Lalitha Sankar

ORCID

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 119

Top Venues

CoRR

ISIT

IEEE Trans. Inf. Theory

SmartGridComm

Publications

Monica Welfert, Nathan Stromberg, Lalitha Sankar
Theoretical Guarantees of Data Augmented Last Layer Retraining Methods. CoRR (2024)
Nathan Stromberg, Rohan Ayyagari, Monica Welfert, Sanmi Koyejo, Lalitha Sankar
Robustness to Subpopulation Shift with Domain Label Noise via Regularized Annotation of Domains. CoRR (2024)
Joel Mathias, Rajasekhar Anguluri, Oliver Kosut, Lalitha Sankar
Model Predictive Control for Joint Ramping and Regulation-Type Service from Distributed Energy Resource Aggregations. CoRR (2024)
Obai Bahwal, Oliver Kosut, Lalitha Sankar
An Adversarial Approach to Evaluating the Robustness of Event Identification Models. CoRR (2024)
Monica Welfert, Gowtham R. Kurri, Kyle Otstot, Lalitha Sankar
Addressing GAN Training Instabilities via Tunable Classification Losses. IEEE J. Sel. Areas Inf. Theory 5 (2024)
Gowtham R. Kurri, Lalitha Sankar, Oliver Kosut
An Operational Approach to Information Leakage via Generalized Gain Functions. IEEE Trans. Inf. Theory 70 (2) (2024)
Atefeh Gilani, Gowtham R. Kurri, Oliver Kosut, Lalitha Sankar
Unifying Privacy Measures via Maximal (α, β)-Leakage (MαbeL). IEEE Trans. Inf. Theory 70 (6) (2024)
Rajasekhar Anguluri, Oliver Kosut, Lalitha Sankar
Identifying Edge Changes in Networks From Input and Output Covariance Data. IEEE Control. Syst. Lett. 8 (2024)
Nathan Stromberg, Rohan Ayyagari, Sanmi Koyejo, Richard Nock, Lalitha Sankar
Label Noise Robustness for Domain-Agnostic Fair Corrections via Nearest Neighbors Label Spreading. CoRR (2024)
Atefeh Gilani, Gowtham R. Kurri, Oliver Kosut, Lalitha Sankar
(α, β)-Leakage: A Unified Privacy Leakage Measure. CoRR (2023)
Monica Welfert, Kyle Otstot, Gowtham R. Kurri, Lalitha Sankar
Towards Addressing GAN Training Instabilities: Dual-objective GANs with Tunable Parameters. CoRR (2023)
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)
Wael Alghamdi, Juan Felipe Gómez, Shahab Asoodeh, Flávio P. Calmon, Oliver Kosut, Lalitha Sankar
The Saddle-Point Method in Differential Privacy. ICML (2023)
Joshua Inman, Tanmay Khandait, Giulia Pedrielli, Lalitha Sankar
Parameter Optimization with Conscious Allocation (POCA). CoRR (2023)
Rajasekhar Anguluri, Oliver Kosut, Lalitha Sankar
Localization and Estimation of Unknown Forced Inputs: A Group LASSO Approach. IEEE Trans. Control. Netw. Syst. 10 (4) (2023)
Monica Welfert, Kyle Otstot, Gowtham R. Kurri, Lalitha Sankar
(αD, αG)-GANs: Addressing GAN Training Instabilities via Dual Objectives. ISIT (2023)
Rajasekhar Anguluri, Nima Taghipourbazargani, Oliver Kosut, Lalitha Sankar
Source Localization in Linear Dynamical Systems using Subspace Model Identification. CCTA (2023)
Nima Taghipourbazargani, Lalitha Sankar, Oliver Kosut
A Semi-Supervised Approach for Power System Event Identification. CoRR (2023)
Tyler Sypherd, Nathaniel Stromberg, Richard Nock, Visar Berisha, Lalitha Sankar
Smoothly Giving up: Robustness for Simple Models. AISTATS (2023)
Monica Welfert, Gowtham R. Kurri, Kyle Otstot, Lalitha Sankar
Addressing GAN Training Instabilities via Tunable Classification Losses. CoRR (2023)
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) (2023)
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)
Joshua Inman, Tanmay Khandait, Giulia Pedrielli, Lalitha Sankar
Parameter Optimization with Conscious Allocation (POCA). WSC (2023)
Tyler Sypherd, Nathan Stromberg, Richard Nock, Visar Berisha, Lalitha Sankar
Smoothly Giving up: Robustness for Simple Models. CoRR (2023)
Anguluri Rajasekhar, Lalitha Sankar, Oliver Kosut
Parameter Estimation in Ill-conditioned Low-inertia Power Systems. CoRR (2022)
Wael Alghamdi, Shahab Asoodeh, Flávio P. Calmon, Juan Felipe Gómez, Oliver Kosut, Lalitha Sankar, Fei Wei
The Saddle-Point Accountant for Differential Privacy. CoRR (2022)
Gowtham R. Kurri, Lalitha Sankar, Oliver Kosut
An Operational Approach to Information Leakage via Generalized Gain Functions. CoRR (2022)
Anjana Arunkumar, Andrea Pinceti, Lalitha Sankar, Chris Bryan
PMU Tracker: A Visualization Platform for Epicentric Event Propagation Analysis in the Power Grid. CoRR (2022)
Gowtham R. Kurri, Monica Welfert, Tyler Sypherd, Lalitha Sankar
α-GAN: Convergence and Estimation Guarantees. CoRR (2022)
Atefeh Gilani, Gowtham R. Kurri, Oliver Kosut, Lalitha Sankar
An Alphabet of Leakage Measures. CoRR (2022)
Kyle Otstot, John Kevin Cava, Tyler Sypherd, Lalitha Sankar
AugLoss: A Learning Methodology for Real-World Dataset Corruption. CoRR (2022)
Gowtham R. Kurri, Oliver Kosut, Lalitha Sankar
A Variational Formula for Infinity-Rényi Divergence with Applications to Information Leakage. CoRR (2022)
Abrar Zahin, Rajasekhar Anguluri, Oliver Kosut, Lalitha Sankar, Gautam Dasarathy
Robust Model Selection of Non Tree-Structured Gaussian Graphical Models. CoRR (2022)
Nima T. Bazargani, Gautam Dasarathy, Lalitha Sankar, Oliver Kosut
A Machine Learning Framework for Event Identification via Modal Analysis of PMU Data. CoRR (2022)
Atefeh Gilani, Gowtham R. Kurri, Oliver Kosut, Lalitha Sankar
An Alphabet of Leakage Measures. ITW (2022)
Gowtham R. Kurri, Oliver Kosut, Lalitha Sankar
A Variational Formula for Infinity-Rényi Divergence with Applications to Information Leakage. ISIT (2022)
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) (2022)
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) (2022)
Gowtham R. Kurri, Monica Welfert, Tyler Sypherd, Lalitha Sankar
α-GAN: Convergence and Estimation Guarantees. ISIT (2022)
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 (2022)
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)
Anguluri Rajasekhar, Gautam Dasarathy, Oliver Kosut, Lalitha Sankar
Grid Topology Identification With Hidden Nodes via Structured Norm Minimization. IEEE Control. Syst. Lett. 6 (2022)
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 (2022)
Tyler Sypherd, Richard Nock, Lalitha Sankar
Being Properly Improper. ICML (2022)
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) (2021)
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) (2021)
Richard Nock, Tyler Sypherd, Lalitha Sankar
Being Properly Improper. CoRR (2021)
Mario Díaz, Peter Kairouz, Jiachun Liao, Lalitha Sankar
Neural Network-based Estimation of the MMSE. ISIT (2021)
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) (2021)
Gowtham R. Kurri, Tyler Sypherd, Lalitha Sankar
Realizing GANs via a Tunable Loss Function. CoRR (2021)
Mario Díaz, Peter Kairouz, Lalitha Sankar
Lower Bounds for the Minimum Mean-Square Error via Neural Network-based Estimation. CoRR (2021)
Andrea Pinceti, Lalitha Sankar, Oliver Kosut
Generation of Synthetic Multi-Resolution Time Series Load Data. CoRR (2021)
Andrea Pinceti, Lalitha Sankar, Oliver Kosut
Synthetic Time-Series Load Data via Conditional Generative Adversarial Networks. CoRR (2021)
Gowtham R. Kurri, Oliver Kosut, Lalitha Sankar
Evaluating Multiple Guesses by an Adversary via a Tunable Loss Function. ISIT (2021)
Gowtham R. Kurri, Tyler Sypherd, Lalitha Sankar
Realizing GANs via a Tunable Loss Function. ITW (2021)
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 (2021)
Gowtham R. Kurri, Oliver Kosut, Lalitha Sankar
Evaluating Multiple Guesses by an Adversary via a Tunable Loss Function. CoRR (2021)
Mario Díaz, Hao Wang, Flávio du Pin Calmon, Lalitha Sankar
On the Robustness of Information-Theoretic Privacy Measures and Mechanisms. IEEE Trans. Inf. Theory 66 (4) (2020)
Tyler Sypherd, Mario Díaz, Lalitha Sankar, Gautam Dasarathy
On the alpha-loss Landscape in the Logistic Model. CoRR (2020)
Zhigang Chu, Jiazi Zhang, Oliver Kosut, Lalitha Sankar
Vulnerability Assessment of Large-scale Power Systems to False Data Injection Attacks. SmartGridComm (2020)
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 (2020)
Shahab Asoodeh, Jiachun Liao, Flávio P. Calmon, Oliver Kosut, Lalitha Sankar
Three Variants of Differential Privacy: Lossless Conversion and Applications. CoRR (2020)
Jiachun Liao, Lalitha Sankar, Oliver Kosut, Flávio P. Calmon
Maximal α-Leakage and its Properties. CNS (2020)
Zhigang Chu, Oliver Kosut, Lalitha Sankar
Detecting Load Redistribution Attacks via Support Vector Models. CoRR (2020)
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)
Tyler Sypherd, Mario Díaz, Lalitha Sankar, Gautam Dasarathy
On the α-loss Landscape in the Logistic Model. ISIT (2020)
Zhigang Chu, Jiazi Zhang, Oliver Kosut, Lalitha Sankar
N-1 Reliability Makes It Difficult for False Data Injection Attacks to Cause Physical Consequences. CoRR (2020)
Jiachun Liao, Lalitha Sankar, Oliver Kosut, Flávio P. Calmon
Robustness of Maximal α-Leakage to Side Information. CoRR (2019)
Jiachun Liao, Lalitha Sankar, Oliver Kosut, Flávio P. Calmon
Robustness of Maximal α-Leakage to Side Information. ISIT (2019)
Tyler Sypherd, Mario Díaz, Lalitha Sankar, Peter Kairouz
A Tunable Loss Function for Binary Classification. ISIT (2019)
Zhigang Chu, Jiazi Zhang, Oliver Kosut, Lalitha Sankar
Vulnerability Assessment of N-1 Reliable Power Systems to False Data Injection Attacks. CoRR (2019)
Jiachun Liao, Chong Huang, Peter Kairouz, Lalitha Sankar
Learning Generative Adversarial RePresentations (GAP) under Fairness and Censoring Constraints. CoRR (2019)
Mario Díaz, Peter Kairouz, Jiachun Liao, Lalitha Sankar
Theoretical Guarantees for Model Auditing with Finite Adversaries. CoRR (2019)
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) (2019)
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)
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 (2019)
Andrea Pinceti, Lalitha Sankar, Oliver Kosut
Detection and Localization of Load Redistribution Attacks on Large Scale Systems. CoRR (2019)
Tyler Sypherd, Mario Díaz, Harshit Laddha, Lalitha Sankar, Peter Kairouz, Gautam Dasarathy
A Tunable Loss Function for Classification. CoRR (2019)
Tyler Sypherd, Mario Díaz, Lalitha Sankar, Peter Kairouz
A Tunable Loss Function for Binary Classification. CoRR (2019)
Mario Díaz, Hao Wang, Flávio P. Calmon, Lalitha Sankar
On the Robustness of Information-Theoretic Privacy Measures and Mechanisms. CoRR (2018)
Jiachun Liao, Oliver Kosut, Lalitha Sankar, Flávio P. Calmon
Privacy Under Hard Distortion Constraints. ITW (2018)
Chong Huang, Lalitha Sankar
Impact of Privacy on Free Online Service Markets. GameSec (2018)
Mario Díaz, Lalitha Sankar, Peter Kairouz
On the Contractivity of Privacy Mechanisms. CoRR (2018)
Hao Wang, Mario Díaz, Flávio du Pin Calmon, Lalitha Sankar
The Utility Cost of Robust Privacy Guarantees. CoRR (2018)
Hao Wang, Mario Díaz, Flávio P. Calmon, Lalitha Sankar
The Utility Cost of Robust Privacy Guarantees. ISIT (2018)
Jiachun Liao, Oliver Kosut, Lalitha Sankar, Flávio du Pin Calmon
Tunable Measures for Information Leakage and Applications to Privacy-Utility Tradeoffs. CoRR (2018)
Jiachun Liao, Oliver Kosut, Lalitha Sankar, Flávio du Pin Calmon
A Tunable Measure for Information Leakage. ISIT (2018)
Kousha Kalantari, Lalitha Sankar, Anand D. Sarwate
Robust Privacy-Utility Tradeoffs Under Differential Privacy and Hamming Distortion. IEEE Trans. Inf. Forensics Secur. 13 (11) (2018)
Chong Huang, Peter Kairouz, Xiao Chen, Lalitha Sankar, Ram Rajagopal
Generative Adversarial Privacy. CoRR (2018)
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) (2018)
Jiachun Liao, Oliver Kosut, Lalitha Sankar, Flávio du Pin Calmon
A Tunable Measure for Information Leakage. CoRR (2018)
Chong Huang, Peter Kairouz, Lalitha Sankar
Generative Adversarial Privacy: A Data-Driven Approach to Information-Theoretic Privacy. ACSSC (2018)
Zhigang Chu, Jiazi Zhang, Oliver Kosut, Lalitha Sankar
Unobservable False Data Injection Attacks against PMUs: Feasible Conditions and Multiplicative Attacks. CoRR (2018)
Zhigang Chu, Jiazi Zhang, Oliver Kosut, Lalitha Sankar
Unobservable False Data Injection Attacks against PMUs: Feasible Conditions and Multiplicative Attacks. SmartGridComm (2018)
Jiachun Liao, Oliver Kosut, Lalitha Sankar, Flávio du Pin Calmon
Privacy Under Hard Distortion Constraints. CoRR (2018)
Oliver Kosut, Lalitha Sankar
Asymptotics and Non-Asymptotics for Universal Fixed-to-Variable Source Coding. IEEE Trans. Inf. Theory 63 (6) (2017)
Jiachun Liao, Lalitha Sankar, Flávio du Pin Calmon, Vincent Yan Fu Tan
Hypothesis Testing under Maximal Leakage Privacy Constraints. CoRR (2017)
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 (2017)
Bahman Moraffah, Lalitha Sankar
Privacy-Guaranteed Two-Agent Interactions Using Information-Theoretic Mechanisms. IEEE Trans. Inf. Forensics Secur. 12 (9) (2017)
Jiazi Zhang, Zhigang Chu, Lalitha Sankar, Oliver Kosut
False Data Injection Attacks on Phasor Measurements That Bypass Low-rank Decomposition. CoRR (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Lalitha Sankar