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Karthikeyan Shanmugam

Identifiers

  • name variant Karthikeyan Shanmugam 0.60 · backfill

Papers (75)

  1. Inferring Asteroseismic Parameters from Short Observations Using Deep Learning: Application to TESS and K2 Red Giants astro-ph.SR · 2026 · author #5
  2. Regret minimization in Linear Bandits with offline data via extended D-optimal exploration cs.LG · 2025 · author #3
  3. Bayesian Collaborative Bandits with Thompson Sampling for Improved Outreach in Maternal Health Program cs.LG · 2024 · author #4
  4. Linear Causal Representation Learning from Unknown Multi-node Interventions cs.LG · 2024 · author #3
  5. A resource-constrained stochastic scheduling algorithm for homeless street outreach and gleaning edible food cs.LG · 2024 · author #7
  6. Blocked Collaborative Bandits: Online Collaborative Filtering with Per-Item Budget Constraints cs.IR · 2023 · author #3
  7. General Identifiability and Achievability for Causal Representation Learning cs.LG · 2023 · author #3
  8. Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation cs.LG · 2023 · author #4
  9. Fairness under Covariate Shift: Improving Fairness-Accuracy tradeoff with few Unlabeled Test Samples cs.LG · 2023 · author #3
  10. Identifiability Guarantees for Causal Disentanglement from Soft Interventions stat.ML · 2023 · author #5
  11. Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge cs.LG · 2023 · author #2
  12. Optimal Best-Arm Identification in Bandits with Access to Offline Data cs.LG · 2023 · author #3
  13. InfoNCE Loss Provably Learns Cluster-Preserving Representations cs.LG · 2023 · author #3
  14. Score-based Causal Representation Learning with Interventions stat.ML · 2023 · author #3
  15. Optimal Algorithms for Latent Bandits with Cluster Structure cs.LG · 2023 · author #3
  16. Selective classification using a robust meta-learning approach cs.LG · 2022 · author #2
  17. Causal Bandits for Linear Structural Equation Models stat.ML · 2022 · author #2
  18. Attribute Graphs Underlying Molecular Generative Models: Path to Learning with Limited Data cs.LG · 2022 · author #3
  19. PAC Generalization via Invariant Representations cs.LG · 2022 · author #2
  20. Fourier Representations for Black-Box Optimization over Categorical Variables cs.LG · 2022 · author #3
  21. Auto-Transfer: Learning to Route Transferrable Representations cs.LG · 2022 · author #4
  22. Scalable Intervention Target Estimation in Linear Models stat.ME · 2021 · author #2
  23. AI Explainability 360: Impact and Design cs.LG · 2021 · author #16
  24. Bandits with Stochastic Experts: Constant Regret, Empirical Experts and Episodes cs.LG · 2021 · author #4
  25. Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators cs.LG · 2021 · author #4
  26. Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge cs.LG · 2021 · author #2
  27. Treatment Effect Estimation using Invariant Risk Minimization cs.LG · 2021 · author #3
  28. Efficient Encrypted Inference on Ensembles of Decision Trees cs.CR · 2021 · author #5
  29. A Lyapunov Theory for Finite-Sample Guarantees of Asynchronous Q-Learning and TD-Learning Variants cs.LG · 2021 · author #4
  30. Stochastic Linear Bandits with Protected Subspace cs.LG · 2020 · author #4
  31. Active Structure Learning of Causal DAGs via Directed Clique Tree stat.ME · 2020 · author #6
  32. Empirical or Invariant Risk Minimization? A Sample Complexity Perspective cs.LG · 2020 · author #4
  33. Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions cs.LG · 2020 · author #2
  34. Causal Feature Selection for Algorithmic Fairness cs.LG · 2020 · author #2
  35. Combinatorial Black-Box Optimization with Expert Advice cs.LG · 2020 · author #2
  36. A Multi-Channel Neural Graphical Event Model with Negative Evidence cs.LG · 2020 · author #3
  37. Bandits with Mean Bounds cs.LG · 2020 · author #3
  38. Learning Global Transparent Models Consistent with Local Contrastive Explanations cs.LG · 2020 · author #3
  39. Invariant Risk Minimization Games cs.LG · 2020 · author #2
  40. Finite-Sample Analysis of Stochastic Approximation Using Smooth Convex Envelopes cs.LG · 2020 · author #4
  41. Differentially Private Distributed Data Summarization under Covariate Shift cs.LG · 2019 · author #2
  42. One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques cs.AI · 2019 · author #16
  43. Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions stat.ML · 2019 · author #3
  44. Model Agnostic Contrastive Explanations for Structured Data cs.LG · 2019 · author #5
  45. Enhancing Simple Models by Exploiting What They Already Know cs.LG · 2019 · author #2
  46. Leveraging Latent Features for Local Explanations cs.LG · 2019 · author #6
  47. Size of Interventional Markov Equivalence Classes in Random DAG Models stat.ML · 2019 · author #2
  48. Improving Simple Models with Confidence Profiles cs.LG · 2018 · author #2
  49. Mimic and Classify : A meta-algorithm for Conditional Independence Testing stat.ML · 2018 · author #2
  50. Structure Learning from Time Series with False Discovery Control stat.ML · 2018 · author #3
  51. Confidence Scoring Using Whitebox Meta-models with Linear Classifier Probes cs.LG · 2018 · author #4
  52. Contextual Bandits with Stochastic Experts stat.ML · 2018 · author #2
  53. Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives cs.AI · 2018 · author #6
  54. From Centralized to Decentralized Coded Caching cs.IT · 2018 · author #2
  55. Model-Powered Conditional Independence Test stat.ML · 2017 · author #3
  56. A Formal Framework to Characterize Interpretability of Procedures cs.AI · 2017 · author #4
  57. TIP: Typifying the Interpretability of Procedures cs.AI · 2017 · author #4
  58. Sparse Quadratic Logistic Regression in Sub-quadratic Time stat.ML · 2017 · author #1
  59. Coded Caching with Linear Subpacketization is Possible using Ruzsa-Szem\'eredi Graphs cs.IT · 2017 · author #1
  60. Identifying Best Interventions through Online Importance Sampling stat.ML · 2017 · author #2
  61. Contextual Bandits with Latent Confounders: An NMF Approach cs.LG · 2016 · author #2
  62. An Efficient Multiple-Groupcast Coded Multicasting Scheme for Finite Fractional Caching cs.IT · 2015 · author #2
  63. Learning Causal Graphs with Small Interventions cs.AI · 2015 · author #1
  64. Distributed Estimation of Graph 4-Profiles cs.SI · 2015 · author #2
  65. Finite Length Analysis of Caching-Aided Coded Multicasting cs.IT · 2015 · author #1
  66. Beyond Triangles: A Distributed Framework for Estimating 3-profiles of Large Graphs cs.SI · 2015 · author #2
  67. On Approximating the Sum-Rate for Multiple-Unicasts cs.IT · 2015 · author #1
  68. On the Information Theoretic Limits of Learning Ising Models cs.LG · 2014 · author #1
  69. Sparse Polynomial Learning and Graph Sketching cs.LG · 2014 · author #2
  70. Graph Theory versus Minimum Rank for Index Coding cs.IT · 2014 · author #1
  71. Bounding Multiple Unicasts through Index Coding and Locally Repairable Codes cs.IT · 2014 · author #1
  72. A Repair Framework for Scalar MDS Codes cs.IT · 2013 · author #1
  73. Index Coding Problem with Side Information Repositories cs.IT · 2013 · author #1
  74. Local Graph Coloring and Index Coding cs.IT · 2013 · author #1
  75. FemtoCaching: Wireless Video Content Delivery through Distributed Caching Helpers cs.NI · 2011 · author #1

Mentions

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Frequent Coauthors