Shanmugam, Karthikeyan

73 publications

TMLR 2025 Combinatorial Multi-Armed Bandits: Arm Selection via Group Testing Arpan Mukherjee, Shashanka Ubaru, Keerthiram Murugesan, Karthikeyan Shanmugam, Ali Tajer

ICLR 2025 Does Safety Training of LLMs Generalize to Semantically Related Natural Prompts? Sravanti Addepalli, Yerram Varun, Arun Suggala, Karthikeyan Shanmugam, Prateek Jain

ICLR 2025 Glauber Generative Model: Discrete Diffusion Models via Binary Classification Harshit Varma, Dheeraj Mysore Nagaraj, Karthikeyan Shanmugam

ICLRW 2025 Interleaved Gibbs Diffusion for Constrained Generation Gautham Govind Anil, Sachin Yadav, Dheeraj Mysore Nagaraj, Karthikeyan Shanmugam, Prateek Jain

MLHC 2025 Learning to Call: A Field Trial of a Collaborative Bandit Algorithm for Optimizing Call Timing in Mobile Maternal Health Arpan Dasgupta, Mizhaan Prajit Maniyar, Awadhesh Srivastava, Sanat Kumar, Amrita Mahale, Aparna Hegde, Arun Suggala, Karthikeyan Shanmugam, Milind Tambe, Aparna Taneja

NeurIPS 2025 Path-Specific Effects for Pulse-Oximetry Guided Decisions in Critical Care Kevin Zhang, Yonghan Jung, Divyat Mahajan, Karthikeyan Shanmugam, Shalmali Joshi

AISTATS 2025 Risk-Sensitive Bandits: Arm Mixture Optimality and Regret-Efficient Algorithms Meltem Tatlı, Arpan Mukherjee, L. A. Prashanth, Karthikeyan Shanmugam, Ali Tajer

JMLR 2025 Score-Based Causal Representation Learning: Linear and General Transformations Burak Varici, Emre Acartürk, Karthikeyan Shanmugam, Abhishek Kumar, Ali Tajer

TMLR 2024 Attribute Graphs Underlying Molecular Generative Models: Path to Learning with Limited Data Samuel C Hoffman, Payel Das, Karthikeyan Shanmugam, Kahini Wadhawan, Prasanna Sattigeri

TMLR 2024 Bandits with Mean Bounds Nihal Sharma, Soumya Basu, Karthikeyan Shanmugam, Sanjay Shakkottai

NeurIPSW 2024 Does Safety Training of LLMs Generalize to Semantically Related Natural Prompts? Sravanti Addepalli, Yerram Varun, Arun Suggala, Karthikeyan Shanmugam, Prateek Jain

AAAI 2024 Fairness Under Covariate Shift: Improving Fairness-Accuracy Tradeoff with Few Unlabeled Test Samples Shreyas Havaldar, Jatin Chauhan, Karthikeyan Shanmugam, Jay Nandy, Aravindan Raghuveer

AISTATS 2024 General Identifiability and Achievability for Causal Representation Learning Burak Varici, Emre Acartürk, Karthikeyan Shanmugam, Ali Tajer

ICMLW 2024 Glauber Generative Model: Discrete Diffusion Models via Binary Classification Harshit Varma, Dheeraj Mysore Nagaraj, Karthikeyan Shanmugam

ICLR 2024 Learning Model Uncertainty as Variance-Minimizing Instance Weights Nishant Jain, Karthikeyan Shanmugam, Pradeep Shenoy

ICLR 2024 Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation Shreyas Havaldar, Navodita Sharma, Shubhi Sareen, Karthikeyan Shanmugam, Aravindan Raghuveer

NeurIPS 2024 Linear Causal Representation Learning from Unknown Multi-Node Interventions Burak Varıcı, Emre Acartürk, Karthikeyan Shanmugam, Ali Tajer

NeurIPS 2024 Sample Complexity of Interventional Causal Representation Learning Emre Acartürk, Burak Varıcı, Karthikeyan Shanmugam, Ali Tajer

NeurIPS 2024 Time-Reversal Provides Unsupervised Feedback to LLMs Varun Yerram, Rahul Madhavan, Sravanti Addepalli, Arun Suggala, Karthikeyan Shanmugam, Prateek Jain

NeurIPSW 2024 TreeTop: Topology-Aware Fine-Tuning for LLM Conversation Tree Understanding Jashn Arora, Rahul Madhavan, Karthikeyan Shanmugam, John Palowitch, Manish Jain

NeurIPS 2023 Blocked Collaborative Bandits: Online Collaborative Filtering with Per-Item Budget Constraints Soumyabrata Pal, Arun Suggala, Karthikeyan Shanmugam, Prateek Jain

JMLR 2023 Causal Bandits for Linear Structural Equation Models Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer

AAAI 2023 Fault Injection Based Interventional Causal Learning for Distributed Applications Qing Wang, Jesus Rios, Saurabh Jha, Karthikeyan Shanmugam, Frank Bagehorn, Xi Yang, Robert Filepp, Naoki Abe, Larisa Shwartz

NeurIPS 2023 Front-Door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge Abhin Shah, Karthikeyan Shanmugam, Murat Kocaoglu

NeurIPS 2023 Identifiability Guarantees for Causal Disentanglement from Soft Interventions Jiaqi Zhang, Kristjan Greenewald, Chandler Squires, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler

COLT 2023 InfoNCE Loss Provably Learns Cluster-Preserving Representations Advait Parulekar, Liam Collins, Karthikeyan Shanmugam, Aryan Mokhtari, Sanjay Shakkottai

NeurIPSW 2023 Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation Shreyas Havaldar, Navodita Sharma, Shubhi Sareen, Karthikeyan Shanmugam, Aravindan Raghuveer

AISTATS 2023 Optimal Algorithms for Latent Bandits with Cluster Structure Soumyabrata Pal, Arun Sai Suggala, Karthikeyan Shanmugam, Prateek Jain

ICML 2023 PAC Generalization via Invariant Representations Advait U Parulekar, Karthikeyan Shanmugam, Sanjay Shakkottai

NeurIPSW 2023 Score-Based Causal Representation Learning from Interventions: Nonparametric Identifiability Burak Varici, Emre Acartürk, Karthikeyan Shanmugam, Ali Tajer

AISTATS 2022 Finding Valid Adjustments Under Non-Ignorability with Minimal DAG Knowledge Abhin Shah, Karthikeyan Shanmugam, Kartik Ahuja

AAAI 2022 AI Explainability 360: Impact and Design 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

ICLR 2022 Auto-Transfer: Learning to Route Transferable Representations Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar

AAAI 2022 Fourier Representations for Black-Box Optimization over Categorical Variables Hamid Dadkhahi, Jesus Rios, Karthikeyan Shanmugam, Payel Das

UAI 2022 Intervention Target Estimation in the Presence of Latent Variables Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer

NeurIPS 2022 Is This the Right Neighborhood? Accurate and Query Efficient Model Agnostic Explanations Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Karthikeyan Shanmugam

CLeaR 2022 Process Independence Testing in Proximal Graphical Event Models Debarun Bhattacharjya, Karthikeyan Shanmugam, Tian Gao, Dharmashankar Subramanian

AISTATS 2021 High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation Kristjan Greenewald, Karthikeyan Shanmugam, Dmitriy Katz

AISTATS 2021 Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions Kartik Ahuja, Karthikeyan Shanmugam, Amit Dhurandhar

NeurIPS 2021 CoFrNets: Interpretable Neural Architecture Inspired by Continued Fractions Isha Puri, Amit Dhurandhar, Tejaswini Pedapati, Karthikeyan Shanmugam, Dennis Wei, Kush R Varshney

UAI 2021 Conditionally Independent Data Generation Kartik Ahuja, Prasanna Sattigeri, Karthikeyan Shanmugam, Dennis Wei, Karthikeyan Natesan Ramamurthy, Murat Kocaoglu

ICLR 2021 Empirical or Invariant Risk Minimization? a Sample Complexity Perspective Kartik Ahuja, Jun Wang, Amit Dhurandhar, Karthikeyan Shanmugam, Kush R. Varshney

NeurIPS 2021 Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam

NeurIPS 2021 Scalable Intervention Target Estimation in Linear Models Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer

AAAI 2020 A Multi-Channel Neural Graphical Event Model with Negative Evidence Tian Gao, Dharmashankar Subramanian, Karthikeyan Shanmugam, Debarun Bhattacharjya, Nicholas Mattei

MLOSS 2020 AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilović, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang

NeurIPS 2020 Active Structure Learning of Causal DAGs via Directed Clique Trees Chandler Squires, Sara Magliacane, Kristjan Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam

NeurIPS 2020 Causal Discovery from Soft Interventions with Unknown Targets: Characterization and Learning Amin Jaber, Murat Kocaoglu, Karthikeyan Shanmugam, Elias Bareinboim

ICML 2020 Enhancing Simple Models by Exploiting What They Already Know Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss

AAAI 2020 Event-Driven Continuous Time Bayesian Networks Debarun Bhattacharjya, Karthikeyan Shanmugam, Tian Gao, Nicholas Mattei, Kush R. Varshney, Dharmashankar Subramanian

NeurIPS 2020 Finite-Sample Analysis of Contractive Stochastic Approximation Using Smooth Convex Envelopes Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam

PGM 2020 Hawkesian Graphical Event Models Xiufan Yu, Karthikeyan Shanmugam, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Lingzhou Xue

ICML 2020 Invariant Risk Minimization Games Kartik Ahuja, Karthikeyan Shanmugam, Kush Varshney, Amit Dhurandhar

NeurIPS 2020 Learning Global Transparent Models Consistent with Local Contrastive Explanations Tejaswini Pedapati, Avinash Balakrishnan, Karthikeyan Shanmugam, Amit Dhurandhar

NeurIPS 2020 Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions Matthew Faw, Rajat Sen, Karthikeyan Shanmugam, Constantine Caramanis, Sanjay Shakkottai

CVPRW 2020 Privacy Enhanced Decision Tree Inference Kanthi K. Sarpatwar, Nalini K. Ratha, Karthik Nandakumar, Karthikeyan Shanmugam, James T. Rayfield, Sharath Pankanti, Roman Vaculín

AISTATS 2019 ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery Raj Agrawal, Chandler Squires, Karren Yang, Karthikeyan Shanmugam, Caroline Uhler

CVPRW 2019 Blockchain Enabled AI Marketplace: The Price You Pay for Trust Kanthi K. Sarpatwar, Venkata Sitaramagiridharganesh Ganapavarapu, Karthikeyan Shanmugam, Akond Rahman, Roman Vaculín

NeurIPS 2019 Characterization and Learning of Causal Graphs with Latent Variables from Soft Interventions Murat Kocaoglu, Amin Jaber, Karthikeyan Shanmugam, Elias Bareinboim

AISTATS 2019 Confidence Scoring Using Whitebox Meta-Models with Linear Classifier Probes Tongfei Chen, Jiri Navratil, Vijay Iyengar, Karthikeyan Shanmugam

NeurIPS 2019 Differentially Private Distributed Data Summarization Under Covariate Shift Kanthi Sarpatwar, Karthikeyan Shanmugam, Venkata Sitaramagiridharganesh Ganapavarapu, Ashish Jagmohan, Roman Vaculin

NeurIPS 2019 Sample Efficient Active Learning of Causal Trees Kristjan Greenewald, Dmitriy Katz, Karthikeyan Shanmugam, Sara Magliacane, Murat Kocaoglu, Enric Boix Adsera, Guy Bresler

AISTATS 2019 Size of Interventional Markov Equivalence Classes in Random DAG Models Dmitriy Katz, Karthikeyan Shanmugam, Chandler Squires, Caroline Uhler

AISTATS 2018 Contextual Bandits with Stochastic Experts Rajat Sen, Karthikeyan Shanmugam, Sanjay Shakkottai

NeurIPS 2018 Explanations Based on the Missing: Towards Contrastive Explanations with Pertinent Negatives Amit Dhurandhar, Pin-Yu Chen, Ronny Luss, Chun-Chen Tu, Paishun Ting, Karthikeyan Shanmugam, Payel Das

NeurIPS 2018 Improving Simple Models with Confidence Profiles Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss, Peder A. Olsen

AISTATS 2017 Contextual Bandits with Latent Confounders: An NMF Approach Rajat Sen, Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sanjay Shakkottai

NeurIPS 2017 Experimental Design for Learning Causal Graphs with Latent Variables Murat Kocaoglu, Karthikeyan Shanmugam, Elias Bareinboim

ICML 2017 Identifying Best Interventions Through Online Importance Sampling Rajat Sen, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai

NeurIPS 2017 Model-Powered Conditional Independence Test Rajat Sen, Ananda Theertha Suresh, Karthikeyan Shanmugam, Alexandros G Dimakis, Sanjay Shakkottai

NeurIPS 2015 Learning Causal Graphs with Small Interventions Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G Dimakis, Sriram Vishwanath

NeurIPS 2014 On the Information Theoretic Limits of Learning Ising Models Rashish Tandon, Karthikeyan Shanmugam, Pradeep K Ravikumar, Alexandros G Dimakis

NeurIPS 2014 Sparse Polynomial Learning and Graph Sketching Murat Kocaoglu, Karthikeyan Shanmugam, Alexandros G Dimakis, Adam Klivans