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ORCIDVikram Krishnamurthy
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- affiliation: Cornell University, Ithaca, NY, USA
- affiliation: University of British Columbia, Vancouver, Canada
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2020 – today
- 2024
[j189]Luke Snow, Shashwat Jain, Vikram Krishnamurthy:
Lyapunov based stochastic stability of a quantum decision system for human-machine interaction. Autom. 164: 111628 (2024)- [j188]Amir Leshem, Vikram Krishnamurthy, Tomer Boyarski:
Distributed learning in congested environments with partial information. Autom. 169: 111817 (2024) - [j187]Adit Jain
, Vikram Krishnamurthy:
Structured Reinforcement Learning for Incentivized Stochastic Covert Optimization. IEEE Control. Syst. Lett. 8: 1295-1300 (2024) - [j186]Rui Luo, Vikram Krishnamurthy:
Fréchet-Statistics-Based Change Point Detection in Dynamic Social Networks. IEEE Trans. Comput. Soc. Syst. 11(2): 2863-2871 (2024) - [j185]Rui Luo, Buddhika Nettasinghe, Vikram Krishnamurthy:
Mutual Information Measure for Glass Ceiling Effect in Preferential Attachment Models. IEEE Trans. Comput. Soc. Syst. 11(6): 7778-7788 (2024) - [j184]Adit Jain, Vikram Krishnamurthy:
Controlling Federated Learning for Covertness. Trans. Mach. Learn. Res. 2024 (2024) - [c183]Vikram Krishnamurthy, Cristian R. Rojas:
Slow Convergence of Interacting Kalman Filters in Word-of-Mouth Social Learning. Allerton 2024: 1-6 - [i87]Shashwat Jain, Vikram Krishnamurthy, Muralidhar Rangaswamy, Bosung Kang, Sandeep Gogineni:
Fisher Information Approach for Masking the Sensing Plan: Applications in Multifunction Radars. CoRR abs/2403.15966 (2024) - [i86]Luke Snow, Vikram Krishnamurthy:
Adaptive Mechanism Design using Multi-Agent Revealed Preferences. CoRR abs/2404.15391 (2024) - [i85]Adit Jain, Vikram Krishnamurthy:
Structured Reinforcement Learning for Incentivized Stochastic Covert Optimization. CoRR abs/2405.07415 (2024) - [i84]Adit Jain, Vikram Krishnamurthy:
Identifying Hate Speech Peddlers in Online Platforms. A Bayesian Social Learning Approach for Large Language Model Driven Decision-Makers. CoRR abs/2405.07417 (2024) - [i83]Luke Snow, Vikram Krishnamurthy:
Distributionally Robust Inverse Reinforcement Learning for Identifying Multi-Agent Coordinated Sensing. CoRR abs/2409.14542 (2024) - [i82]Vikram Krishnamurthy, Cristian R. Rojas:
Slow Convergence of Interacting Kalman Filters in Word-of-Mouth Social Learning. CoRR abs/2410.08447 (2024) - [i81]George Yin, Vikram Krishnamurthy:
Finite Sample and Large Deviations Analysis of Stochastic Gradient Algorithm with Correlated Noise. CoRR abs/2410.08449 (2024) - [i80]Adit Jain, Soumyabrata Pal, Sunav Choudhary, Ramasuri Narayanam, Vikram Krishnamurthy:
Annotation Efficiency: Identifying Hard Samples via Blocked Sparse Linear Bandits. CoRR abs/2410.20041 (2024) - [i79]Adit Jain, Vikram Krishnamurthy:
Interacting Large Language Model Agents. Interpretable Models and Social Learning. CoRR abs/2411.01271 (2024) - 2023
- [j183]Vikram Krishnamurthy:
Interval dominance based structural results for Markov decision process. Autom. 153: 111024 (2023) - [j182]Kunal Pattanayak, Vikram Krishnamurthy:
Necessary and Sufficient Conditions for Inverse Reinforcement Learning of Bayesian Stopping Time Problems. J. Mach. Learn. Res. 24: 52:1-52:64 (2023) - [j181]Shashwat Jain, Vikram Krishnamurthy, Muralidhar Rangaswamy, Bosung Kang, Sandeep Gogineni:
Radar Clutter Covariance Estimation: A Nonlinear Spectral Shrinkage Approach. IEEE Trans. Aerosp. Electron. Syst. 59(6): 7640-7653 (2023) - [j180]Kunal Pattanayak, Vikram Krishnamurthy, Christopher Berry:
Metacognitive Radar: Masking Cognition From an Inverse Reinforcement Learner. IEEE Trans. Aerosp. Electron. Syst. 59(6): 8826-8844 (2023) - [j179]Vikram Krishnamurthy:
Adaptive Filtering Algorithms for Set-Valued Observations - Symmetric Measurement Approach to Unlabeled and Anonymized Data. IEEE Trans. Signal Process. 71: 2760-2775 (2023) - [c182]Luke Snow, Vikram Krishnamurthy:
Finite-Sample Bounds for Adaptive Inverse Reinforcement Learning Using Passive Langevin Dynamics. CDC 2023: 3618-3625 - [c181]Rui Luo, Buddhika Nettasinghe, Vikram Krishnamurthy:
Anomalous Edge Detection in Edge Exchangeable Social Network Models. COPA 2023: 287-310 - [c180]Luke Snow, Vikram Krishnamurthy, Brian M. Sadler:
Statistical Detection of Coordination in a Cognitive Radar Network through Inverse Multi-Objective Optimization. FUSION 2023: 1-8 - [c179]Shashwat Jain, Vikram Krishnamurthy, Muralidhar Rangaswamy, Bosung Kang, Sandeep Gogineni:
Radar Clutter Covariance Estimation: A Nonlinear Spectral Shrinkage Approach. ICASSP 2023: 1-5 - [c178]Shashwat Jain, Kunal Pattanayak, Vikram Krishnamurthy, Christopher Berry:
Adaptive Eccm for Mitigating Smart Jammers. ICASSP 2023: 1-5 - [c177]Vikram Krishnamurthy:
Adaptive Filtering Algorithms For Set-Valued Observations-Symmetric Measurement Approach To Unlabeled And Anonymized Data. ICASSP 2023: 1-5 - [c176]Luke Snow, Vikram Krishnamurthy, Brian M. Sadler:
Identifying Coordination in a Cognitive Radar Network - A Multi-Objective Inverse Reinforcement Learning Approach. ICASSP 2023: 1-5 - [i78]Rui Luo, Buddhika Nettasinghe, Vikram Krishnamurthy:
Mutual Information Measure for Glass Ceiling Effect in Preferential Attachment Models. CoRR abs/2303.09990 (2023) - [i77]Rui Luo, Vikram Krishnamurthy:
Fréchet Statistics Based Change Point Detection in Dynamic Social Networks. CoRR abs/2303.10753 (2023) - [i76]Rui Luo, Vikram Krishnamurthy:
Who You Play Affects How You Play: Predicting Sports Performance Using Graph Attention Networks With Temporal Convolution. CoRR abs/2303.16741 (2023) - [i75]Luke Snow, Vikram Krishnamurthy:
Finite-Sample Bounds for Adaptive Inverse Reinforcement Learning using Passive Langevin Dynamics. CoRR abs/2304.09123 (2023) - [i74]Anurag Gupta, Vikram Krishnamurthy:
Energy-Efficient Mining for Blockchain-Enabled IoT Applications. An Optimal Multiple-Stopping Time Approach. CoRR abs/2305.05479 (2023) - [i73]Rui Luo, Vikram Krishnamurthy:
Fréchet Statistics Based Change Point Detection in Multivariate Hawkes Process. CoRR abs/2308.06769 (2023) - [i72]Adit Jain, Vikram Krishnamurthy:
Controlling Federated Learning for Covertness. CoRR abs/2308.08825 (2023) - 2022
- [j178]Vikram Krishnamurthy, George Yin:
Multikernel Passive Stochastic Gradient Algorithms and Transfer Learning. IEEE Trans. Autom. Control. 67(4): 1792-1805 (2022) - [j177]Anurag Gupta, Vikram Krishnamurthy:
Principal-Agent Problem as a Principled Approach to Electronic Counter-Countermeasures in Radar. IEEE Trans. Aerosp. Electron. Syst. 58(4): 3223-3235 (2022) - [j176]Rui Luo, Buddhika Nettasinghe, Vikram Krishnamurthy:
Echo Chambers and Segregation in Social Networks: Markov Bridge Models and Estimation. IEEE Trans. Comput. Soc. Syst. 9(3): 891-901 (2022) - [j175]Rui Luo, Buddhika Nettasinghe, Vikram Krishnamurthy:
Controlling Segregation in Social Network Dynamics as an Edge Formation Game. IEEE Trans. Netw. Sci. Eng. 9(4): 2317-2329 (2022) - [c175]Vikram Krishnamurthy, Luke Snow:
Quickest Change Detection using Time Inconsistent Anticipatory and Quantum Decision Modeling. Allerton 2022: 1-8 - [c174]Luke Snow, Shashwat Jain, Vikram Krishnamurthy:
Lyapunov based Stochastic Stability of Human-Machine Interaction: A Quantum Decision System Approach. CDC 2022: 3170-3175 - [c173]Kunal Pattanayak, Vikram Krishnamurthy, Christopher Berry:
Inverse-Inverse Reinforcement Learning. How to Hide Strategy from an Adversarial Inverse Reinforcement Learner. CDC 2022: 3631-3636 - [c172]Kunal Pattanayak, Vikram Krishnamurthy, Christopher Berry:
Meta-Cognition. An Inverse-Inverse Reinforcement Learning Approach for Cognitive Radars. FUSION 2022: 1-8 - [c171]Kunal Pattanayak, Vikram Krishnamurthy, Christopher Berry:
How Can a Cognitive Radar Mask its Cognition? ICASSP 2022: 5897-5901 - [i71]Rui Luo, Vikram Krishnamurthy:
Mitigating Misinformation Spread on Blockchain Enabled Social Media Networks. CoRR abs/2201.07076 (2022) - [i70]Anurag Gupta, Vikram Krishnamurthy:
Controlling Transaction Rate in Tangle Ledger: A Principal Agent Problem Approach. CoRR abs/2203.05643 (2022) - [i69]Vikram Krishnamurthy:
Interval Dominance based Structural Results for Markov Decision Process. CoRR abs/2203.10618 (2022) - [i68]Rui Luo, Vikram Krishnamurthy, Erik Blasch:
Hawkes Process Modeling of Block Arrivals in Bitcoin Blockchain. CoRR abs/2203.16666 (2022) - [i67]Luke Snow, Shashwat Jain, Vikram Krishnamurthy:
Lyapunov based Stochastic Stability of Human-Machine Interaction: A Quantum Decision System Approach. CoRR abs/2204.00059 (2022) - [i66]Kunal Pattanayak, Vikram Krishnamurthy, Christopher Berry:
Meta-Cognition. An Inverse-Inverse Reinforcement Learning Approach for Cognitive Radars. CoRR abs/2205.01794 (2022) - [i65]Kunal Pattanayak, Vikram Krishnamurthy, Christopher Berry:
Inverse-Inverse Reinforcement Learning. How to Hide Strategy from an Adversarial Inverse Reinforcement Learner. CoRR abs/2205.10802 (2022) - [i64]Luke Snow, Shashwat Jain, Vikram Krishnamurthy:
Lyapunov based Stochastic Stability of a Quantum Decision System for Human-Machine Interaction. CoRR abs/2205.12378 (2022) - [i63]Buddhika Nettasinghe, Kowe Kadoma, Mor Naaman, Vikram Krishnamurthy:
Estimating Exposure to Information on Social Networks. CoRR abs/2207.05980 (2022) - [i62]Luke Snow, Vikram Krishnamurthy, Brian M. Sadler:
Quickest Detection for Human-Sensor Systems using Quantum Decision Theory. CoRR abs/2208.08583 (2022) - [i61]Vikram Krishnamurthy:
Adaptive Filtering Algorithms for Set-Valued Observations - Symmetric Measurement Approach to Unlabeled and Anonymized Data. CoRR abs/2208.14576 (2022) - [i60]Kunal Pattanayak, Vikram Krishnamurthy, Christopher Berry:
How can a Radar Mask its Cognition? CoRR abs/2210.11444 (2022) - [i59]Luke Snow, Vikram Krishnamurthy, Brian M. Sadler:
Identifying Coordination in a Cognitive Radar Network - A Multi-Objective Inverse Reinforcement Learning Approach. CoRR abs/2211.06967 (2022) - [i58]Kunal Pattanayak, Shashwat Jain, Vikram Krishnamurthy, Christopher Berry:
Adaptive ECCM for Mitigating Smart Jammers. CoRR abs/2212.02002 (2022) - 2021
- [j174]Buddhika Nettasinghe, Nazanin Alipourfard, Stephen Iota, Vikram Krishnamurthy, Kristina Lerman:
Scale-free degree distributions, homophily and the glass ceiling effect in directed networks. J. Complex Networks 10(2) (2021) - [j173]Vikram Krishnamurthy, George Yin:
Langevin Dynamics for Adaptive Inverse Reinforcement Learning of Stochastic Gradient Algorithms. J. Mach. Learn. Res. 22: 121:1-121:49 (2021) - [j172]Geethu Joseph, Buddhika Nettasinghe, Vikram Krishnamurthy, Pramod K. Varshney:
Controllability of Network Opinion in Erdös-Rényi Graphs Using Sparse Control Inputs. SIAM J. Control. Optim. 59(3): 2321-2345 (2021) - [j171]Sujay Bhatt, Vikram Krishnamurthy:
Controlled Sequential Information Fusion With Social Sensors. IEEE Trans. Autom. Control. 66(12): 5893-5908 (2021) - [j170]Bashar I. Ahmad, Simon J. Godsill, Vikram Krishnamurthy, Peter Willett, Muralidhar Rangaswamy:
Foreword to the Special Section on Meta-Level and Adversarial Tracking. IEEE Trans. Aerosp. Electron. Syst. 57(4): 1994-1995 (2021) - [j169]Vikram Krishnamurthy, Kunal Pattanayak, Sandeep Gogineni, Bosung Kang, Muralidhar Rangaswamy:
Adversarial Radar Inference: Inverse Tracking, Identifying Cognition, and Designing Smart Interference. IEEE Trans. Aerosp. Electron. Syst. 57(4): 2067-2081 (2021) - [j168]William Hoiles, S. M. Shahrear Tanzil, Vikram Krishnamurthy:
Risk-Averse Caching Policies for YouTube Content in Femtocell Networks using Density Forecasting. IEEE Trans. Cloud Comput. 9(1): 331-346 (2021) - [j167]Buddhika Nettasinghe, Vikram Krishnamurthy:
Maximum Likelihood Estimation of Power-law Degree Distributions via Friendship Paradox-based Sampling. ACM Trans. Knowl. Discov. Data 15(6): 106:1-106:28 (2021) - [j166]Buddhika Nettasinghe, Vikram Krishnamurthy:
"What Do Your Friends Think?": Efficient Polling Methods for Networks Using Friendship Paradox. IEEE Trans. Knowl. Data Eng. 33(3): 1291-1305 (2021) - [j165]Vikram Krishnamurthy:
Quickest Change Detection of Time Inconsistent Anticipatory Agents. Human-Sensor and Cyber-Physical Systems. IEEE Trans. Signal Process. 69: 1054-1069 (2021) - [c170]Alec Koppel, Amrit S. Bedi, Vikram Krishnamurthy:
A Dynamical Systems Perspective on Online Bayesian Nonparametric Estimators with Adaptive Hyperparameters. ICASSP 2021: 2975-2979 - [c169]Vikram Krishnamurthy:
Quickest Change Detection With Time Inconsistent Anticipatory Agents In Cyber-Physical Systems. ICASSP 2021: 5000-5004 - [c168]Vikram Krishnamurthy, Rui Luo, Buddhika Nettasinghe:
Segregation in Social Networks: MARKOV Bridge Models and Estimation. ICASSP 2021: 5484-5488 - [i57]Kunal Pattanayak, Vikram Krishnamurthy:
Behavioral Economics Approach to Interpretable Deep Image Classification. Rationally Inattentive Utility Maximization Explains Deep Image Classification. CoRR abs/2102.04594 (2021) - [i56]Buddhika Nettasinghe, Nazanin Alipourfard, Vikram Krishnamurthy, Kristina Lerman:
Emergence of Structural Inequalities in Scientific Citation Networks. CoRR abs/2103.10944 (2021) - [i55]Buddhika Nettasinghe, Nazanin Alipourfard, Vikram Krishnamurthy, Kristina Lerman:
A Directed, Bi-Populated Preferential Attachment Model with Applications to Analyzing the Glass Ceiling Effect. CoRR abs/2103.12149 (2021) - [i54]Tomer Boyarski, Amir Leshem, Vikram Krishnamurthy:
Distributed learning in congested environments with partial information. CoRR abs/2103.15901 (2021) - [i53]Kunal Pattanayak, Vikram Krishnamurthy:
Unifying Classical and Bayesian Revealed Preference. CoRR abs/2106.14486 (2021) - [i52]Rui Luo, Buddhika Nettasinghe, Vikram Krishnamurthy:
Controlling Segregation in Social Network Dynamics as an Edge Formation Game. CoRR abs/2108.12741 (2021) - [i51]Rui Luo, Buddhika Nettasinghe, Vikram Krishnamurthy:
Anomalous Edge Detection in Edge Exchangeable Social Network Models. CoRR abs/2109.12727 (2021) - 2020
- [j164]William Hoiles, Vikram Krishnamurthy, Kunal Pattanayak:
Rationally Inattentive Inverse Reinforcement Learning Explains YouTube Commenting Behavior. J. Mach. Learn. Res. 21: 170:1-170:39 (2020) - [j163]Vikram Krishnamurthy:
Convex Stochastic Dominance in Bayesian Localization, Filtering, and Controlled Sensing POMDPs. IEEE Trans. Inf. Theory 66(5): 3187-3201 (2020) - [j162]Buddhika Nettasinghe, Vikram Krishnamurthy, Kristina Lerman:
Diffusion in Social Networks: Effects of Monophilic Contagion, Friendship Paradox, and Reactive Networks. IEEE Trans. Netw. Sci. Eng. 7(3): 1121-1132 (2020) - [j161]Vikram Krishnamurthy, Daniel Angley, Robin J. Evans, Bill Moran:
Identifying Cognitive Radars - Inverse Reinforcement Learning Using Revealed Preferences. IEEE Trans. Signal Process. 68: 4529-4542 (2020) - [j160]Robert Mattila, Cristian R. Rojas, Vikram Krishnamurthy, Bo Wahlberg:
Inverse Filtering for Hidden Markov Models With Applications to Counter-Adversarial Autonomous Systems. IEEE Trans. Signal Process. 68: 4987-5002 (2020) - [c167]Kunal Pattanayak, Vikram Krishnamurthy, Erik Blasch:
Inverse Sequential Hypothesis Testing. FUSION 2020: 1-7 - [c166]Robert Mattila, Inês Lourenço, Vikram Krishnamurthy, Cristian R. Rojas, Bo Wahlberg:
What did your adversary believeƒ Optimal Filtering and Smoothing in Counter-Adversarial Autonomous Systems. ICASSP 2020: 5495-5499 - [c165]Robert Mattila, Cristian R. Rojas, Eric Moulines, Vikram Krishnamurthy, Bo Wahlberg:
Fast and Consistent Learning of Hidden Markov Models by Incorporating Non-Consecutive Correlations. ICML 2020: 6785-6796 - [i50]Robert Mattila, Cristian R. Rojas, Vikram Krishnamurthy, Bo Wahlberg:
Inverse Filtering for Hidden Markov Models with Applications to Counter-Adversarial Autonomous Systems. CoRR abs/2001.11809 (2020) - [i49]Vikram Krishnamurthy:
Anticipatory Psychological Models for Quickest Change Detection: Human Sensor Interaction. CoRR abs/2003.10910 (2020) - [i48]Geethu Joseph, Buddhika Nettasinghe, Vikram Krishnamurthy, Pramod K. Varshney:
Controllability of Network Opinion in Erdős-Rényi Graphs using Sparse Control Inputs. CoRR abs/2003.12817 (2020) - [i47]Sujay Bhatt, Alec Koppel, Vikram Krishnamurthy:
Policy Gradient using Weak Derivatives for Reinforcement Learning. CoRR abs/2004.04843 (2020) - [i46]Vikram Krishnamurthy, George Yin:
Langevin Dynamics for Inverse Reinforcement Learning of Stochastic Gradient Algorithms. CoRR abs/2006.11674 (2020) - [i45]Kunal Pattanayak, Vikram Krishnamurthy:
Inverse Reinforcement Learning for Sequential Hypothesis Testing and Search. CoRR abs/2007.03481 (2020) - [i44]Vikram Krishnamurthy, Kunal Pattanayak, Sandeep Gogineni, Bosung Kang, Muralidhar Rangaswamy:
Adversarial Radar Inference: Inverse Tracking, Identifying Cognition and Designing Smart Interference. CoRR abs/2008.01559 (2020) - [i43]Vikram Krishnamurthy, George Yin:
Multi-kernel Passive Stochastic Gradient Algorithms. CoRR abs/2008.10020 (2020) - [i42]Bingjia Wang, Alec Koppel, Vikram Krishnamurthy:
A Markov Decision Process Approach to Active Meta Learning. CoRR abs/2009.04950 (2020) - [i41]Vikram Krishnamurthy, George Yin:
Adaptive Non-reversible Stochastic Gradient Langevin Dynamics. CoRR abs/2009.12690 (2020) - [i40]Rui Luo, Buddhika Nettasinghe, Vikram Krishnamurthy:
Echo Chambers and Segregation in Social Networks: Markov Bridge Models and Estimation. CoRR abs/2012.13643 (2020)
2010 – 2019
- 2019
- [j159]Robert Mattila, Inês Lourenço, Cristian R. Rojas, Vikram Krishnamurthy, Bo Wahlberg:
Estimating Private Beliefs of Bayesian Agents Based on Observed Decisions. IEEE Control. Syst. Lett. 3(3): 523-528 (2019) - [j158]S. M. Shahrear Tanzil, Omid Namvar Gharehshiran, Vikram Krishnamurthy:
A Distributed Coalition Game Approach to Femto-Cloud Formation. IEEE Trans. Cloud Comput. 7(1): 129-140 (2019) - [j157]Buddhika Nettasinghe, Vikram Krishnamurthy:
Influence Maximization Over Markovian Graphs: A Stochastic Optimization Approach. IEEE Trans. Signal Inf. Process. over Networks 5(1): 1-14 (2019) - [j156]Sujay Bhatt, Vikram Krishnamurthy:
Adaptive Polling in Hierarchical Social Networks Using Blackwell Dominance. IEEE Trans. Signal Inf. Process. over Networks 5(3): 538-553 (2019) - [j155]Vikram Krishnamurthy, Muralidhar Rangaswamy:
How to Calibrate Your Adversary's Capabilities? Inverse Filtering for Counter-Autonomous Systems. IEEE Trans. Signal Process. 67(24): 6511-6525 (2019) - [c164]Vikram Krishnamurthy, Kusha Nezafati, Juhyun Bae, Mehmet Emre Gursoy, Mian Zhong, Vikrant Singh:
Classification of Driving Behavior Events Utilizing Kinematic Classification and Machine Learning for Down Sampled Time Series Data. IEEE BigData 2019: 3789-3796 - [c163]Vikram Krishnamurthy, Kusha Nezafati, Vikrant Singh:
Application of Machine Learning and Spatial Bootstrapping to Image Processing for Predictive Maintenance. IEEE BigData 2019: 4395-4401 - [c162]Sujay Bhatt, Alec Koppel, Vikram Krishnamurthy:
Policy Gradient using Weak Derivatives for Reinforcement Learning. CDC 2019: 5531-5537 - [c161]Sujay Bhatt, Alec Koppel, Vikram Krishnamurthy:
Policy Gradient using Weak Derivatives for Reinforcement Learning. CISS 2019: 1-3 - [c160]Sujay Bhatt, Buddhika Nettasinghe, Vikram Krishnamurthy:
Efficient Polling Algorithms using Friendship Paradox and Blackwell Dominance. FUSION 2019: 1-8 - [c159]Vikram Krishnamurthy, Muralidhar Rangaswamy:
How to Calibrate your Enemy's Capabilities? Inverse Filtering for Counter-Autonomous Systems. FUSION 2019: 1-6 - [c158]Buddhika Nettasinghe, Vikram Krishnamurthy:
The Friendship Paradox: Implications In Statistical Inference Of Social Networks. MLSP 2019: 1-6 - [i39]Vikram Krishnamurthy:
Convex Stochastic Dominance in Bayesian Estimation and Controlled Sensing POMDPs. CoRR abs/1904.00287 (2019) - [i38]Nazanin Alipourfard, Buddhika Nettasinghe, Andrés Abeliuk, Vikram Krishnamurthy, Kristina Lerman:
Friendship Paradox Biases Perceptions in Directed Networks. CoRR abs/1905.05286 (2019) - [i37]Buddhika Nettasinghe, Vikram Krishnamurthy:
Maximum likelihood estimation of power-law degree distributions using friendship paradox based sampling. CoRR abs/1908.00310 (2019) - [i36]Robert Mattila, Inês Lourenço, Vikram Krishnamurthy, Cristian R. Rojas, Bo Wahlberg:
What Did Your Adversary Believe? Optimal Filtering and Smoothing in Counter-Adversarial Autonomous Systems. CoRR abs/1910.07332 (2019) - [i35]William Hoiles, Vikram Krishnamurthy, Kunal Pattanayak:
Rationally Inattentive Inverse Reinforcement Learning Explains YouTube Commenting Behavior. CoRR abs/1910.11703 (2019) - [i34]Vikram Krishnamurthy, Robin J. Evans, William Moran:
Inverse Cognitive Radar - A Revealed Preferences Approach. CoRR abs/1912.00331 (2019) - 2018
- [j154]Vikram Krishnamurthy, Anup Aprem, Sujay Bhatt:
Multiple stopping time POMDPs: Structural results & application in interactive advertising on social media. Autom. 95: 385-398 (2018) - [c157]Robert Mattila, Cristian R. Rojas, Vikram Krishnamurthy, Bo Wahlberg:
Inverse Filtering for Linear Gaussian State-Space Models. CDC 2018: 5556-5561 - [c156]