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ORCIDShiva Prasad Kasiviswanathan
Person information
- affiliation: Amazon Web Services, Palo Alto, CA, USA
- affiliation: Samsung Research America, Mountain View, CA, USA
- affiliation: GE Global Research Center, Camino Ramon, CA, USA
- affiliation: IBM T. J. Watson Research Center, Yorktown Heights, NY, USA
- affiliation: Los Alamos National Laboratory, NM, USA
- affiliation (PhD): Pennsylvania State University, University Park, PA, USA
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2020 – today
- 2024
[c55]Iden Kalemaj, Shiva Prasad Kasiviswanathan, Aaditya Ramdas:
Differentially Private Conditional Independence Testing. AISTATS 2024: 3700-3708- [c54]Michaela Hardt, William Roy Orchard, Patrick Blöbaum, Elke Kirschbaum, Shiva Prasad Kasiviswanathan:
The PetShop Dataset - Finding Causes of Performance Issues across Microservices. CLeaR 2024: 957-978 - 2023
- [c53]Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton, Patrick Blöbaum:
Thompson Sampling with Diffusion Generative Prior. ICML 2023: 13434-13468 - [c52]Aleksandr Podkopaev, Patrick Blöbaum, Shiva Prasad Kasiviswanathan, Aaditya Ramdas:
Sequential Kernelized Independence Testing. ICML 2023: 27957-27993 - [c51]Lie He, Shiva Prasad Kasiviswanathan:
Debiasing Conditional Stochastic Optimization. NeurIPS 2023 - [i29]Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton, Patrick Blöbaum:
Thompson Sampling with Diffusion Generative Prior. CoRR abs/2301.05182 (2023) - [i28]Patrick Chao, Patrick Blöbaum, Shiva Prasad Kasiviswanathan:
Interventional and Counterfactual Inference with Diffusion Models. CoRR abs/2302.00860 (2023) - [i27]Lie He, Shiva Prasad Kasiviswanathan:
Debiasing Conditional Stochastic Optimization. CoRR abs/2304.10613 (2023) - [i26]Iden Kalemaj, Shiva Prasad Kasiviswanathan, Aaditya Ramdas:
Differentially Private Conditional Independence Testing. CoRR abs/2306.06721 (2023) - [i25]Michaela Hardt, William Roy Orchard, Patrick Blöbaum, Shiva Prasad Kasiviswanathan, Elke Kirschbaum:
The PetShop Dataset - Finding Causes of Performance Issues across Microservices. CoRR abs/2311.04806 (2023) - 2022
- [c50]Abhinav Aggarwal, Shiva Prasad Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier:
Reconstructing Test Labels from Noisy Loss Functions. AISTATS 2022: 8570-8591 - [c49]Yonghan Jung, Shiva Prasad Kasiviswanathan, Jin Tian, Dominik Janzing, Patrick Blöbaum, Elias Bareinboim:
On Measuring Causal Contributions via do-interventions. ICML 2022: 10476-10501 - [c48]Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton:
Uplifting Bandits. NeurIPS 2022 - [c47]Jacob Imola, Shiva Prasad Kasiviswanathan, Stephen White, Abhinav Aggarwal, Nathanael Teissier:
Balancing utility and scalability in metric differential privacy. UAI 2022: 885-894 - [i24]Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton:
Uplifting Bandits. CoRR abs/2206.04091 (2022) - [i23]Aleksandr Podkopaev, Patrick Blöbaum, Shiva Prasad Kasiviswanathan, Aaditya Ramdas:
Sequential Kernelized Independence Testing. CoRR abs/2212.07383 (2022) - 2021
- [c46]Abhinav Aggarwal, Shiva Prasad Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier:
Label Inference Attacks from Log-loss Scores. ICML 2021: 120-129 - [c45]Dmitrii Avdiukhin, Shiva Prasad Kasiviswanathan:
Federated Learning under Arbitrary Communication Patterns. ICML 2021: 425-435 - [c44]Raghavendra Addanki, Shiva Prasad Kasiviswanathan:
Collaborative Causal Discovery with Atomic Interventions. NeurIPS 2021: 12761-12773 - [c43]Shiva Prasad Kasiviswanathan:
SGD with low-dimensional gradients with applications to private and distributed learning. UAI 2021: 1905-1915 - [i22]Abhinav Aggarwal, Shiva Prasad Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier:
Label Inference Attacks from Log-loss Scores. CoRR abs/2105.08266 (2021) - [i21]Raghavendra Addanki, Shiva Prasad Kasiviswanathan:
Collaborative Causal Discovery with Atomic Interventions. CoRR abs/2106.03028 (2021) - [i20]Abhinav Aggarwal, Shiva Prasad Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier:
On Codomain Separability and Label Inference from (Noisy) Loss Functions. CoRR abs/2107.03022 (2021) - 2020
- [j11]Yu-Xiang Wang
, Borja Balle, Shiva Prasad Kasiviswanathan:
Subsampled Rényi Differential Privacy and Analytical Moments Accountant. J. Priv. Confidentiality 10(2) (2020) - [c42]Shiyun Chen, Shiva Prasad Kasiviswanathan:
Contextual Online False Discovery Rate Control. AISTATS 2020: 952-961 - [c41]Raghavendra Addanki, Shiva Prasad Kasiviswanathan, Andrew McGregor, Cameron Musco:
Efficient Intervention Design for Causal Discovery with Latents. ICML 2020: 63-73 - [i19]Raghavendra Addanki, Shiva Prasad Kasiviswanathan, Andrew McGregor, Cameron Musco:
Efficient Intervention Design for Causal Discovery with Latents. CoRR abs/2005.11736 (2020)
2010 – 2019
- 2019
- [c40]Yu-Xiang Wang, Borja Balle, Shiva Prasad Kasiviswanathan:
Subsampled Renyi Differential Privacy and Analytical Moments Accountant. AISTATS 2019: 1226-1235 - [i18]Shiva Prasad Kasiviswanathan, Mark Rudelson:
Restricted Isometry Property under High Correlations. CoRR abs/1904.05510 (2019) - 2018
- [c39]Nina Narodytska, Shiva Prasad Kasiviswanathan, Leonid Ryzhyk, Mooly Sagiv, Toby Walsh:
Verifying Properties of Binarized Deep Neural Networks. AAAI 2018: 6615-6624 - [c38]Shiva Prasad Kasiviswanathan, Mark Rudelson:
Restricted Eigenvalue from Stable Rank with Applications to Sparse Linear Regression. COLT 2018: 1011-1041 - [c37]Tal Wagner, Sudipto Guha, Shiva Prasad Kasiviswanathan, Nina Mishra:
Semi-Supervised Learning on Data Streams via Temporal Label Propagation. ICML 2018: 5082-5091 - [c36]Shiva Prasad Kasiviswanathan, Nina Narodytska, Hongxia Jin:
Network Approximation using Tensor Sketching. IJCAI 2018: 2319-2325 - [i17]Yu-Xiang Wang, Borja Balle, Shiva Prasad Kasiviswanathan:
Subsampled Rényi Differential Privacy and Analytical Moments Accountant. CoRR abs/1808.00087 (2018) - 2017
- [c35]Nina Narodytska, Shiva Prasad Kasiviswanathan:
Simple Black-Box Adversarial Attacks on Deep Neural Networks. CVPR Workshops 2017: 1310-1318 - [c34]Shiva Prasad Kasiviswanathan, Kobbi Nissim, Hongxia Jin:
Private Incremental Regression. PODS 2017: 167-182 - [i16]Shiva Prasad Kasiviswanathan, Kobbi Nissim, Hongxia Jin:
Private Incremental Regression. CoRR abs/1701.01093 (2017) - [i15]Shiva Prasad Kasiviswanathan, Mark Rudelson:
Compressed Sparse Linear Regression. CoRR abs/1707.08092 (2017) - [i14]Nina Narodytska, Shiva Prasad Kasiviswanathan, Leonid Ryzhyk, Mooly Sagiv, Toby Walsh:
Verifying Properties of Binarized Deep Neural Networks. CoRR abs/1709.06662 (2017) - [i13]Shiva Prasad Kasiviswanathan, Nina Narodytska, Hongxia Jin:
Deep Neural Network Approximation using Tensor Sketching. CoRR abs/1710.07850 (2017) - 2016
- [c33]Rui Chen, Haoran Li, A. Kai Qin, Shiva Prasad Kasiviswanathan, Hongxia Jin:
Private spatial data aggregation in the local setting. ICDE 2016: 289-300 - [c32]Shinjae Yoo, Hao Huang, Shiva Prasad Kasiviswanathan:
Streaming spectral clustering. ICDE 2016: 637-648 - [c31]Shiva Prasad Kasiviswanathan, Hongxia Jin:
Efficient Private Empirical Risk Minimization for High-dimensional Learning. ICML 2016: 488-497 - [i12]Nina Narodytska, Shiva Prasad Kasiviswanathan:
Simple Black-Box Adversarial Perturbations for Deep Networks. CoRR abs/1612.06299 (2016) - 2015
- [j10]Hao Huang, Shiva Prasad Kasiviswanathan:
Streaming Anomaly Detection Using Randomized Matrix Sketching. Proc. VLDB Endow. 9(3): 192-203 (2015) - [c30]Shengping Zhang, Shiva Prasad Kasiviswanathan, Pong C. Yuen, Mehrtash Harandi:
Online Dictionary Learning on Symmetric Positive Definite Manifolds with Vision Applications. AAAI 2015: 3165-3173 - [c29]Shiva Prasad Kasiviswanathan, Mark Rudelson:
Spectral Norm of Random Kernel Matrices with Applications to Privacy. APPROX-RANDOM 2015: 898-914 - [c28]Hao Huang, Shinjae Yoo, Shiva Prasad Kasiviswanathan:
Unsupervised Feature Selection on Data Streams. CIKM 2015: 1031-1040 - [i11]Shiva Prasad Kasiviswanathan, Mark Rudelson:
Spectral Norm of Random Kernel Matrices with Applications to Privacy. CoRR abs/1504.05880 (2015) - 2014
- [j9]Martin Fürer, Shiva Prasad Kasiviswanathan:
Approximately Counting Embeddings into Random Graphs. Comb. Probab. Comput. 23(6): 1028-1056 (2014) - [j8]Shiva Prasad Kasiviswanathan, Adam D. Smith:
On the 'Semantics' of Differential Privacy: A Bayesian Formulation. J. Priv. Confidentiality 6(1) (2014) - [j7]Amos Beimel, Hai Brenner, Shiva Prasad Kasiviswanathan, Kobbi Nissim:
Bounds on the sample complexity for private learning and private data release. Mach. Learn. 94(3): 401-437 (2014) - 2013
- [j6]Shiva Prasad Kasiviswanathan, Gao Cong, Prem Melville, Richard D. Lawrence:
Novel document detection for massive data streams using distributed dictionary learning. IBM J. Res. Dev. 57(3/4): 9 (2013) - [j5]Martin Fürer, Serge Gaspers, Shiva Prasad Kasiviswanathan:
An exponential time 2-approximation algorithm for bandwidth. Theor. Comput. Sci. 511: 23-31 (2013) - [c27]Shiva Prasad Kasiviswanathan:
Fast online L1-dictionary learning algorithms for novel document detection. ICASSP 2013: 8585-8589 - [c26]Shiva Prasad Kasiviswanathan, Mark Rudelson, Adam D. Smith:
The Power of Linear Reconstruction Attacks. SODA 2013: 1415-1433 - [c25]Shiva Prasad Kasiviswanathan, Kobbi Nissim, Sofya Raskhodnikova, Adam D. Smith:
Analyzing Graphs with Node Differential Privacy. TCC 2013: 457-476 - 2012
- [j4]Martin Fürer, Shiva Prasad Kasiviswanathan:
Spanners for geometric intersection graphs with applications. J. Comput. Geom. 3(1): 31-64 (2012) - [c24]Haim Avron, Satyen Kale, Shiva Prasad Kasiviswanathan, Vikas Sindhwani:
Efficient and Practical Stochastic Subgradient Descent for Nuclear Norm Regularization. ICML 2012 - [c23]Shiva Prasad Kasiviswanathan, Huahua Wang, Arindam Banerjee, Prem Melville:
Online L1-Dictionary Learning with Application to Novel Document Detection. NIPS 2012: 2267-2275 - [i10]Shiva Prasad Kasiviswanathan, Mark Rudelson, Adam D. Smith:
The Power of Linear Reconstruction Attacks. CoRR abs/1210.2381 (2012) - 2011
- [j3]Shiva Prasad Kasiviswanathan, Bo Zhao, Sudarshan Vasudevan, Bhuvan Urgaonkar:
Bandwidth provisioning in infrastructure-based wireless networks employing directional antennas. Pervasive Mob. Comput. 7(1): 114-127 (2011) - [j2]Shiva Prasad Kasiviswanathan, Homin K. Lee, Kobbi Nissim, Sofya Raskhodnikova, Adam D. Smith:
What Can We Learn Privately? SIAM J. Comput. 40(3): 793-826 (2011) - [c22]Shiva Prasad Kasiviswanathan, Prem Melville, Arindam Banerjee, Vikas Sindhwani:
Emerging topic detection using dictionary learning. CIKM 2011: 745-754 - [c21]Shiva Prasad Kasiviswanathan, Stephan J. Eidenbenz, Guanhua Yan:
Geography-based analysis of the Internet infrastructure. INFOCOM 2011: 131-135 - [c20]Feng Pan, Shiva Prasad Kasiviswanathan:
Efficient placement of directional antennas in infrastructure-based wireless networks. MILCOM 2011: 1796-1801 - [c19]Shiva Prasad Kasiviswanathan, Cristopher Moore, Louis Theran:
The Rigidity Transition in Random Graphs. SODA 2011: 1237-1252 - 2010
- [c18]Shiva Prasad Kasiviswanathan, Feng Pan:
Matrix Interdiction Problem. CPAIOR 2010: 219-231 - [c17]Shiva Prasad Kasiviswanathan, Bo Zhao, Sudarshan Vasudevan, Bhuvan Urgaonkar:
Bandwidth Provisioning in Infrastructure-Based Wireless Networks Employing Directional Antennas. ICDCN 2010: 295-306 - [c16]Sunil Thulasidasan, Shiva Prasad Kasiviswanathan, Stephan J. Eidenbenz, Philip Romero:
Explicit Spatial Scattering for Load Balancing in Conservatively Synchronized Parallel Discrete Event Simulations. PADS 2010: 150-157 - [c15]Shiva Prasad Kasiviswanathan, Mark Rudelson, Adam D. Smith, Jonathan R. Ullman:
The price of privately releasing contingency tables and the spectra of random matrices with correlated rows. STOC 2010: 775-784 - [c14]Amos Beimel, Shiva Prasad Kasiviswanathan, Kobbi Nissim:
Bounds on the Sample Complexity for Private Learning and Private Data Release. TCC 2010: 437-454 - [i9]Shiva Prasad Kasiviswanathan, Cristopher Moore, Louis Theran:
The rigidity transition in random graphs. CoRR abs/1010.3605 (2010)
2000 – 2009
- 2009
- [c13]Sunil Thulasidasan, Shiva Prasad Kasiviswanathan, Stephan J. Eidenbenz, Emanuele Galli, Susan M. Mniszewski, Philip Romero:
Designing systems for large-scale, discrete-event simulations: Experiences with the FastTrans parallel microsimulator. HiPC 2009: 428-437 - [c12]Martin Fürer, Serge Gaspers, Shiva Prasad Kasiviswanathan:
An Exponential Time 2-Approximation Algorithm for Bandwidth. IWPEC 2009: 173-184 - [i8]Martin Fürer, Serge Gaspers, Shiva Prasad Kasiviswanathan:
An Exponential Time 2-Approximation Algorithm for Bandwidth. CoRR abs/0906.1953 (2009) - 2008
- [c11]Martin Fürer, Shiva Prasad Kasiviswanathan:
Approximately Counting Embeddings into Random Graphs. APPROX-RANDOM 2008: 416-429 - [c10]Shiva Prasad Kasiviswanathan, Homin K. Lee, Kobbi Nissim, Sofya Raskhodnikova, Adam D. Smith:
What Can We Learn Privately? FOCS 2008: 531-540 - [c9]Srivatsava Ranjit Ganta, Shiva Prasad Kasiviswanathan, Adam D. Smith:
Composition attacks and auxiliary information in data privacy. KDD 2008: 265-273 - [i7]Srivatsava Ranjit Ganta, Shiva Prasad Kasiviswanathan, Adam D. Smith:
Composition Attacks and Auxiliary Information in Data Privacy. CoRR abs/0803.0032 (2008) - [i6]Shiva Prasad Kasiviswanathan, Homin K. Lee, Kobbi Nissim, Sofya Raskhodnikova, Adam D. Smith:
What Can We Learn Privately? CoRR abs/0803.0924 (2008) - [i5]Shiva Prasad Kasiviswanathan, Adam D. Smith:
A Note on Differential Privacy: Defining Resistance to Arbitrary Side Information. CoRR abs/0803.3946 (2008) - [i4]Martin Fürer, Shiva Prasad Kasiviswanathan:
Approximately Counting Embeddings into Random Graphs. CoRR abs/0806.2287 (2008) - 2007
- [c8]Martin Fürer, Shiva Prasad Kasiviswanathan:
Algorithms for Counting 2-SatSolutions and Colorings with Applications. AAIM 2007: 47-57 - [c7]Martin Fürer, Shiva Prasad Kasiviswanathan:
Exact Max 2-Sat: Easier and Faster. SOFSEM (1) 2007: 272-283 - [c6]Piotr Berman, Jieun K. Jeong, Shiva Prasad Kasiviswanathan, Bhuvan Urgaonkar:
Packing to angles and sectors. SPAA 2007: 171-180 - [c5]Martin Fürer, Shiva Prasad Kasiviswanathan:
Spanners for Geometric Intersection Graphs. WADS 2007: 312-324 - [c4]Piotr Berman, Shiva Prasad Kasiviswanathan:
Faster Approximation of Distances in Graphs. WADS 2007: 541-552 - 2006
- [j1]Anders Hansson, Gabriel Istrate, Shiva Prasad Kasiviswanathan:
Combinatorics of TCP reordering. J. Comb. Optim. 12(1-2): 57-70 (2006) - [c3]Martin Fürer, Shiva Prasad Kasiviswanathan:
Approximate Distance Queries in Disk Graphs. WAOA 2006: 174-187 - [i3]Martin Fürer, Shiva Prasad Kasiviswanathan:
Spanners for Geometric Intersection Graphs. CoRR abs/cs/0605029 (2006) - [i2]Piotr Berman, Jieun K. Jeong, Shiva Prasad Kasiviswanathan, Bhuvan Urgaonkar:
Packing to angles and sectors. Electron. Colloquium Comput. Complex. TR06 (2006) - 2005
- [c2]Martin Fürer, Shiva Prasad Kasiviswanathan:
Approximately Counting Perfect Matchings in General Graphs. ALENEX/ANALCO 2005: 263-272 - [i1]Martin Fürer, Shiva Prasad Kasiviswanathan:
Algorithms for Counting 2-SAT Solutions and Colorings with Applications. Electron. Colloquium Comput. Complex. TR05 (2005) - 2004
- [c1]Martin Fürer, Shiva Prasad Kasiviswanathan:
An Almost Linear Time Approximation Algorithm for the Permanen of a Random (0-1) Matrix. FSTTCS 2004: 263-274
Coauthor Index
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