairable Codes. ISIT Karthikeyan Shanmugam, Alexandros G. Dimakis
2014	—	`conf`	Finite length analysis of caching-aided coded multicasting. Allerton Karthikeyan Shanmugam, Mingyue Ji, Antonia M. Tulino, Jaime Llorca, Alexandros G. Dimakis
2014	J	`jnl`	Graph Theory versus Minimum Rank for Index Coding. CoRR Karthikeyan Shanmugam, Alexandros G. Dimakis, Michael Langberg
2014	B	`conf`	Graph theory versus minimum rank for index coding. ISIT Karthikeyan Shanmugam, Alexandros G. Dimakis, Michael Langberg
2014	—	`conf`	On the Information Theoretic Limits of Learning Ising Models. NIPS Rashish Tandon, Karthikeyan Shanmugam, Pradeep Ravikumar, Alexandros G. Dimakis
2014	J	`jnl`	On the Information Theoretic Limits of Learning Ising Models. CoRR Karthikeyan Shanmugam, Rashish Tandon, Alexandros G. Dimakis, Pradeep Ravikumar
2014	—	`conf`	Sparse Polynomial Learning and Graph Sketching. NIPS Murat Kocaoglu, Karthikeyan Shanmugam, Alexandros G. Dimakis, Adam R. Klivans
2013	J	`jnl`	A Repair Framework for Scalar MDS Codes. CoRR Karthikeyan Shanmugam, Dimitris S. Papailiopoulos, Alexandros G. Dimakis, Giuseppe Caire
2013	J	`jnl`	FemtoCaching: Wireless Content Delivery Through Distributed Caching Helpers. IEEE Trans. Inf. Theory Karthikeyan Shanmugam, Negin Golrezaei, Alexandros G. Dimakis, Andreas F. Molisch, Giuseppe Caire
2013	J	`jnl`	Index Coding Problem with Side Information Repositories. CoRR Karthikeyan Shanmugam, Alexandros G. Dimakis, Giuseppe Caire
2013	—	`conf`	Index coding problem with side information repositories. Allerton Karthikeyan Shanmugam, Alexandros G. Dimakis, Giuseppe Caire
2013	J	`jnl`	Local Graph Coloring and Index Coding CoRR Karthikeyan Shanmugam, Alexandros G. Dimakis, Michael Langberg
2013	B	`conf`	Local graph coloring and index coding. ISIT Karthikeyan Shanmugam, Alexandros G. Dimakis, Michael Langberg
2012	—	`conf`	A repair framework for scalar MDS codes. Allerton Conference Karthikeyan Shanmugam, Dimitris S. Papailiopoulos, Alexandros G. Dimakis, Giuseppe Caire
2012	A*	`conf`	FemtoCaching: Wireless video content delivery through distributed caching helpers. INFOCOM Negin Golrezaei, Karthikeyan Shanmugam, Alexandros G. Dimakis, Andreas F. Molisch, Giuseppe Caire
2012	B	`conf`	Wireless downloading delay under proportional fair scheduling with coupled service and requests: An approximated analysis. ISIT Karthikeyan Shanmugam, Giuseppe Caire
2012	—	`conf`	Wireless video content delivery through coded distributed caching. ICC Negin Golrezaei, Karthikeyan Shanmugam, Alexandros G. Dimakis, Andreas F. Molisch, Giuseppe Caire
2011	J	`jnl`	FemtoCaching: Wireless Video Content Delivery through Distributed Caching Helpers CoRR Negin Golrezaei, Karthikeyan Shanmugam, Alexandros G. Dimakis, Andreas F. Molisch, Giuseppe Caire
2010	B	`conf`	Rate Gap Analysis for Rate-Adaptive Antenna Selection and Beamforming Schemes. GLOBECOM Karthikeyan Shanmugam, Srikrishna Bhashyam