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ORCIDShana Moothedath
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2020 – today
- 2024
[j13]Shana Moothedath, Dinuka Sahabandu, Joey Allen, Linda Bushnell
, Wenke Lee, Radha Poovendran:
Stochastic Dynamic Information Flow Tracking game using supervised learning for detecting advanced persistent threats. Autom. 159: 111353 (2024)- [j12]Jiabin Lin, Shana Moothedath:
Fast and Sample-Efficient Relevance-Based Multi-Task Representation Learning. IEEE Control. Syst. Lett. 8: 1397-1402 (2024) - [j11]Sharu Theresa Jose, Shana Moothedath:
Thompson Sampling for Stochastic Bandits with Noisy Contexts: An Information-Theoretic Regret Analysis. Entropy 26(7): 606 (2024) - [j10]Shana Moothedath, Dinuka Sahabandu, Joey Allen, Andrew Clark, Linda Bushnell, Wenke Lee, Radha Poovendran:
Dynamic Information Flow Tracking for Detection of Advanced Persistent Threats: A Stochastic Game Approach. IEEE Trans. Autom. Control. 69(10): 6684-6699 (2024) - [c23]Jiabin Lin, Karuna Anna Sajeevan, Bibek Acharya, Shana Moothedath, Ratul Chowdhury:
Distributed Stochastic Contextual Bandits for Protein Drug Interaction. ICASSP 2024: 7160-7164 - [c22]Shana Moothedath, Namrata Vaswani:
Decentralized Low Rank Matrix Recovery from Column-Wise Projections by Alternating GD and Minimization. ICASSP 2024: 12936-12940 - [c21]Jiabin Lin, Shana Moothedath, Namrata Vaswani:
Fast and Sample Efficient Multi-Task Representation Learning in Stochastic Contextual Bandits. ICML 2024 - [c20]Jiabin Lin, Shana Moothedath:
Federated Learning for Heterogeneous Bandits with Unobserved Contexts. ISIT 2024: 2086-2091 - [i14]Jiabin Lin, Shana Moothedath:
Distributed Multi-Task Learning for Stochastic Bandits with Context Distribution and Stage-wise Constraints. CoRR abs/2401.11563 (2024) - [i13]Sharu Theresa Jose, Shana Moothedath:
Thompson Sampling for Stochastic Bandits with Noisy Contexts: An Information-Theoretic Regret Analysis. CoRR abs/2401.11565 (2024) - 2023
- [c19]Ahmed Ali Abbasi, Shana Moothedath, Namrata Vaswani:
Fast Federated Low Rank Matrix Completion. Allerton 2023: 1-6 - [c18]Jiabin Lin, Shana Moothedath:
Feature Selection in Distributed Stochastic Linear Bandits. ACC 2023: 3939-3944 - [c17]Jiabin Lin, Shana Moothedath:
Distributed Stochastic Bandit Learning with Delayed Context Observation. ECC 2023: 1-6 - [c16]Jiabin Lin, Shana Moothedath:
Distributed Stochastic Bandits with Hidden Contexts. ECC 2023: 1-6 - [c15]Shana Moothedath, Namrata Vaswani:
Comparing Decentralized Gradient Descent Approaches and Guarantees. ICASSP 2023: 1-5 - [i12]Jiabin Lin, Shana Moothedath:
Federated Stochastic Bandit Learning with Unobserved Context. CoRR abs/2303.17043 (2023) - [i11]Geethu Joseph, Shana Moothedath, Jiabin Lin:
Minimal Input Structural Modifications for Strongly Structural Controllability. CoRR abs/2311.05653 (2023) - 2022
- [c14]Shana Moothedath, Namrata Vaswani:
Fully Decentralized and Federated Low Rank Compressive Sensing. ACC 2022: 1491-1496 - [c13]Shana Moothedath, Namrata Vaswani:
Dec-AltProjGDmin: Fully-Decentralized Alternating Projected Gradient Descent for Low Rank Column-wise Compressive Sensing. CDC 2022: 1648-1653 - [c12]Jiabin Lin, Xian Yeow Lee, Talukder Z. Jubery, Shana Moothedath, Soumik Sarkar, Baskar Ganapathysubramanian:
Stochastic Conservative Contextual Linear Bandits. CDC 2022: 7321-7326 - [i10]Jiabin Lin, Xian Yeow Lee, Talukder Z. Jubery, Shana Moothedath, Soumik Sarkar, Baskar Ganapathysubramanian:
Stochastic Conservative Contextual Linear Bandits. CoRR abs/2203.15629 (2022) - [i9]Shana Moothedath, Namrata Vaswani:
Fully-Decentralized Alternating Projected Gradient Descent for Low Rank column-wise Compressive Sensing. CoRR abs/2204.08117 (2022) - [i8]Jiabin Lin, Shana Moothedath:
Distributed Stochastic Bandit Learning with Context Distributions. CoRR abs/2207.14391 (2022) - 2021
- [j9]RaviTeja Gundeti, Shana Moothedath, Prasanna Chaporkar:
Feedback Robustness in Structured Closed-loop System. Eur. J. Control 57: 95-108 (2021) - [i7]Shana Moothedath, Namrata Vaswani:
Fully Decentralized and Federated Low Rank Compressive Sensing. CoRR abs/2112.13412 (2021) - 2020
- [j8]Shana Moothedath, Dinuka Sahabandu, Joey Allen, Andrew Clark, Linda Bushnell, Wenke Lee, Radha Poovendran:
A Game-Theoretic Approach for Dynamic Information Flow Tracking to Detect Multistage Advanced Persistent Threats. IEEE Trans. Autom. Control. 65(12): 5248-5263 (2020) - [j7]Aishwary Joshi, Shana Moothedath, Prasanna Chaporkar:
Minimum Cost Feedback Selection in Structured Systems: Hardness and Approximation Algorithm. IEEE Trans. Autom. Control. 65(12): 5517-5524 (2020) - [j6]Shana Moothedath, Prasanna Chaporkar, Madhu N. Belur:
Optimal Network Topology Design in Composite Systems for Structural Controllability. IEEE Trans. Control. Netw. Syst. 7(3): 1164-1175 (2020) - [c11]Dinuka Sahabandu, Joey Allen, Shana Moothedath, Linda Bushnell, Wenke Lee, Radha Poovendran:
Quickest Detection of Advanced Persistent Threats: A Semi-Markov Game Approach. ICCPS 2020: 9-19 - [i6]Shana Moothedath, Dinuka Sahabandu, Joey Allen, Andrew Clark, Linda Bushnell, Wenke Lee, Radha Poovendran:
Dynamic Information Flow Tracking for Detection of Advanced Persistent Threats: A Stochastic Game Approach. CoRR abs/2006.12327 (2020) - [i5]Dinuka Sahabandu, Shana Moothedath, Joey Allen, Linda Bushnell, Wenke Lee, Radha Poovendran:
A Multi-Agent Reinforcement Learning Approach for Dynamic Information Flow Tracking Games for Advanced Persistent Threats. CoRR abs/2007.00076 (2020) - [i4]Shana Moothedath, Dinuka Sahabandu, Joey Allen, Linda Bushnell, Wenke Lee, Radha Poovendran:
Stochastic Dynamic Information Flow Tracking Game using Supervised Learning for Detecting Advanced Persistent Threats. CoRR abs/2007.12327 (2020)
2010 – 2019
- 2019
- [j5]Shana Moothedath, Prasanna Chaporkar, Madhu N. Belur:
Optimal selection of essential interconnections for structural controllability in heterogeneous subsystems. Autom. 103: 424-434 (2019) - [j4]Shana Moothedath, Prasanna Chaporkar, Madhu N. Belur:
Approximating constrained minimum cost input-output selection for generic arbitrary pole placement in structured systems. Autom. 107: 200-210 (2019) - [j3]Shana Moothedath, Prasanna Chaporkar, Madhu N. Belur:
Sparsest Feedback Selection for Structurally Cyclic Systems With Dedicated Actuators and Sensors in Polynomial Time. IEEE Trans. Autom. Control. 64(9): 3956-3963 (2019) - [c10]Kumar Yashashwi, Shana Moothedath, Prasanna Chaporkar:
Minimizing Inputs for Strong Structural Controllability. ACC 2019: 2048-2053 - [c9]Shana Moothedath, Prasanna Chaporkar, Aishwary Joshi:
Optimal Network Topology Design in Composite Systems with Constrained Neighbors for Structural Controllability. ACC 2019: 2078-2083 - [c8]Dinuka Sahabandu, Shana Moothedath, Linda Bushnell, Radha Poovendran, Joey Allen, Wenke Lee, Andrew Clark:
A Game Theoretic Approach for Dynamic Information Flow Tracking with Conditional Branching. ACC 2019: 2289-2296 - [c7]Dinuka Sahabandu, Shana Moothedath, Joey Allen, Andrew Clark, Linda Bushnell, Wenke Lee, Radha Poovendran:
Dynamic Information Flow Tracking Games for Simultaneous Detection of Multiple Attackers. CDC 2019: 567-574 - [c6]Shruti Misra, Shana Moothedath, Hossein Hosseini, Joey Allen, Linda Bushnell, Wenke Lee, Radha Poovendran:
Learning Equilibria in Stochastic Information Flow Tracking Games with Partial Knowledge. CDC 2019: 4053-4060 - [c5]Shana Moothedath, Kumar Yashashwi, Prasanna Chaporkar, Madhu N. Belur:
Target Controllability of Structured Systems. ECC 2019: 3484-3489 - [c4]Dinuka Sahabandu, Shana Moothedath, Joey Allen, Linda Bushnell, Wenke Lee, Radha Poovendran:
Stochastic Dynamic Information Flow Tracking Game with Reinforcement Learning. GameSec 2019: 417-438 - 2018
- [j2]Shana Moothedath, Prasanna Chaporkar, Madhu N. Belur:
A Flow-Network-Based Polynomial-Time Approximation Algorithm for the Minimum Constrained Input Structural Controllability Problem. IEEE Trans. Autom. Control. 63(9): 3151-3158 (2018) - [j1]Shana Moothedath, Prasanna Chaporkar, Madhu N. Belur:
Minimum Cost Feedback Selection for Arbitrary Pole Placement in Structured Systems. IEEE Trans. Autom. Control. 63(11): 3881-3888 (2018) - [c3]Shana Moothedath, Prasanna Chaporkar, Madhu N. Belur:
A Randomized Algorithm for Minimum Cost Constrained Input Selection for State Space Structural Controllability. ECC 2018: 483-488 - [c2]Shana Moothedath, Dinuka Sahabandu, Andrew Clark, Sangho Lee, Wenke Lee, Radha Poovendran:
Multi-stage Dynamic Information Flow Tracking Game. GameSec 2018: 80-101 - [i3]Shana Moothedath, Dinuka Sahabandu, Joey Allen, Andrew Clark, Linda Bushnell, Wenke Lee, Radha Poovendran:
A Game Theoretic Approach for Dynamic Information Flow Tracking to Detect Multi-Stage Advanced Persistent Threats. CoRR abs/1811.05622 (2018) - 2017
- [i2]Shana Moothedath, Prasanna Chaporkar, Madhu N. Belur:
Approximating Constrained Minimum Cost Input-Output Selection for Generic Arbitrary Pole Placement in Structured Systems. CoRR abs/1705.09600 (2017) - [i1]Shana Moothedath, Prasanna Chaporkar, Madhu N. Belur:
Rapidly Mixing Markov Chain Monte Carlo Technique for Matching Problems with Global Utility Function. CoRR abs/1710.10037 (2017) - 2016
- [c1]Saurabh Kumar, Shana Moothedath, Prasanna Chaporkar, Madhu N. Belur:
An MCMC Based Course to Teaching Assistant Allocation. ICNCC 2016: 131-134
Coauthor Index
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