An Almost Linear Time Approximation Algorithm for the Permanen of a Random (0-1) Matrix. - Martin Fürer; Shiva Prasad Kasiviswanathan (FSTTCS, 2004)

Approximately Counting Perfect Matchings in General Graphs. - Martin Fürer; Shiva Prasad Kasiviswanathan (ALENEX/ANALCO, 2005)

Algorithms for Counting 2-SAT Solutions and Colorings with Applications - Martin Fürer; Shiva Prasad Kasiviswanathan (Electron. Colloquium Comput. Complex., 2005)

Approximate Distance Queries in Disk Graphs. - Martin Fürer; Shiva Prasad Kasiviswanathan (WAOA, 2006)

Packing to angles and sectors. - Piotr Berman; Jieun K. Jeong; Shiva Prasad Kasiviswanathan; Bhuvan Urgaonkar (Electron. Colloquium Comput. Complex., 2006)

Combinatorics of TCP reordering. - Anders Hansson; Gabriel Istrate; Shiva Prasad Kasiviswanathan (J. Comb. Optim., 2006)

Algorithms for Counting 2-SatSolutions and Colorings with Applications. - Martin Fürer; Shiva Prasad Kasiviswanathan (AAIM, 2007)

Exact Max 2-Sat: Easier and Faster. - Martin Fürer; Shiva Prasad Kasiviswanathan (SOFSEM (1), 2007)

Faster Approximation of Distances in Graphs. - Piotr Berman; Shiva Prasad Kasiviswanathan (WADS, 2007)

Spanners for Geometric Intersection Graphs. - Martin Fürer; Shiva Prasad Kasiviswanathan (WADS, 2007)

Composition attacks and auxiliary information in data privacy. - Srivatsava Ranjit Ganta; Shiva Prasad Kasiviswanathan; Adam D. Smith 001 (KDD, 2008)

A Note on Differential Privacy: Defining Resistance to Arbitrary Side Information - Shiva Prasad Kasiviswanathan; Adam D. Smith 001 (CoRR, 2008)

Designing systems for large-scale, discrete-event simulations: Experiences with the FastTrans parallel microsimulator. - Sunil Thulasidasan; Shiva Prasad Kasiviswanathan; Stephan J. Eidenbenz; Emanuele Galli; Susan M. Mniszewski; Philip Romero (HiPC, 2009)

Matrix Interdiction Problem. - Shiva Prasad Kasiviswanathan; Feng Pan 005 (CPAIOR, 2010)

Explicit Spatial Scattering for Load Balancing in Conservatively Synchronized Parallel Discrete Event Simulations. - Sunil Thulasidasan; Shiva Prasad Kasiviswanathan; Stephan J. Eidenbenz; Philip Romero (PADS, 2010)

The price of privately releasing contingency tables and the spectra of random matrices with correlated rows. - Shiva Prasad Kasiviswanathan; Mark Rudelson; Adam D. Smith 001; Jonathan R. Ullman (STOC, 2010)

Bounds on the Sample Complexity for Private Learning and Private Data Release. - Amos Beimel; Shiva Prasad Kasiviswanathan; Kobbi Nissim (TCC, 2010)

Emerging topic detection using dictionary learning. - Shiva Prasad Kasiviswanathan; Prem Melville; Arindam Banerjee 001; Vikas Sindhwani (CIKM, 2011)

Geography-based analysis of the Internet infrastructure. - Shiva Prasad Kasiviswanathan; Stephan J. Eidenbenz; Guanhua Yan (INFOCOM, 2011)

Efficient placement of directional antennas in infrastructure-based wireless networks. - Feng Pan 005; Shiva Prasad Kasiviswanathan (MILCOM, 2011)

The Rigidity Transition in Random Graphs. - Shiva Prasad Kasiviswanathan; Cristopher Moore; Louis Theran (SODA, 2011)

Bandwidth provisioning in infrastructure-based wireless networks employing directional antennas. - Shiva Prasad Kasiviswanathan; Bo Zhao 009; Sudarshan Vasudevan; Bhuvan Urgaonkar (Pervasive Mob. Comput., 2011)

What Can We Learn Privately? - Shiva Prasad Kasiviswanathan; Homin K. Lee; Kobbi Nissim; Sofya Raskhodnikova; Adam D. Smith 001 (SIAM J. Comput., 2011)

Efficient and Practical Stochastic Subgradient Descent for Nuclear Norm Regularization. - Haim Avron; Satyen Kale; Shiva Prasad Kasiviswanathan; Vikas Sindhwani (ICML, 2012)

Online L1-Dictionary Learning with Application to Novel Document Detection. - Shiva Prasad Kasiviswanathan; Huahua Wang; Arindam Banerjee 001; Prem Melville (NIPS, 2012)

Spanners for geometric intersection graphs with applications. - Martin Fürer; Shiva Prasad Kasiviswanathan (J. Comput. Geom., 2012)

Fast online L1-dictionary learning algorithms for novel document detection. - Shiva Prasad Kasiviswanathan (ICASSP, 2013)

The Power of Linear Reconstruction Attacks. - Shiva Prasad Kasiviswanathan; Mark Rudelson; Adam D. Smith 001 (SODA, 2013)

Analyzing Graphs with Node Differential Privacy. - Shiva Prasad Kasiviswanathan; Kobbi Nissim; Sofya Raskhodnikova; Adam D. Smith 001 (TCC, 2013)

Novel document detection for massive data streams using distributed dictionary learning. - Shiva Prasad Kasiviswanathan; Gao Cong; Prem Melville; Richard D. Lawrence (IBM J. Res. Dev., 2013)

An exponential time 2-approximation algorithm for bandwidth. - Martin Fürer; Serge Gaspers; Shiva Prasad Kasiviswanathan (Theor. Comput. Sci., 2013)

Approximately Counting Embeddings into Random Graphs. - Martin Fürer; Shiva Prasad Kasiviswanathan (Comb. Probab. Comput., 2014)

On the 'Semantics' of Differential Privacy: A Bayesian Formulation. - Shiva Prasad Kasiviswanathan; Adam D. Smith 001 (J. Priv. Confidentiality, 2014)

Bounds on the sample complexity for private learning and private data release. - Amos Beimel; Hai Brenner; Shiva Prasad Kasiviswanathan; Kobbi Nissim (Mach. Learn., 2014)

Online Dictionary Learning on Symmetric Positive Definite Manifolds with Vision Applications. - Shengping Zhang; Shiva Prasad Kasiviswanathan; Pong C. Yuen; Mehrtash Harandi (AAAI, 2015)

Spectral Norm of Random Kernel Matrices with Applications to Privacy. - Shiva Prasad Kasiviswanathan; Mark Rudelson (APPROX-RANDOM, 2015)

Unsupervised Feature Selection on Data Streams. - Hao Huang 007; Shinjae Yoo; Shiva Prasad Kasiviswanathan (CIKM, 2015)

Streaming Anomaly Detection Using Randomized Matrix Sketching. - Hao Huang; Shiva Prasad Kasiviswanathan (Proc. VLDB Endow., 2015)

Private spatial data aggregation in the local setting. - Rui Chen 012; Haoran Li; A. Kai Qin; Shiva Prasad Kasiviswanathan; Hongxia Jin (ICDE, 2016)

Streaming spectral clustering. - Shinjae Yoo; Hao Huang 007; Shiva Prasad Kasiviswanathan (ICDE, 2016)

Efficient Private Empirical Risk Minimization for High-dimensional Learning. - Shiva Prasad Kasiviswanathan; Hongxia Jin (ICML, 2016)

Simple Black-Box Adversarial Perturbations for Deep Networks. - Nina Narodytska; Shiva Prasad Kasiviswanathan (CoRR, 2016)

Simple Black-Box Adversarial Attacks on Deep Neural Networks. - Nina Narodytska; Shiva Prasad Kasiviswanathan (CVPR Workshops, 2017)

Private Incremental Regression. - Shiva Prasad Kasiviswanathan; Kobbi Nissim; Hongxia Jin (PODS, 2017)

Compressed Sparse Linear Regression. - Shiva Prasad Kasiviswanathan; Mark Rudelson (CoRR, 2017)

Deep Neural Network Approximation using Tensor Sketching. - Shiva Prasad Kasiviswanathan; Nina Narodytska; Hongxia Jin (CoRR, 2017)

Verifying Properties of Binarized Deep Neural Networks. - Nina Narodytska; Shiva Prasad Kasiviswanathan; Leonid Ryzhyk; Mooly Sagiv; Toby Walsh (AAAI, 2018)

Restricted Eigenvalue from Stable Rank with Applications to Sparse Linear Regression. - Shiva Prasad Kasiviswanathan; Mark Rudelson (COLT, 2018)

Semi-Supervised Learning on Data Streams via Temporal Label Propagation. - Tal Wagner; Sudipto Guha; Shiva Prasad Kasiviswanathan; Nina Mishra (ICML, 2018)

Network Approximation using Tensor Sketching. - Shiva Prasad Kasiviswanathan; Nina Narodytska; Hongxia Jin (IJCAI, 2018)

Restricted Isometry Property under High Correlations. - Shiva Prasad Kasiviswanathan; Mark Rudelson (CoRR, 2019)

Contextual Online False Discovery Rate Control. - Shiyun Chen; Shiva Prasad Kasiviswanathan (AISTATS, 2020)

Efficient Intervention Design for Causal Discovery with Latents. - Raghavendra Addanki; Shiva Prasad Kasiviswanathan; Andrew McGregor 001; Cameron Musco (ICML, 2020)

Subsampled Rényi Differential Privacy and Analytical Moments Accountant. - Yu-Xiang Wang 003; Borja Balle; Shiva Prasad Kasiviswanathan (J. Priv. Confidentiality, 2020)

Label Inference Attacks from Log-loss Scores. - Abhinav Aggarwal; Shiva Prasad Kasiviswanathan; Zekun Xu; Oluwaseyi Feyisetan; Nathanael Teissier (ICML, 2021)

Federated Learning under Arbitrary Communication Patterns. - Dmitrii Avdiukhin; Shiva Prasad Kasiviswanathan (ICML, 2021)

Collaborative Causal Discovery with Atomic Interventions. - Raghavendra Addanki; Shiva Prasad Kasiviswanathan (NeurIPS, 2021)

SGD with low-dimensional gradients with applications to private and distributed learning. - Shiva Prasad Kasiviswanathan (UAI, 2021)

On Codomain Separability and Label Inference from (Noisy) Loss Functions. - Abhinav Aggarwal; Shiva Prasad Kasiviswanathan; Zekun Xu; Oluwaseyi Feyisetan; Nathanael Teissier (CoRR, 2021)

Reconstructing Test Labels from Noisy Loss Functions. - Abhinav Aggarwal; Shiva Prasad Kasiviswanathan; Zekun Xu; Oluwaseyi Feyisetan; Nathanael Teissier (AISTATS, 2022)

On Measuring Causal Contributions via do-interventions. - Yonghan Jung; Shiva Prasad Kasiviswanathan; Jin Tian 001; Dominik Janzing; Patrick Blöbaum; Elias Bareinboim (ICML, 2022)

Uplifting Bandits. - Yu-Guan Hsieh; Shiva Prasad Kasiviswanathan; Branislav Kveton (NeurIPS, 2022)

Balancing utility and scalability in metric differential privacy. - Jacob Imola; Shiva Prasad Kasiviswanathan; Stephen White; Abhinav Aggarwal; Nathanael Teissier (UAI, 2022)

Thompson Sampling with Diffusion Generative Prior. - Yu-Guan Hsieh; Shiva Prasad Kasiviswanathan; Branislav Kveton; Patrick Blöbaum (ICML, 2023)

Sequential Kernelized Independence Testing. - Aleksandr Podkopaev; Patrick Blöbaum; Shiva Prasad Kasiviswanathan; Aaditya Ramdas (ICML, 2023)

Debiasing Conditional Stochastic Optimization. - Lie He; Shiva Prasad Kasiviswanathan (NeurIPS, 2023)

Interventional and Counterfactual Inference with Diffusion Models. - Patrick Chao; Patrick Blöbaum; Shiva Prasad Kasiviswanathan (CoRR, 2023)

Differentially Private Conditional Independence Testing. - Iden Kalemaj; Shiva Prasad Kasiviswanathan; Aaditya Ramdas (AISTATS, 2024)

The PetShop Dataset - Finding Causes of Performance Issues across Microservices. - Michaela Hardt; William Roy Orchard; Patrick Blöbaum; Elke Kirschbaum; Shiva Prasad Kasiviswanathan (CLeaR, 2024)

Benign Overfitting for Regression with Trained Two-Layer ReLU Networks. - Junhyung Park; Patrick Blöbaum; Shiva Prasad Kasiviswanathan (CoRR, 2024)

β-calibration of Language Model Confidence Scores for Generative QA. - Putra Manggala; Atalanti-Anastasia Mastakouri; Elke Kirschbaum; Shiva Prasad Kasiviswanathan; Aaditya Ramdas (CoRR, 2024)

Modeling Causal Mechanisms with Diffusion Models for Interventional and Counterfactual Queries. - Patrick Chao; Patrick Blöbaum; Sapan Kirit Patel; Shiva Prasad Kasiviswanathan (Trans. Mach. Learn. Res., 2024)

QA-Calibration of Language Model Confidence Scores. - Putra Manggala; Atalanti-Anastasia Mastakouri; Elke Kirschbaum; Shiva Prasad Kasiviswanathan; Aaditya Ramdas (ICLR, 2025)

A Classical View on Benign Overfitting: The Role of Sample Size. - Junhyung Park; Patrick Blöbaum; Shiva Prasad Kasiviswanathan (CoRR, 2025)