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ORCIDLalitha Sankar
Lalitha Sankaranarayanan
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- affiliation: Arizona State University, Tempe, Arizona, USA
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2020 – today
- 2024
[j36]Rajasekhar Anguluri
, Oliver Kosut, Lalitha Sankar:
Identifying Edge Changes in Networks From Input and Output Covariance Data. IEEE Control. Syst. Lett. 8: 364-369 (2024)- [j35]Monica Welfert, Gowtham R. Kurri, Kyle Otstot, Lalitha Sankar:
Addressing GAN Training Instabilities via Tunable Classification Losses. IEEE J. Sel. Areas Inf. Theory 5: 534-553 (2024) - [j34]Gowtham R. Kurri, Lalitha Sankar, Oliver Kosut:
An Operational Approach to Information Leakage via Generalized Gain Functions. IEEE Trans. Inf. Theory 70(2): 1349-1375 (2024) - [j33]Atefeh Gilani, Gowtham R. Kurri, Oliver Kosut, Lalitha Sankar:
Unifying Privacy Measures via Maximal (α, β)-Leakage (MαbeL). IEEE Trans. Inf. Theory 70(6): 4368-4395 (2024) - [c67]Daniil Vankov, Angelia Nedich, Lalitha Sankar:
Generalized Smooth Variational Inequalities: Methods with Adaptive Stepsizes. ICML 2024 - [i87]Nathan Stromberg, Rohan Ayyagari, Monica Welfert, Sanmi Koyejo, Lalitha Sankar:
Robustness to Subpopulation Shift with Domain Label Noise via Regularized Annotation of Domains. CoRR abs/2402.11039 (2024) - [i86]Obai Bahwal, Oliver Kosut, Lalitha Sankar:
An Adversarial Approach to Evaluating the Robustness of Event Identification Models. CoRR abs/2402.12338 (2024) - [i85]Joel Mathias, Rajasekhar Anguluri, Oliver Kosut, Lalitha Sankar:
Model Predictive Control for Joint Ramping and Regulation-Type Service from Distributed Energy Resource Aggregations. CoRR abs/2405.02813 (2024) - [i84]Monica Welfert, Nathan Stromberg, Lalitha Sankar:
Theoretical Guarantees of Data Augmented Last Layer Retraining Methods. CoRR abs/2405.05934 (2024) - [i83]Nathan Stromberg, Rohan Ayyagari, Sanmi Koyejo, Richard Nock, Lalitha Sankar:
Label Noise Robustness for Domain-Agnostic Fair Corrections via Nearest Neighbors Label Spreading. CoRR abs/2406.09561 (2024) - 2023
- [j32]Rajasekhar Anguluri, Oliver Kosut, Lalitha Sankar:
Localization and Estimation of Unknown Forced Inputs: A Group LASSO Approach. IEEE Trans. Control. Netw. Syst. 10(4): 1997-2009 (2023) - [j31]Anjana Arunkumar, Andrea Pinceti, Lalitha Sankar, Chris Bryan:
PMU Tracker: A Visualization Platform for Epicentric Event Propagation Analysis in the Power Grid. IEEE Trans. Vis. Comput. Graph. 29(1): 1081-1090 (2023) - [c66]Tyler Sypherd, Nathaniel Stromberg, Richard Nock, Visar Berisha, Lalitha Sankar:
Smoothly Giving up: Robustness for Simple Models. AISTATS 2023: 5376-5410 - [c65]Rajasekhar Anguluri, Nima Taghipourbazargani, Oliver Kosut, Lalitha Sankar:
Source Localization in Linear Dynamical Systems using Subspace Model Identification. CCTA 2023: 1016-1021 - [c64]Wael Alghamdi, Juan Felipe Gómez, Shahab Asoodeh, Flávio P. Calmon, Oliver Kosut, Lalitha Sankar:
The Saddle-Point Method in Differential Privacy. ICML 2023: 508-528 - [c63]Monica Welfert, Kyle Otstot, Gowtham R. Kurri, Lalitha Sankar:
(αD, αG)-GANs: Addressing GAN Training Instabilities via Dual Objectives. ISIT 2023: 915-920 - [c62]Wael Alghamdi, Shahab Asoodeh, Flávio P. Calmon, Juan Felipe Gómez, Oliver Kosut, Lalitha Sankar:
Optimal Multidimensional Differentially Private Mechanisms in the Large-Composition Regime. ISIT 2023: 2195-2200 - [c61]Wael Alghamdi, Shahab Asoodeh, Flávio P. Calmon, Juan Felipe Gómez, Oliver Kosut, Lalitha Sankar:
Schrödinger Mechanisms: Optimal Differential Privacy Mechanisms for Small Sensitivity. ISIT 2023: 2201-2206 - [c60]Joshua Inman, Tanmay Khandait, Giulia Pedrielli, Lalitha Sankar:
Parameter Optimization with Conscious Allocation (POCA). WSC 2023: 3436-3447 - [i82]Tyler Sypherd, Nathan Stromberg, Richard Nock, Visar Berisha, Lalitha Sankar:
Smoothly Giving up: Robustness for Simple Models. CoRR abs/2302.09114 (2023) - [i81]Monica Welfert, Kyle Otstot, Gowtham R. Kurri, Lalitha Sankar:
Towards Addressing GAN Training Instabilities: Dual-objective GANs with Tunable Parameters. CoRR abs/2302.14320 (2023) - [i80]Atefeh Gilani, Gowtham R. Kurri, Oliver Kosut, Lalitha Sankar:
(α, β)-Leakage: A Unified Privacy Leakage Measure. CoRR abs/2304.07456 (2023) - [i79]Nima Taghipourbazargani, Lalitha Sankar, Oliver Kosut:
A Semi-Supervised Approach for Power System Event Identification. CoRR abs/2309.10095 (2023) - [i78]Monica Welfert, Gowtham R. Kurri, Kyle Otstot, Lalitha Sankar:
Addressing GAN Training Instabilities via Tunable Classification Losses. CoRR abs/2310.18291 (2023) - [i77]Joshua Inman, Tanmay Khandait, Giulia Pedrielli, Lalitha Sankar:
Parameter Optimization with Conscious Allocation (POCA). CoRR abs/2312.17404 (2023) - 2022
- [j30]Anjana Arunkumar, Nitin Gupta, Andrea Pinceti, Lalitha Sankar, Chris Bryan:
PMUVis : A Large-Scale Platform to Assist Power System Operators in a Smart Grid. IEEE Computer Graphics and Applications 42(6): 84-95 (2022) - [j29]Anguluri Rajasekhar, Gautam Dasarathy, Oliver Kosut, Lalitha Sankar:
Grid Topology Identification With Hidden Nodes via Structured Norm Minimization. IEEE Control. Syst. Lett. 6: 1244-1249 (2022) - [j28]Peter Kairouz, Jiachun Liao, Chong Huang, Maunil Vyas, Monica Welfert, Lalitha Sankar:
Generating Fair Universal Representations Using Adversarial Models. IEEE Trans. Inf. Forensics Secur. 17: 1970-1985 (2022) - [j27]Tyler Sypherd, Mario Díaz, John Kevin Cava, Gautam Dasarathy, Peter Kairouz, Lalitha Sankar:
A Tunable Loss Function for Robust Classification: Calibration, Landscape, and Generalization. IEEE Trans. Inf. Theory 68(9): 6021-6051 (2022) - [c59]Tyler Sypherd, Richard Nock, Lalitha Sankar:
Being Properly Improper. ICML 2022: 20891-20932 - [c58]Gowtham R. Kurri, Monica Welfert, Tyler Sypherd, Lalitha Sankar:
α-GAN: Convergence and Estimation Guarantees. ISIT 2022: 276-281 - [c57]Wael Alghamdi, Shahab Asoodeh, Flávio P. Calmon, Oliver Kosut, Lalitha Sankar, Fei Wei:
Cactus Mechanisms: Optimal Differential Privacy Mechanisms in the Large-Composition Regime. ISIT 2022: 1838-1843 - [c56]Gowtham R. Kurri, Oliver Kosut, Lalitha Sankar:
A Variational Formula for Infinity-Rényi Divergence with Applications to Information Leakage. ISIT 2022: 2493-2498 - [c55]Atefeh Gilani, Gowtham R. Kurri, Oliver Kosut, Lalitha Sankar:
An Alphabet of Leakage Measures. ITW 2022: 458-463 - [i76]Gowtham R. Kurri, Oliver Kosut, Lalitha Sankar:
A Variational Formula for Infinity-Rényi Divergence with Applications to Information Leakage. CoRR abs/2202.06040 (2022) - [i75]Nima T. Bazargani, Gautam Dasarathy, Lalitha Sankar, Oliver Kosut:
A Machine Learning Framework for Event Identification via Modal Analysis of PMU Data. CoRR abs/2202.06836 (2022) - [i74]Gowtham R. Kurri, Monica Welfert, Tyler Sypherd, Lalitha Sankar:
α-GAN: Convergence and Estimation Guarantees. CoRR abs/2205.06393 (2022) - [i73]Kyle Otstot, John Kevin Cava, Tyler Sypherd, Lalitha Sankar:
AugLoss: A Learning Methodology for Real-World Dataset Corruption. CoRR abs/2206.02286 (2022) - [i72]Wael Alghamdi, Shahab Asoodeh, Flávio P. Calmon, Oliver Kosut, Lalitha Sankar, Fei Wei:
Cactus Mechanisms: Optimal Differential Privacy Mechanisms in the Large-Composition Regime. CoRR abs/2207.00420 (2022) - [i71]Anguluri Rajasekhar, Lalitha Sankar, Oliver Kosut:
Parameter Estimation in Ill-conditioned Low-inertia Power Systems. CoRR abs/2208.04471 (2022) - [i70]Wael Alghamdi, Shahab Asoodeh, Flávio P. Calmon, Juan Felipe Gómez, Oliver Kosut, Lalitha Sankar, Fei Wei:
The Saddle-Point Accountant for Differential Privacy. CoRR abs/2208.09595 (2022) - [i69]Anjana Arunkumar, Andrea Pinceti, Lalitha Sankar, Chris Bryan:
PMU Tracker: A Visualization Platform for Epicentric Event Propagation Analysis in the Power Grid. CoRR abs/2209.03514 (2022) - [i68]Gowtham R. Kurri, Lalitha Sankar, Oliver Kosut:
An Operational Approach to Information Leakage via Generalized Gain Functions. CoRR abs/2209.13862 (2022) - [i67]Abrar Zahin, Rajasekhar Anguluri, Oliver Kosut, Lalitha Sankar, Gautam Dasarathy:
Robust Model Selection of Non Tree-Structured Gaussian Graphical Models. CoRR abs/2211.05690 (2022) - [i66]Atefeh Gilani, Gowtham R. Kurri, Oliver Kosut, Lalitha Sankar:
An Alphabet of Leakage Measures. CoRR abs/2211.15453 (2022) - 2021
- [j26]H. Vincent Poor, Matthieu R. Bloch, Onur Günlü, Frédérique E. Oggier, Lalitha Sankar, Rafael F. Schaefer, Aylin Yener:
Editorial. IEEE J. Sel. Areas Inf. Theory 2(1): 3-4 (2021) - [j25]Matthieu R. Bloch, Onur Günlü, Aylin Yener, Frédérique E. Oggier, H. Vincent Poor, Lalitha Sankar, Rafael F. Schaefer:
An Overview of Information-Theoretic Security and Privacy: Metrics, Limits and Applications. IEEE J. Sel. Areas Inf. Theory 2(1): 5-22 (2021) - [j24]Shahab Asoodeh, Jiachun Liao, Flávio P. Calmon, Oliver Kosut, Lalitha Sankar:
Three Variants of Differential Privacy: Lossless Conversion and Applications. IEEE J. Sel. Areas Inf. Theory 2(1): 208-222 (2021) - [c54]Mario Díaz, Peter Kairouz, Jiachun Liao, Lalitha Sankar:
Neural Network-based Estimation of the MMSE. ISIT 2021: 1023-1028 - [c53]Gowtham R. Kurri, Oliver Kosut, Lalitha Sankar:
Evaluating Multiple Guesses by an Adversary via a Tunable Loss Function. ISIT 2021: 2002-2007 - [c52]Gowtham R. Kurri, Tyler Sypherd, Lalitha Sankar:
Realizing GANs via a Tunable Loss Function. ITW 2021: 1-6 - [i65]Zhigang Chu, Andrea Pinceti, Ramin Kaviani, Roozbeh Khodadadeh, Xingpeng Li, Jiazi Zhang, Karthik Saikumar, Mostafa Sahraei-Ardakani, Christopher Mosier, Robin Podmore, Kory W. Hedman, Oliver Kosut, Lalitha Sankar:
A Verifiable Framework for Cyber-Physical Attacks and Countermeasures in a Resilient Electric Power Grid. CoRR abs/2104.13908 (2021) - [i64]Gowtham R. Kurri, Tyler Sypherd, Lalitha Sankar:
Realizing GANs via a Tunable Loss Function. CoRR abs/2106.05232 (2021) - [i63]Richard Nock, Tyler Sypherd, Lalitha Sankar:
Being Properly Improper. CoRR abs/2106.09920 (2021) - [i62]Andrea Pinceti, Lalitha Sankar, Oliver Kosut:
Synthetic Time-Series Load Data via Conditional Generative Adversarial Networks. CoRR abs/2107.03545 (2021) - [i61]Andrea Pinceti, Lalitha Sankar, Oliver Kosut:
Generation of Synthetic Multi-Resolution Time Series Load Data. CoRR abs/2107.03547 (2021) - [i60]Gowtham R. Kurri, Oliver Kosut, Lalitha Sankar:
Evaluating Multiple Guesses by an Adversary via a Tunable Loss Function. CoRR abs/2108.08774 (2021) - [i59]Mario Díaz, Peter Kairouz, Lalitha Sankar:
Lower Bounds for the Minimum Mean-Square Error via Neural Network-based Estimation. CoRR abs/2108.12851 (2021) - 2020
- [j23]Mario Díaz, Hao Wang, Flávio P. Calmon, Lalitha Sankar:
On the Robustness of Information-Theoretic Privacy Measures and Mechanisms. IEEE Trans. Inf. Theory 66(4): 1949-1978 (2020) - [c51]Jiachun Liao, Lalitha Sankar, Oliver Kosut, Flávio P. Calmon:
Maximal α-Leakage and its Properties. CNS 2020: 1-6 - [c50]Shahab Asoodeh, Jiachun Liao, Flávio P. Calmon, Oliver Kosut, Lalitha Sankar:
A Better Bound Gives a Hundred Rounds: Enhanced Privacy Guarantees via f-Divergences. ISIT 2020: 920-925 - [c49]Tyler Sypherd, Mario Díaz, Lalitha Sankar, Gautam Dasarathy:
On the α-loss Landscape in the Logistic Model. ISIT 2020: 2700-2705 - [c48]Zhigang Chu, Jiazi Zhang, Oliver Kosut, Lalitha Sankar:
Vulnerability Assessment of Large-scale Power Systems to False Data Injection Attacks. SmartGridComm 2020: 1-6 - [i58]Shahab Asoodeh, Jiachun Liao, Flávio P. Calmon, Oliver Kosut, Lalitha Sankar:
A Better Bound Gives a Hundred Rounds: Enhanced Privacy Guarantees via $f$-Divergences. CoRR abs/2001.05990 (2020) - [i57]Zhigang Chu, Oliver Kosut, Lalitha Sankar:
Detecting Load Redistribution Attacks via Support Vector Models. CoRR abs/2003.06543 (2020) - [i56]Zhigang Chu, Jiazi Zhang, Oliver Kosut, Lalitha Sankar:
N-1 Reliability Makes It Difficult for False Data Injection Attacks to Cause Physical Consequences. CoRR abs/2003.07699 (2020) - [i55]Tyler Sypherd, Mario Díaz, Lalitha Sankar, Gautam Dasarathy:
On the alpha-loss Landscape in the Logistic Model. CoRR abs/2006.12406 (2020) - [i54]Shahab Asoodeh, Jiachun Liao, Flávio P. Calmon, Oliver Kosut, Lalitha Sankar:
Three Variants of Differential Privacy: Lossless Conversion and Applications. CoRR abs/2008.06529 (2020)
2010 – 2019
- 2019
- [j22]Jiachun Liao, Oliver Kosut, Lalitha Sankar, Flávio du Pin Calmon:
Tunable Measures for Information Leakage and Applications to Privacy-Utility Tradeoffs. IEEE Trans. Inf. Theory 65(12): 8043-8066 (2019) - [c47]Jiachun Liao, Lalitha Sankar, Oliver Kosut, Flávio P. Calmon:
Robustness of Maximal α-Leakage to Side Information. ISIT 2019: 642-646 - [c46]Tyler Sypherd, Mario Díaz, Lalitha Sankar, Peter Kairouz:
A Tunable Loss Function for Binary Classification. ISIT 2019: 2479-2483 - [c45]Zhigang Chu, Andrea Pinceti, Reetam Sen Biswas, Oliver Kosut, Anamitra Pal, Lalitha Sankar:
Can Predictive Filters Detect Gradually Ramping False Data Injection Attacks Against PMUs? SmartGridComm 2019: 1-6 - [i53]Jiachun Liao, Lalitha Sankar, Oliver Kosut, Flávio P. Calmon:
Robustness of Maximal α-Leakage to Side Information. CoRR abs/1901.07105 (2019) - [i52]Tyler Sypherd, Mario Díaz, Lalitha Sankar, Peter Kairouz:
A Tunable Loss Function for Binary Classification. CoRR abs/1902.04639 (2019) - [i51]Zhigang Chu, Jiazi Zhang, Oliver Kosut, Lalitha Sankar:
Vulnerability Assessment of N-1 Reliable Power Systems to False Data Injection Attacks. CoRR abs/1903.07781 (2019) - [i50]Zhigang Chu, Andrea Pinceti, Reetam Sen Biswas, Oliver Kosut, Anamitra Pal, Lalitha Sankar:
Can Predictive Filters Detect Gradually Ramping False Data Injection Attacks Against PMUs? CoRR abs/1905.02271 (2019) - [i49]Tyler Sypherd, Mario Díaz, Harshit Laddha, Lalitha Sankar, Peter Kairouz, Gautam Dasarathy:
A Tunable Loss Function for Classification. CoRR abs/1906.02314 (2019) - [i48]Jiachun Liao, Chong Huang, Peter Kairouz, Lalitha Sankar:
Learning Generative Adversarial RePresentations (GAP) under Fairness and Censoring Constraints. CoRR abs/1910.00411 (2019) - [i47]Mario Díaz, Peter Kairouz, Jiachun Liao, Lalitha Sankar:
Theoretical Guarantees for Model Auditing with Finite Adversaries. CoRR abs/1911.03405 (2019) - [i46]Andrea Pinceti, Lalitha Sankar, Oliver Kosut:
Detection and Localization of Load Redistribution Attacks on Large Scale Systems. CoRR abs/1912.09453 (2019) - 2018
- [j21]Jiachun Liao, Lalitha Sankar, Vincent Y. F. Tan, Flávio du Pin Calmon:
Hypothesis Testing Under Mutual Information Privacy Constraints in the High Privacy Regime. IEEE Trans. Inf. Forensics Secur. 13(4): 1058-1071 (2018) - [j20]Kousha Kalantari, Lalitha Sankar, Anand D. Sarwate:
Robust Privacy-Utility Tradeoffs Under Differential Privacy and Hamming Distortion. IEEE Trans. Inf. Forensics Secur. 13(11): 2816-2830 (2018) - [c44]Chong Huang, Peter Kairouz, Lalitha Sankar:
Generative Adversarial Privacy: A Data-Driven Approach to Information-Theoretic Privacy. ACSSC 2018: 2162-2166 - [c43]Chong Huang, Lalitha Sankar:
Impact of Privacy on Free Online Service Markets. GameSec 2018: 1-21 - [c42]Jiachun Liao, Oliver Kosut, Lalitha Sankar, Flávio P. Calmon:
A Tunable Measure for Information Leakage. ISIT 2018: 701-705 - [c41]Hao Wang, Mario Díaz, Flávio P. Calmon, Lalitha Sankar:
The Utility Cost of Robust Privacy Guarantees. ISIT 2018: 706-710 - [c40]Jiachun Liao, Oliver Kosut, Lalitha Sankar, Flávio P. Calmon:
Privacy Under Hard Distortion Constraints. ITW 2018: 1-5 - [c39]Zhigang Chu, Jiazi Zhang, Oliver Kosut, Lalitha Sankar:
Unobservable False Data Injection Attacks against PMUs: Feasible Conditions and Multiplicative Attacks. SmartGridComm 2018: 1-6 - [i45]Hao Wang, Mario Díaz, Flávio P. Calmon, Lalitha Sankar:
The Utility Cost of Robust Privacy Guarantees. CoRR abs/1801.05926 (2018) - [i44]Mario Díaz, Lalitha Sankar, Peter Kairouz:
On the Contractivity of Privacy Mechanisms. CoRR abs/1801.06255 (2018) - [i43]Jiachun Liao, Oliver Kosut, Lalitha Sankar, Flávio P. Calmon:
Privacy Under Hard Distortion Constraints. CoRR abs/1806.00063 (2018) - [i42]Jiachun Liao, Oliver Kosut, Lalitha Sankar, Flávio P. Calmon:
A Tunable Measure for Information Leakage. CoRR abs/1806.03332 (2018) - [i41]Zhigang Chu, Jiazi Zhang, Oliver Kosut, Lalitha Sankar:
Unobservable False Data Injection Attacks against PMUs: Feasible Conditions and Multiplicative Attacks. CoRR abs/1806.05057 (2018) - [i40]Chong Huang, Peter Kairouz, Xiao Chen, Lalitha Sankar, Ram Rajagopal:
Generative Adversarial Privacy. CoRR abs/1807.05306 (2018) - [i39]Jiachun Liao, Oliver Kosut, Lalitha Sankar, Flávio du Pin Calmon:
Tunable Measures for Information Leakage and Applications to Privacy-Utility Tradeoffs. CoRR abs/1809.09231 (2018) - [i38]Mario Díaz, Hao Wang, Flávio P. Calmon, Lalitha Sankar:
On the Robustness of Information-Theoretic Privacy Measures and Mechanisms. CoRR abs/1811.06057 (2018) - 2017
- [j19]Chong Huang, Peter Kairouz, Xiao Chen, Lalitha Sankar, Ram Rajagopal:
Context-Aware Generative Adversarial Privacy. Entropy 19(12): 656 (2017) - [j18]Bahman Moraffah, Lalitha Sankar:
Privacy-Guaranteed Two-Agent Interactions Using Information-Theoretic Mechanisms. IEEE Trans. Inf. Forensics Secur. 12(9): 2168-2183 (2017) - [j17]Oliver Kosut, Lalitha Sankar:
Asymptotics and Non-Asymptotics for Universal Fixed-to-Variable Source Coding. IEEE Trans. Inf. Theory 63(6): 3757-3772 (2017) - [c38]Jiachun Liao, Lalitha Sankar, Flávio P. Calmon, Vincent Y. F. Tan:
Hypothesis testing under maximal leakage privacy constraints. ISIT 2017: 779-783 - [c37]Kousha Kalantari, Lalitha Sankar, Oliver Kosut:
On information-theoretic privacy with general distortion cost functions. ISIT 2017: 2865-2869 - [c36]Jiazi Zhang, Zhigang Chu, Lalitha Sankar, Oliver Kosut:
False data injection attacks on phasor measurements that bypass low-rank decomposition. SmartGridComm 2017: 96-101 - [i37]Jiachun Liao, Lalitha Sankar, Flávio du Pin Calmon, Vincent Yan Fu Tan:
Hypothesis Testing under Maximal Leakage Privacy Constraints. CoRR abs/1701.07099 (2017) - [i36]Jiazi Zhang, Zhigang Chu, Lalitha Sankar, Oliver Kosut:
Can Attackers with Limited Information Exploit Historical Data to Mount Successful False Data Injection Attacks on Power Systems? CoRR abs/1703.07500 (2017) - [i35]Jiachun Liao, Lalitha Sankar, Vincent Y. F. Tan, Flávio du Pin Calmon:
Hypothesis Testing under Mutual Information Privacy Constraints in the High Privacy Regime. CoRR abs/1704.08347 (2017) - [i34]Jiazi Zhang, Zhigang Chu, Lalitha Sankar, Oliver Kosut:
False Data Injection Attacks on Phasor Measurements That Bypass Low-rank Decomposition. CoRR abs/1705.02038 (2017) - [i33]Zhigang Chu, Jiazi Zhang, Oliver Kosut, Lalitha Sankar:
Vulnerability Assessment of Large-scale Power Systems to False Data Injection Attacks. CoRR abs/1705.04218 (2017) - [i32]Kousha Kalantari, Oliver Kosut, Lalitha Sankar:
Information-Theoretic Privacy with General Distortion Constraints. CoRR abs/1708.05468 (2017) - [i31]Chong Huang, Peter Kairouz, Xiao Chen, Lalitha Sankar, Ram Rajagopal:
Context-Aware Generative Adversarial Privacy. CoRR abs/1710.09549 (2017) - 2016
- [j16]Jiazi Zhang, Lalitha Sankar:
Physical System Consequences of Unobservable State-and-Topology Cyber-Physical Attacks. IEEE Trans. Smart Grid 7(4): 2016-2025 (2016) - [c35]Kousha Kalantari, Oliver Kosut, Lalitha Sankar:
On the fine asymptotics of information theoretic privacy. Allerton 2016: 532-539 - [c34]Jiachun Liao, Lalitha Sankar, Vincent Y. F. Tan, Flávio P. Calmon:
Hypothesis testing in the high privacy limit. Allerton 2016: 649-656 - [c33]Chong Huang, Lalitha Sankar:
Incentive mechanisms for privacy-sensitive electricity consumers with alternative energy sources. CISS 2016: 175-180 - [c32]Kousha Kalantari, Lalitha Sankar, Anand D. Sarwate:
Optimal differential privacy mechanisms under Hamming distortion for structured source classes. ISIT 2016: 2069-2073 - [c31]Zhigang Chu, Jiazi Zhang, Oliver Kosut, Lalitha Sankar:
Evaluating power system vulnerability to false data injection attacks via scalable optimization. SmartGridComm 2016: 260-265 - [i30]Kousha Kalantari, Lalitha Sankar, Anand D. Sarwate:
The Optimal Differential Privacy Mechanism under Hamming Distortion for Universal Memoryless Source Classes. CoRR abs/1601.06426 (2016) - [i29]Zhigang Chu, Jiazi Zhang, Oliver Kosut, Lalitha Sankar:
Evaluating Power System Vulnerability to False Data Injection Attacks via Scalable Optimization. CoRR abs/1605.06557 (2016) - [i28]