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Arunesh Sinha
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- affiliation: Rutgers University, NJ, USA
- affiliation (former): Singapore Management University, Singapore
- affiliation (former): University of Southern California, CA, USA
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2020 – today
- 2025
- [e7]Arunesh Sinha
, Jie Fu
Decision and Game Theory for Security - 15th International Conference, GameSec 2024, New York City, NY, USA, October 16-18, 2024, Proceedings. Lecture Notes in Computer Science 14908, Springer 2025, ISBN 978-3-031-74834-9 [contents] - 2024
- [j9]Hai Truong, Dheryta Jaisinghani, Shubham Jain, Arunesh Sinha, JeongGil Ko, Rajesh Balan:
Tracking people across ultra populated indoor spaces by matching unreliable Wi-Fi signals with disconnected video feeds. Pervasive Mob. Comput. 97: 101860 (2024) - [c67]Yuxiao Lu, Arunesh Sinha, Pradeep Varakantham
Handling Long and Richly Constrained Tasks through Constrained Hierarchical Reinforcement Learning. AAAI 2024: 21368-21377 - [c66]Tien Mai, Avinandan Bose, Arunesh Sinha, Thanh Hong Nguyen, Ayushman Kumar singh:
Tackling Stackelberg Network Interdiction against a Boundedly Rational Adversary. IJCAI 2024: 2913-2921 - [c65]Chen Gong, Zhou Yang, Yunpeng Bai, Junda He, Jieke Shi, Kecen Li, Arunesh Sinha, Bowen Xu, Xinwen Hou, David Lo, Tianhao Wang:
Baffle: Hiding Backdoors in Offline Reinforcement Learning Datasets. SP 2024: 2086-2104 - [e6]Francesco Amigoni, Arunesh Sinha:
Autonomous Agents and Multiagent Systems. Best and Visionary Papers - AAMAS 2023 Workshops, London, UK, May 29 - June 2, 2023, Revised Selected Papers. Lecture Notes in Computer Science 14456, Springer 2024, ISBN 978-3-031-56254-9 [contents] - [i30]Roman Belaire, Arunesh Sinha, Pradeep Varakantham
Probabilistic Perspectives on Error Minimization in Adversarial Reinforcement Learning. CoRR abs/2406.04724 (2024) - [i29]Changyu Chen, Zichen Liu, Chao Du, Tianyu Pang
Bootstrapping Language Models with DPO Implicit Rewards. CoRR abs/2406.09760 (2024) - [i28]Changyu Chen, Shashank Reddy Chirra, Maria José Ferreira, Cleotilde Gonzalez, Arunesh Sinha, Pradeep Varakantham
Towards Neural Network based Cognitive Models of Dynamic Decision-Making by Humans. CoRR abs/2407.17622 (2024) - 2023
- [c64]Tien Mai, Arunesh Sinha:
Securing Lifelines: Safe Delivery of Critical Services in Areas with Volatile Security Situation via a Stackelberg Game Approach. AAAI 2023: 5805-5813 - [c63]Thanh Hong Nguyen, Arunesh Sinha:
Behavioral Learning in Security Games: Threat of Multi-Step Manipulative Attacks. AAAI 2023: 9302-9309 - [c62]Avinandan Bose, Tracey Li, Arunesh Sinha, Tien Mai:
A Fair Incentive Scheme for Community Health Workers. AAAI 2023: 14127-14135 - [c61]Wai Tuck Wong, Sarah Eve Kinsey, Ramesha Karunasena, Thanh Hong Nguyen, Arunesh Sinha:
Beyond NaN: Resiliency of Optimization Layers in the Face of Infeasibility. AAAI 2023: 15242-15250 - [c60]Sonja Johnson-Yu
Characterizing and Improving the Robustness of Predict-Then-Optimize Frameworks. GameSec 2023: 133-152 - [c59]Sarah Eve Kinsey, Jack Wolf, Nalini Saligram, Varun Ramesan, Meeta Walavalkar, Nidhi Jaswal, Sandhya Ramalingam, Arunesh Sinha, Thanh Hong Nguyen:
Building a Personalized Messaging System for Health Intervention in Underprivileged Regions Using Reinforcement Learning. IJCAI 2023: 6022-6030 - [c58]Changyu Chen, Ramesha Karunasena, Thanh Hong Nguyen, Arunesh Sinha, Pradeep Varakantham:
Generative Modelling of Stochastic Actions with Arbitrary Constraints in Reinforcement Learning. NeurIPS 2023 - [i27]Tien Mai, Avinandan Bose, Arunesh Sinha, Thanh Hong Nguyen:
Tackling Stackelberg Network Interdiction against a Boundedly Rational Adversary. CoRR abs/2301.12232 (2023) - [i26]Yuxiao Lu, Pradeep Varakantham
Conditioning Hierarchical Reinforcement Learning on Flexible Constraints. CoRR abs/2302.10639 (2023) - [i25]Changyu Chen, Ramesha Karunasena, Thanh Hong Nguyen, Arunesh Sinha, Pradeep Varakantham
Generative Modelling of Stochastic Actions with Arbitrary Constraints in Reinforcement Learning. CoRR abs/2311.15341 (2023) - 2022
- [c57]Tien Mai, Arunesh Sinha:
Choices Are Not Independent: Stackelberg Security Games with Nested Quantal Response Models. AAAI 2022: 5141-5149 - [c56]Changyu Chen, Avinandan Bose, Shih-Fen Cheng, Arunesh Sinha:
Multiscale Generative Models: Improving Performance of a Generative Model Using Feedback from Other Dependent Generative Models. AAAI 2022: 6193-6201 - [c55]Chen Gong
Curiosity-Driven and Victim-Aware Adversarial Policies. ACSAC 2022: 186-200 - [c54]Arunesh Sinha
AI and Security: A Game Perspective. COMSNETS 2022: 393-396 - [c53]Chaithanya Basrur, Arambam James Singh, Arunesh Sinha, Akshat Kumar, T. K. Satish Kumar:
Trajectory Optimization for Safe Navigation in Maritime Traffic Using Historical Data. CP 2022: 5:1-5:17 - [c52]Sarah Eve Kinsey, Wong Wai Tuck, Arunesh Sinha, Thanh Hong Nguyen:
An Exploration of Poisoning Attacks on Data-Based Decision Making. GameSec 2022: 231-252 - [c51]Avinandan Bose, Arunesh Sinha, Tien Mai:
Scalable Distributional Robustness in a Class of Non-Convex Optimization with Guarantees. NeurIPS 2022 - [i24]Changyu Chen, Avinandan Bose, Shih-Fen Cheng, Arunesh Sinha:
Multiscale Generative Models: Improving Performance of a Generative Model Using Feedback from Other Dependent Generative Models. CoRR abs/2201.09644 (2022) - [i23]Wai Tuck Wong, Andrew Butler, Ramesha Karunasena, Thanh Hong Nguyen, Arunesh Sinha:
Beyond NaN: Resiliency of Optimization Layers in The Face of Infeasibility. CoRR abs/2202.06242 (2022) - [i22]Thanh Hong Nguyen, Arunesh Sinha:
The Art of Manipulation: Threat of Multi-Step Manipulative Attacks in Security Games. CoRR abs/2202.13424 (2022) - [i21]James Holt, Edward Raff, Ahmad Ridley, Dennis Ross, Arunesh Sinha, Diane Staheli, William Streilen, Milind Tambe, Yevgeniy Vorobeychik, Allan B. Wollaber:
Artificial Intelligence for Cyber Security (AICS). CoRR abs/2202.14010 (2022) - [i20]Tien Mai, Arunesh Sinha:
Safe Delivery of Critical Services in Areas with Volatile Security Situation via a Stackelberg Game Approach. CoRR abs/2204.11451 (2022) - [i19]Avinandan Bose, Arunesh Sinha
Scalable Distributional Robustness in a Class of Non Convex Optimization with Guarantees. CoRR abs/2205.15624 (2022) - [i18]Chen Gong, Zhou Yang, Yunpeng Bai, Junda He, Jieke Shi, Arunesh Sinha, Bowen Xu, Xinwen Hou, Guoliang Fan, David Lo:
Mind Your Data! Hiding Backdoors in Offline Reinforcement Learning Datasets. CoRR abs/2210.04688 (2022) - 2021
- [c50]Chaithanya Basrur, Arambam James Singh, Arunesh Sinha, Akshat Kumar:
Ship-GAN: Generative Modeling Based Maritime Traffic Simulator. AAMAS 2021: 1755-1757 - [c49]Ramesha Karunasena, Mohammad Sarparajul Ambiya, Arunesh Sinha
Measuring Data Collection Diligence for Community Healthcare. EAAMO 2021: 10:1-10:12 - [c48]Andrew R. Butler, Thanh Hong Nguyen, Arunesh Sinha
Countering Attacker Data Manipulation in Security Games. GameSec 2021: 59-79 - [c47]Yongzhao Wang, Arunesh Sinha
Building Action Sets in a Deep Reinforcement Learner. ICMLA 2021: 484-489 - [e5]Branislav Bosanský
Decision and Game Theory for Security - 12th International Conference, GameSec 2021, Virtual Event, October 25-27, 2021, Proceedings. Lecture Notes in Computer Science 13061, Springer 2021, ISBN 978-3-030-90369-5 [contents] - 2020
- [j8]Andrew Perrault, Fei Fang
Artificial Intelligence for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline. AI Mag. 41(4): 3-16 (2020) - [j7]Ankit Shah, Arunesh Sinha
Two Can Play That Game: An Adversarial Evaluation of a Cyber-Alert Inspection System. ACM Trans. Intell. Syst. Technol. 11(3): 32:1-32:20 (2020) - [c46]Junyi Li, Xintong Wang, Yaoyang Lin, Arunesh Sinha, Michael P. Wellman:
Generating Realistic Stock Market Order Streams. AAAI 2020: 727-734 - [c45]Sanket Shah
Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning. AAAI 2020: 2226-2235 - [c44]Steven Jecmen, Arunesh Sinha, Zun Li, Long Tran-Thanh:
Bounding Regret in Empirical Games. AAAI 2020: 4280-4287 - [c43]Han-Ching Ou, Arunesh Sinha, Sze-Chuan Suen, Andrew Perrault, Alpan Raval, Milind Tambe:
Who and When to Screen: Multi-Round Active Screening for Network Recurrent Infectious Diseases Under Uncertainty. AAMAS 2020: 992-1000 - [c42]Thanh Hong Nguyen, Arunesh Sinha, He He:
Partial Adversarial Behavior Deception in Security Games. IJCAI 2020: 283-289 - [i17]Andrew Perrault, Fei Fang, Arunesh Sinha, Milind Tambe:
AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline. CoRR abs/2001.00088 (2020) - [i16]Dennis Ross, Arunesh Sinha, Diane Staheli, Bill Streilein:
Proceedings of the Artificial Intelligence for Cyber Security (AICS) Workshop 2020. CoRR abs/2002.08320 (2020) - [i15]Junyi Li, Xintong Wang, Yaoyang Lin, Arunesh Sinha, Michael P. Wellman:
Generating Realistic Stock Market Order Streams. CoRR abs/2006.04212 (2020) - [i14]Ramesha Karunasena, Mohammad Sarparajul Ambiya, Arunesh Sinha, Ruchit Nagar, Saachi Dalal, Divy Thakkar, Milind Tambe:
Measuring Data Collection Quality for Community Healthcare. CoRR abs/2011.02962 (2020)
2010 – 2019
- 2019
- [c41]Thanh Hong Nguyen, Yongzhao Wang, Arunesh Sinha, Michael P. Wellman:
Deception in Finitely Repeated Security Games. AAAI 2019: 2133-2140 - [c40]Arunesh Sinha, Michael P. Wellman:
Incentivizing Collaboration in a Competition. AAMAS 2019: 556-564 - [c39]Parinaz Naghizadeh
Adversarial Contract Design for Private Data Commercialization. EC 2019: 681-699 - [i13]Han-Ching Ou, Arunesh Sinha, Sze-Chuan Suen, Andrew Perrault, Milind Tambe:
Who and When to Screen: Multi-Round Active Screening for Recurrent Infectious Diseases Under Uncertainty. CoRR abs/1903.06113 (2019) - [i12]Sanket Shah
Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning. CoRR abs/1911.08799 (2019) - 2018
- [j6]Bruno Bouchard
Reports of the Workshops of the 32nd AAAI Conference on Artificial Intelligence. AI Mag. 39(4): 45-56 (2018) - [c38]Thanh Hong Nguyen, Michael P. Wellman, Arunesh Sinha:
Deceitful Attacks in Security Games. AAAI Workshops 2018: 260-267 - [c37]Nicolas Papernot, Patrick D. McDaniel, Arunesh Sinha
SoK: Security and Privacy in Machine Learning. EuroS&P 2018: 399-414 - [c36]Arunesh Sinha
Scaling-Up Stackelberg Security Games Applications Using Approximations. GameSec 2018: 432-452 - [c35]Linh Nguyen, Sky Wang, Arunesh Sinha
A Learning and Masking Approach to Secure Learning. GameSec 2018: 453-464 - [c34]Sara Marie McCarthy, Corine M. Laan, Kai Wang, Phebe Vayanos
The Price of Usability: Designing Operationalizable Strategies for Security Games. IJCAI 2018: 454-460 - [c33]Arunesh Sinha
Stackelberg Security Games: Looking Beyond a Decade of Success. IJCAI 2018: 5494-5501 - [i11]Ankit Shah, Arunesh Sinha, Rajesh Ganesan, Sushil Jajodia, Hasan Cam:
Two Can Play That Game: An Adversarial Evaluation of a Cyber-alert Inspection System. CoRR abs/1810.05921 (2018) - [i10]Parinaz Naghizadeh, Arunesh Sinha:
Adversarial Contract Design for Private Data Commercialization. CoRR abs/1810.07608 (2018) - 2017
- [j5]Monica Anderson
Reports of the Workshops of the Thirty-First AAAI Conference on Artificial Intelligence. AI Mag. 38(3): 72-82 (2017) - [j4]Fei Fang
Predicting poaching for wildlife Protection. IBM J. Res. Dev. 61(6): 3:1-3:12 (2017) - [c32]Battista Biggio
10th International Workshop on Artificial Intelligence and Security (AISec 2017). CCS 2017: 2621-2622 - [c31]Aaron Schlenker, Haifeng Xu, Mina Guirguis, Christopher Kiekintveld, Arunesh Sinha
Don't Bury your Head in Warnings: A Game-Theoretic Approach for Intelligent Allocation of Cyber-security Alerts. IJCAI 2017: 381-387 - [e4]Bhavani Thuraisingham, Battista Biggio, David Mandell Freeman, Brad Miller, Arunesh Sinha:
Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security, AISec@CCS 2017, Dallas, TX, USA, November 3, 2017. ACM 2017, ISBN 978-1-4503-5202-4 [contents] - [i9]Linh Nguyen, Arunesh Sinha:
A Learning Approach to Secure Learning. CoRR abs/1709.04447 (2017) - [i8]Arunesh Sinha, Aaron Schlenker, Donnabell Dmello, Milind Tambe:
Practical Scalability for Stackelberg Security Games. CoRR abs/1711.04208 (2017) - 2016
- [j3]Stefano V. Albrecht, Bruno Bouchard, John S. Brownstein, David L. Buckeridge, Cornelia Caragea
Reports of the 2016 AAAI Workshop Program. AI Mag. 37(3): 99-108 (2016) - [j2]Chao Zhang, Shahrzad Gholami, Debarun Kar, Arunesh Sinha
Keeping Pace with Criminals: An Extended Study of Designing Patrol Allocation against Adaptive Opportunistic Criminals. Games 7(3): 15 (2016) - [c30]Matthew Brown, Arunesh Sinha, Aaron Schlenker, Milind Tambe:
One Size Does Not Fit All: A Game-Theoretic Approach for Dynamically and Effectively Screening for Threats. AAAI 2016: 425-431 - [c29]Thanh Hong Nguyen, Arunesh Sinha, Shahrzad Gholami, Andrew J. Plumptre, Lucas Joppa, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Rob Critchlow, Colin M. Beale:
Protecting Wildlife under Imperfect Observation. AAAI Workshop: Computer Poker and Imperfect Information Games 2016 - [c28]Thanh Hong Nguyen, Arunesh Sinha, Milind Tambe:
Conquering Adversary Behavioral Uncertainty in Security Games: An Efficient Modeling Robust Based Algorithm. AAAI 2016: 4242-4243 - [c27]Chao Zhang, Victor Bucarey, Ayan Mukhopadhyay, Arunesh Sinha, Yundi Qian, Yevgeniy Vorobeychik, Milind Tambe:
Using Abstractions to Solve Opportunistic Crime Security Games at Scale. AAMAS 2016: 196-204 - [c26]Arunesh Sinha, Debarun Kar, Milind Tambe:
Learning Adversary Behavior in Security Games: A PAC Model Perspective. AAMAS 2016: 214-222 - [c25]Thanh Hong Nguyen, Arunesh Sinha, Shahrzad Gholami, Andrew J. Plumptre, Lucas Joppa, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Rob Critchlow, Colin M. Beale:
CAPTURE: A New Predictive Anti-Poaching Tool for Wildlife Protection. AAMAS 2016: 767-775 - [c24]Shahrzad Gholami, Bryan Wilder, Matthew Brown, Arunesh Sinha, Nicole D. Sintov, Milind Tambe:
SPECTRE: A Game Theoretic Framework for Preventing Collusion in Security Games (Demonstration). AAMAS 2016: 1498-1500 - [c23]David Mandell Freeman, Katerina Mitrokotsa
9th International Workshop on Artificial Intelligence and Security: AISec 2016. CCS 2016: 1881 - [c22]Aaron Schlenker, Matthew Brown, Arunesh Sinha
Get Me to My GATE on Time: Efficiently Solving General-Sum Bayesian Threat Screening Games. ECAI 2016: 1476-1484 - [c21]Sara Marie McCarthy, Arunesh Sinha
Data Exfiltration Detection and Prevention: Virtually Distributed POMDPs for Practically Safer Networks. GameSec 2016: 39-61 - [c20]Nika Haghtalab, Fei Fang, Thanh Hong Nguyen, Arunesh Sinha, Ariel D. Procaccia, Milind Tambe:
Three Strategies to Success: Learning Adversary Models in Security Games. IJCAI 2016: 308-314 - [c19]Thanh Hong Nguyen, Arunesh Sinha
Addressing Behavioral Uncertainty in Security Games: An Efficient Robust Strategic Solution for Defender Patrols. IPDPS Workshops 2016: 1831-1838 - [c18]Benjamin J. Ford, Matthew Brown, Amulya Yadav, Amandeep Singh, Arunesh Sinha
Protecting the NECTAR of the Ganga River Through Game-Theoretic Factory Inspections. PAAMS 2016: 97-108 - [e3]David R. Martinez, William W. Streilein, Kevin M. Carter, Arunesh Sinha:
Artificial Intelligence for Cyber Security, Papers from the 2016 AAAI Workshop, Phoenix, Arizona, USA, February 12, 2016. AAAI Technical Report WS-16-03, AAAI Press 2016 [contents] - [e2]David Mandell Freeman, Aikaterini Mitrokotsa
Proceedings of the 2016 ACM Workshop on Artificial Intelligence and Security, AISec@CCS 2016, Vienna, Austria, October 28, 2016. ACM 2016, ISBN 978-1-4503-4573-6 [contents] - [i7]Nicolas Papernot, Patrick D. McDaniel, Arunesh Sinha, Michael P. Wellman:
Towards the Science of Security and Privacy in Machine Learning. CoRR abs/1611.03814 (2016) - 2015
- [j1]Arunesh Sinha
From physical security to cybersecurity. J. Cybersecur. 1(1): 19-35 (2015) - [c17]Jeremiah Blocki, Nicolas Christin, Anupam Datta, Ariel D. Procaccia, Arunesh Sinha:
Audit Games with Multiple Defender Resources. AAAI 2015: 791-797 - [c16]Chao Zhang, Arunesh Sinha, Milind Tambe:
Keeping Pace with Criminals: Designing Patrol Allocation Against Adaptive Opportunistic Criminals. AAMAS 2015: 1351-1359 - [c15]Chao Zhang, Manish Jain, Ripple Goyal, Arunesh Sinha, Milind Tambe:
Learning, Predicting and Planning against Crime: Demonstration Based on Real Urban Crime Data (Demonstration). AAMAS 2015: 1911-1912 - [c14]Christos Dimitrakakis, Aikaterini Mitrokotsa, Arunesh Sinha:
Workshop Summary of AISec'15: 2015 Workshop on Artificial Intelligent and Security. CCS 2015: 1702 - [c13]Anupam Datta, Deepak Garg, Dilsun Kirli Kaynar, Divya Sharma, Arunesh Sinha
Program Actions as Actual Causes: A Building Block for Accountability. CSF 2015: 261-275 - [c12]Alejandro Uriel Carbonara, Anupam Datta, Arunesh Sinha, Yair Zick:
Incentivizing Peer Grading in MOOCS: An Audit Game Approach. IJCAI 2015: 497-503 - [c11]Haifeng Xu, Albert Xin Jiang, Arunesh Sinha, Zinovi Rabinovich, Shaddin Dughmi, Milind Tambe:
Security Games with Information Leakage: Modeling and Computation. IJCAI 2015: 674-680 - [e1]Indrajit Ray, Xiaofeng Wang, Kui Ren, Christos Dimitrakakis, Aikaterini Mitrokotsa, Arunesh Sinha:
Proceedings of the 8th ACM Workshop on Artificial Intelligence and Security, AISec 2015, Denver, Colorado, USA, October 16, 2015. ACM 2015, ISBN 978-1-4503-3826-4 [contents] - [i6]Haifeng Xu, Albert Xin Jiang, Arunesh Sinha, Zinovi Rabinovich, Shaddin Dughmi, Milind Tambe:
Security Games With Information Leakage: Modeling and Computation. CoRR abs/1504.06058 (2015) - [i5]Anupam Datta, Deepak Garg, Dilsun Kirli Kaynar, Divya Sharma, Arunesh Sinha:
Program Actions as Actual Causes: A Building Block for Accountability. CoRR abs/1505.01131 (2015) - [i4]Arunesh Sinha, Debarun Kar, Milind Tambe:
Learning Adversary Behavior in Security Games: A PAC Model Perspective. CoRR abs/1511.00043 (2015) - 2014
- [b1]Arunesh Sinha:
Audit Games. Carnegie Mellon University, USA, 2014 - [c10]Arunesh Sinha
Continuous Tamper-Proof Logging Using TPM 2.0. TRUST 2014: 19-36 - [i3]Jeremiah Blocki, Nicolas Christin
Audit Games with Multiple Defender Resources. CoRR abs/1409.4503 (2014) - 2013
- [c9]Arunesh Sinha
What you want is not what you get: predicting sharing policies for text-based content on facebook. AISec 2013: 13-24 - [c8]Jeremiah Blocki
Adaptive Regret Minimization in Bounded-Memory Games. GameSec 2013: 65-84 - [c7]Jeremiah Blocki, Nicolas Christin, Anupam Datta, Ariel D. Procaccia, Arunesh Sinha:
Audit Games. IJCAI 2013: 41-47 - [i2]Jeremiah Blocki, Nicolas Christin, Anupam Datta, Ariel D. Procaccia, Arunesh Sinha:
Audit Games. CoRR abs/1303.0356 (2013) - 2012
- [c6]Jeremiah Blocki
Audit Mechanisms for Provable Risk Management and Accountable Data Governance. GameSec 2012: 38-59 - [c5]Anupam Datta, Divya Sharma, Arunesh Sinha
Provable De-anonymization of Large Datasets with Sparse Dimensions. POST 2012: 229-248 - 2011
- [c4]Jeremiah Blocki
Regret Minimizing Audits: A Learning-Theoretic Basis for Privacy Protection. CSF 2011: 312-327 - [c3]Anupam Datta, Jeremiah Blocki
Understanding and Protecting Privacy: Formal Semantics and Principled Audit Mechanisms. ICISS 2011: 1-27 - [c2]Jeremiah Blocki, Nicolas Christin, Anupam Datta, Arunesh Sinha:
Audit Mechanisms for Privacy Protection in Healthcare Environments. HealthSec 2011 - [i1]Jeremiah Blocki, Nicolas Christin
Adaptive Regret Minimization in Bounded-Memory Games. CoRR abs/1111.2888 (2011)
2000 – 2009
- 2009
- [c1]Pushparani Bhallamudi, Scott R. Tilley, Arunesh Sinha
Migrating a Web-based application to a service-based system - an experience report. WSE 2009: 71-74
Coauthor Index
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