Karthikeyan Shanmugam

According to our database, Karthikeyan Shanmugam authored at least 113 papers between 2005 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

A resource-constrained stochastic scheduling algorithm for homeless street outreach and gleaning edible food.

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

CoRR, 2024

Score-based Causal Representation Learning: Linear and General Transformations.

Burak Varici, Emre Acartürk, Karthikeyan Shanmugam, Abhishek Kumar, Ali Tajer

CoRR, 2024

Fairness under Covariate Shift: Improving Fairness-Accuracy Tradeoff with Few Unlabeled Test Samples.

Shreyas Havaldar, Jatin Chauhan, Karthikeyan Shanmugam, Jay Nandy, Aravindan Raghuveer

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Parental neglect and emotional wellbeing among adolescent students from India: social network addiction as a mediator and gender as a moderator.

Vijayabanu Chidambaram, Karthikeyan Shanmugam, Satyanarayana Parayitam

Behav. Inf. Technol., May, 2023

General Identifiability and Achievability for Causal Representation Learning.

Burak Varici, Emre Acartürk, Karthikeyan Shanmugam, Ali Tajer

CoRR, 2023

Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation.

Shreyas Havaldar, Navodita Sharma, Shubhi Sareen, Karthikeyan Shanmugam, Aravindan Raghuveer

CoRR, 2023

Improving Fairness-Accuracy tradeoff with few Test Samples under Covariate Shift.

Shreyas Havaldar, Jatin Chauhan, Karthikeyan Shanmugam, Jay Nandy, Aravindan Raghuveer

CoRR, 2023

Optimal Best-Arm Identification in Bandits with Access to Offline Data.

Shubhada Agrawal, Sandeep Juneja, Karthikeyan Shanmugam, Arun Sai Suggala

CoRR, 2023

Score-based Causal Representation Learning with Interventions.

Burak Varici, Emre Acartürk, Karthikeyan Shanmugam, Abhishek Kumar, Ali Tajer

CoRR, 2023

Identifiability Guarantees for Causal Disentanglement from Soft Interventions.

Jiaqi Zhang, Kristjan H. Greenewald, Chandler Squires, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge.

Abhin Shah, Karthikeyan Shanmugam, Murat Kocaoglu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Blocked Collaborative Bandits: Online Collaborative Filtering with Per-Item Budget Constraints.

Soumyabrata Pal, Arun Sai Suggala, Karthikeyan Shanmugam, Prateek Jain

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PAC Generalization via Invariant Representations.

Advait U. Parulekar, Karthikeyan Shanmugam, Sanjay Shakkottai

Proceedings of the International Conference on Machine Learning, 2023

InfoNCE Loss Provably Learns Cluster-Preserving Representations.

Advait Parulekar, Liam Collins, Karthikeyan Shanmugam, Aryan Mokhtari, Sanjay Shakkottai

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Optimal Algorithms for Latent Bandits with Cluster Structure.

Soumyabrata Pal, Arun Sai Suggala, Karthikeyan Shanmugam, Prateek Jain

Proceedings of the International Conference on Artificial Intelligence and Statistics, 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

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Causal Bandits for Linear Structural Equation Models.

Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer

CoRR, 2022

Causal Graphs Underlying Generative Models: Path to Learning with Limited Data.

Samuel C. Hoffman, Kahini Wadhawan, Payel Das, Prasanna Sattigeri, Karthikeyan Shanmugam

CoRR, 2022

Auto-Transfer: Learning to Route Transferrable Representations.

Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar

CoRR, 2022

Intervention target estimation in the presence of latent variables.

Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Causal Feature Selection for Algorithmic Fairness.

Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

Is this the Right Neighborhood? Accurate and Query Efficient Model Agnostic Explanations.

Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Karthikeyan Shanmugam

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Auto-Transfer: Learning to Route Transferable Representations.

Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar

Proceedings of the Tenth International Conference on Learning Representations, 2022

Process Independence Testing in Proximal Graphical Event Models.

Debarun Bhattacharjya, Karthikeyan Shanmugam, Tian Gao, Dharmashankar Subramanian

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge.

Abhin Shah, Karthikeyan Shanmugam, Kartik Ahuja

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Fourier Representations for Black-Box Optimization over Categorical Variables.

Hamid Dadkhahi, Jesus Rios, Karthikeyan Shanmugam, Payel Das

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 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

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Interventional Fairness with Indirect Knowledge of Unobserved Protected Attributes.

Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney

Entropy, 2021

Episodic Bandits with Stochastic Experts.

Nihal Sharma, Soumya Basu, Karthikeyan Shanmugam, Sanjay Shakkottai

CoRR, 2021

Efficient Encrypted Inference on Ensembles of Decision Trees.

Kanthi K. Sarpatwar, Karthik Nandakumar, Nalini K. Ratha, James T. Rayfield, Karthikeyan Shanmugam, Sharath Pankanti, Roman Vaculín

CoRR, 2021

A Lyapunov Theory for Finite-Sample Guarantees of Asynchronous Q-Learning and TD-Learning Variants.

Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam

CoRR, 2021

Conditionally independent data generation.

Kartik Ahuja, Prasanna Sattigeri, Karthikeyan Shanmugam, Dennis Wei, Karthikeyan Natesan Ramamurthy, Murat Kocaoglu

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Scalable Intervention Target Estimation in Linear Models.

Burak Varici, Karthikeyan Shanmugam, Prasanna Sattigeri, Ali Tajer

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

CoFrNets: Interpretable Neural Architecture Inspired by Continued Fractions.

Isha Puri, Amit Dhurandhar, Tejaswini Pedapati, Karthikeyan Shanmugam, Dennis Wei, Kush R. Varshney

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators.

Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Leveraging Latent Features for Local Explanations.

Ronny Luss, Pin-Yu Chen, Amit Dhurandhar, Prasanna Sattigeri, Yunfeng Zhang, Karthikeyan Shanmugam, Chun-Chen Tu

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Empirical or Invariant Risk Minimization? A Sample Complexity Perspective.

Kartik Ahuja, Jun Wang, Amit Dhurandhar, Karthikeyan Shanmugam, Kush R. Varshney

Proceedings of the 9th International Conference on Learning Representations, 2021

Treatment Effect Estimation Using Invariant Risk Minimization.

Abhin Shah, Kartik Ahuja, Karthikeyan Shanmugam, Dennis Wei, Kush R. Varshney, Amit Dhurandhar

Proceedings of the IEEE International Conference on Acoustics, 2021

Evaluation of Causal Inference Techniques for AIOps.

Vijay Arya, Karthikeyan Shanmugam, Pooja Aggarwal, Qing Wang, Prateeti Mohapatra, Seema Nagar

Proceedings of the CODS-COMAD 2021: 8th ACM IKDD CODS and 26th COMAD, 2021

AI Explainability 360 Toolkit.

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

Proceedings of the CODS-COMAD 2021: 8th ACM IKDD CODS and 26th COMAD, 2021

High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation.

Kristjan H. Greenewald, Karthikeyan Shanmugam, Dmitriy A. Katz-Rogozhnikov

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions.

Kartik Ahuja, Karthikeyan Shanmugam, Amit Dhurandhar

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Detecting Causal Structure on Cloud Application Microservices Using Granger Causality Models.

Qing Wang, Larisa Shwartz, Genady Ya. Grabarnik, Vijay Arya, Karthikeyan Shanmugam

Proceedings of the 14th IEEE International Conference on Cloud Computing, 2021

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 Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang

J. Mach. Learn. Res., 2020

Stochastic Linear Bandits with Protected Subspace.

Advait Parulekar, Soumya Basu, Aditya Gopalan, Karthikeyan Shanmugam, Sanjay Shakkottai

CoRR, 2020

Active Structure Learning of Causal DAGs via Directed Clique Tree.

Chandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam

CoRR, 2020

Fair Data Integration.

Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney

CoRR, 2020

Warm Starting Bandits with Side Information from Confounded Data.

Nihal Sharma, Soumya Basu, Karthikeyan Shanmugam, Sanjay Shakkottai

CoRR, 2020

Learning Global Transparent Models from Local Contrastive Explanations.

Tejaswini Pedapati, Avinash Balakrishnan, Karthikeyan Shanmugam, Amit Dhurandhar

CoRR, 2020

Finite-Sample Analysis of Stochastic Approximation Using Smooth Convex Envelopes.

Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam

CoRR, 2020

Hawkesian Graphical Event Models.

Xiufan Yu, Karthikeyan Shanmugam, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Lingzhou Xue

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

Active Structure Learning of Causal DAGs via Directed Clique Trees.

Chandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Global Transparent Models consistent with Local Contrastive Explanations.

Tejaswini Pedapati, Avinash Balakrishnan, Karthikeyan Shanmugam, Amit Dhurandhar

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Causal Discovery from Soft Interventions with Unknown Targets: Characterization and Learning.

Amin Jaber, Murat Kocaoglu, Karthikeyan Shanmugam, Elias Bareinboim

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Finite-Sample Analysis of Contractive Stochastic Approximation Using Smooth Convex Envelopes.

Zaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Combinatorial Black-Box Optimization with Expert Advice.

Hamid Dadkhahi, Karthikeyan Shanmugam, Jesus Rios, Payel Das, Samuel C. Hoffman, Troy David Loeffler, Subramanian Sankaranarayanan

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Enhancing Simple Models by Exploiting What They Already Know.

Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss

Proceedings of the 37th International Conference on Machine Learning, 2020

Invariant Risk Minimization Games.

Kartik Ahuja, Karthikeyan Shanmugam, Kush R. Varshney, Amit Dhurandhar

Proceedings of the 37th International Conference on Machine Learning, 2020

AI explainability 360: hands-on tutorial.

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

Proceedings of the FAT* '20: Conference on Fairness, 2020

Privacy Enhanced Decision Tree Inference.

Kanthi K. Sarpatwar, Nalini K. Ratha, Karthik Nandakumar, Karthikeyan Shanmugam, James T. Rayfield, Sharath Pankanti, Roman Vaculín

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

A Multi-Channel Neural Graphical Event Model with Negative Evidence.

Tian Gao, Dharmashankar Subramanian, Karthikeyan Shanmugam, Debarun Bhattacharjya, Nicholas Mattei

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Event-Driven Continuous Time Bayesian Networks.

Debarun Bhattacharjya, Karthikeyan Shanmugam, Tian Gao, Nicholas Mattei, Kush R. Varshney, Dharmashankar Subramanian

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Efficient Algorithms for Coded Multicasting in Heterogeneous Caching Networks.

Giuseppe Vettigli, Mingyue Ji, Karthikeyan Shanmugam, Jaime Llorca, Antonia Maria Tulino, Giuseppe Caire

Entropy, 2019

One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques.

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

CoRR, 2019

Model Agnostic Contrastive Explanations for Structured Data.

Amit Dhurandhar, Tejaswini Pedapati, Avinash Balakrishnan, Pin-Yu Chen, Karthikeyan Shanmugam, Ruchir Puri

CoRR, 2019

Leveraging Simple Model Predictions for Enhancing its Performance.

Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss

CoRR, 2019

Generating Contrastive Explanations with Monotonic Attribute Functions.

Ronny Luss, Pin-Yu Chen, Amit Dhurandhar, Prasanna Sattigeri, Karthikeyan Shanmugam, Chun-Chen Tu

CoRR, 2019

Differentially Private Distributed Data Summarization under Covariate Shift.

Kanthi K. Sarpatwar, Karthikeyan Shanmugam, Venkata Sitaramagiridharganesh Ganapavarapu, Ashish Jagmohan, Roman Vaculín

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Characterization and Learning of Causal Graphs with Latent Variables from Soft Interventions.

Murat Kocaoglu, Amin Jaber, Karthikeyan Shanmugam, Elias Bareinboim

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Sample Efficient Active Learning of Causal Trees.

Kristjan H. Greenewald, Dmitriy Katz, Karthikeyan Shanmugam, Sara Magliacane, Murat Kocaoglu, Enric Boix Adserà, Guy Bresler

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Blockchain Enabled AI Marketplace: The Price You Pay for Trust.

Kanthi K. Sarpatwar, Venkata Sitaramagiridharganesh Ganapavarapu, Karthikeyan Shanmugam, Akond Rahman, Roman Vaculín

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

Size of Interventional Markov Equivalence Classes in random DAG models.

Dmitriy Katz, Karthikeyan Shanmugam, Chandler Squires, Caroline Uhler

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Confidence Scoring Using Whitebox Meta-models with Linear Classifier Probes.

Tongfei Chen, Jirí Navrátil, Vijay S. Iyengar, Karthikeyan Shanmugam

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery.

Raj Agrawal, Chandler Squires, Karren D. Yang, Karthikeyan Shanmugam, Caroline Uhler

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Mimic and Classify : A meta-algorithm for Conditional Independence Testing.

Rajat Sen, Karthikeyan Shanmugam, Himanshu Asnani, Arman Rahimzamani, Sreeram Kannan

CoRR, 2018

Structure Learning from Time Series with False Discovery Control.

Bernat Guillen Pegueroles, Bhanukiran Vinzamuri, Karthikeyan Shanmugam, Steve Hedden, Jonathan D. Moyer, Kush R. Varshney

CoRR, 2018

From Centralized to Decentralized Coded Caching.

Yitao Chen, Karthikeyan Shanmugam, Alexandros G. Dimakis

CoRR, 2018

Improving Simple Models with Confidence Profiles.

Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss, Peder A. Olsen

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives.

Amit Dhurandhar, Pin-Yu Chen, Ronny Luss, Chun-Chen Tu, Pai-Shun Ting, Karthikeyan Shanmugam, Payel Das

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Contextual Bandits with Stochastic Experts.

Rajat Sen, Karthikeyan Shanmugam, Sanjay Shakkottai

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Sparse Quadratic Logistic Regression in Sub-quadratic Time.

Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sujay Sanghavi

CoRR, 2017

Causal Best Intervention Identification via Importance Sampling.

Rajat Sen, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai

CoRR, 2017

A Formal Framework to Characterize Interpretability of Procedures.

Amit Dhurandhar, Vijay S. Iyengar, Ronny Luss, Karthikeyan Shanmugam

CoRR, 2017

TIP: Typifying the Interpretability of Procedures.

Amit Dhurandhar, Vijay S. Iyengar, Ronny Luss, Karthikeyan Shanmugam

CoRR, 2017

Model-Powered Conditional Independence Test.

Rajat Sen, Ananda Theertha Suresh, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Experimental Design for Learning Causal Graphs with Latent Variables.

Murat Kocaoglu, Karthikeyan Shanmugam, Elias Bareinboim

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Coded caching with linear subpacketization is possible using Ruzsa-Szeméredi graphs.

Karthikeyan Shanmugam, Antonia Maria Tulino, Alexandros G. Dimakis

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Identifying Best Interventions through Online Importance Sampling.

Rajat Sen, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai

Proceedings of the 34th International Conference on Machine Learning, 2017

Contextual Bandits with Latent Confounders: An NMF Approach.

Rajat Sen, Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sanjay Shakkottai

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

A unified Ruzsa-Szemerédi framework for finite-length coded caching.

Karthikeyan Shanmugam, Alexandros G. Dimakis, Jaime Llorca, Antonia Maria Tulino

Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

2016

Finite-Length Analysis of Caching-Aided Coded Multicasting.

Karthikeyan Shanmugam, Mingyue Ji, Antonia Maria Tulino, Jaime Llorca, Alexandros G. Dimakis

IEEE Trans. Inf. Theory, 2016

Latent Contextual Bandits: A Non-Negative Matrix Factorization Approach.

Rajat Sen, Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sanjay Shakkottai

CoRR, 2016

Distributed Estimation of Graph 4-Profiles.

Ethan R. Elenberg, Karthikeyan Shanmugam, Michael Borokhovich, Alexandros G. Dimakis

Proceedings of the 25th International Conference on World Wide Web, 2016

2015

Learning Causal Graphs with Small Interventions.

Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Beyond Triangles: A Distributed Framework for Estimating 3-profiles of Large Graphs.

Ethan R. Elenberg, Karthikeyan Shanmugam, Michael Borokhovich, Alexandros G. Dimakis

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

On approximating the sum-rate for multiple-unicasts.

Karthikeyan Shanmugam, Megasthenis Asteris, Alexandros G. Dimakis

Proceedings of the IEEE International Symposium on Information Theory, 2015

An efficient multiple-groupcast coded multicasting scheme for finite fractional caching.

Mingyue Ji, Karthikeyan Shanmugam, Giuseppe Vettigli, Jaime Llorca, Antonia Maria Tulino, Giuseppe Caire

Proceedings of the 2015 IEEE International Conference on Communications, 2015

2014

A Repair Framework for Scalar MDS Codes.

Karthikeyan Shanmugam, Dimitris S. Papailiopoulos, Alexandros G. Dimakis, Giuseppe Caire

IEEE J. Sel. Areas Commun., 2014

A Smoothed Analysis for Learning Sparse Polynomials.

Alexandros G. Dimakis, Adam R. Klivans, Murat Kocaoglu, Karthikeyan Shanmugam

CoRR, 2014

On the Information Theoretic Limits of Learning Ising Models.

Rashish Tandon, Karthikeyan Shanmugam, Pradeep Ravikumar, Alexandros G. Dimakis

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Sparse Polynomial Learning and Graph Sketching.

Murat Kocaoglu, Karthikeyan Shanmugam, Alexandros G. Dimakis, Adam R. Klivans

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Graph theory versus minimum rank for index coding.

Karthikeyan Shanmugam, Alexandros G. Dimakis, Michael Langberg

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Bounding multiple unicasts through index coding and Locally Repairable Codes.

Karthikeyan Shanmugam, Alexandros G. Dimakis

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

2013

FemtoCaching: Wireless Content Delivery Through Distributed Caching Helpers.

Karthikeyan Shanmugam, Negin Golrezaei, Alexandros G. Dimakis, Andreas F. Molisch, Giuseppe Caire

IEEE Trans. Inf. Theory, 2013

Local graph coloring and index coding.

Karthikeyan Shanmugam, Alexandros G. Dimakis, Michael Langberg

Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

Index coding problem with side information repositories.

Karthikeyan Shanmugam, Alexandros G. Dimakis, Giuseppe Caire

Proceedings of the 51st Annual Allerton Conference on Communication, 2013

2012

Wireless downloading delay under proportional fair scheduling with coupled service and requests: An approximated analysis.

Karthikeyan Shanmugam, Giuseppe Caire

Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

FemtoCaching: Wireless video content delivery through distributed caching helpers.

Negin Golrezaei, Karthikeyan Shanmugam, Alexandros G. Dimakis, Andreas F. Molisch, Giuseppe Caire

Proceedings of the IEEE INFOCOM 2012, Orlando, FL, USA, March 25-30, 2012, 2012

Wireless video content delivery through coded distributed caching.

Negin Golrezaei, Karthikeyan Shanmugam, Alexandros G. Dimakis, Andreas F. Molisch, Giuseppe Caire

Proceedings of IEEE International Conference on Communications, 2012

2011

An Approach for Validation of Digital Anti-Forensic Evidence.

Karthikeyan Shanmugam, Roger S. Powell, Tom Owens

Inf. Secur. J. A Glob. Perspect., 2011

2010

Rate Gap Analysis for Rate-Adaptive Antenna Selection and Beamforming Schemes.

Karthikeyan Shanmugam, Srikrishna Bhashyam

Proceedings of the Global Communications Conference, 2010

2005

Real Time Vision-based Control of a Carrom Playing Robot.

Guruprasad Somasundaram, Karthik Krishnakumar, Karthikeyan Shanmugam, Vinodh Kumar Rajendran

Proceedings of the 2nd Indian International Conference on Artificial Intelligence, 2005