Pritish Kamath

According to our database, Pritish Kamath authored at least 62 papers between 2011 and 2025.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2025

How Unique is Whose Web Browser? The role of demographics in browser fingerprinting among US users.

Alex Berke, Badih Ghazi, Enrico Bacis, Pritish Kamath, Ravi Kumar, Robin Lassonde, Pasin Manurangsi, Umar Syed

Proc. Priv. Enhancing Technol., 2025

2024

Summary Reports Optimization in the Privacy Sandbox Attribution Reporting API.

Hidayet Aksu, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon, Avinash V. Varadarajan

Proc. Priv. Enhancing Technol., 2024

Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy.

Yangsibo Huang, Daogao Liu, Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Milad Nasr, Amer Sinha, Chiyuan Zhang

CoRR, 2024

Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models.

Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chulin Xie, Chiyuan Zhang

CoRR, 2024

Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning.

Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Daogao Liu, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang

CoRR, 2024

Differentially Private Optimization with Sparse Gradients.

Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

CoRR, 2024

How Private is DP-SGD?

Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang

CoRR, 2024

Training Differentially Private Ad Prediction Models with Semi-Sensitive Features.

Lynn Chua, Qiliang Cui, Badih Ghazi, Charlie Harrison, Pritish Kamath, Walid Krichene, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang

CoRR, 2024

Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization.

Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon

Proceedings of the Forty-first International Conference on Machine Learning, 2024

How Private are DP-SGD Implementations?

Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

LabelDP-Pro: Learning with Label Differential Privacy via Projections.

Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

On Convex Optimization with Semi-Sensitive Features.

Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Learning Neural Networks with Sparse Activations.

Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath, Raghu Meka

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Training Differentially Private Ad Prediction Models With Semi-Sensitive Features.

Lynn Chua, Qiliang Cui, Badih Ghazi, Charlie Harrison, Pritish Kamath, Walid Krichene, Ravi Kumar, Pasin Manurangsi, Nicolas Mayoraz, Hema Venkata Krishna Giri Narra, Steffen Rendle, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang

Proceedings of the Workshop on Data Mining for Online Advertising (AdKDD 2024) co-located with the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024), 2024

2023

Supervised Bayesian specification inference from demonstrations.

Ankit Shah, Pritish Kamath, Shen Li, Patrick L. Craven, Kevin J. Landers, Kevin Oden, Julie Shah

Int. J. Robotics Res., December, 2023

Separating Computational and Statistical Differential Privacy (Under Plausible Assumptions).

Badih Ghazi, Rahul Ilango, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

CoRR, 2023

Optimal Unbiased Randomizers for Regression with Label Differential Privacy.

Ashwinkumar Badanidiyuru Varadaraja, Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On Computing Pairwise Statistics with Local Differential Privacy.

Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

User-Level Differential Privacy With Few Examples Per User.

Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Sparsity-Preserving Differentially Private Training of Large Embedding Models.

Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On User-Level Private Convex Optimization.

Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang

Proceedings of the International Conference on Machine Learning, 2023

Regression with Label Differential Privacy.

Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

On Differentially Private Counting on Trees.

Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Kewen Wu

Proceedings of the 50th International Colloquium on Automata, Languages, and Programming, 2023

Towards Separating Computational and Statistical Differential Privacy.

Badih Ghazi, Rahul Ilango, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023

Ticketed Learning-Unlearning Schemes.

Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Private Ad Modeling with DP-SGD.

Carson Denison, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang

Proceedings of the Workshop on Data Mining for Online Advertising (AdKDD 2023) co-located with the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023), 2023

Optimizing Hierarchical Queries for the Attribution Reporting API.

Matthew Dawson, Badih Ghazi, Pritish Kamath, Kapil Kumar, Ravi Kumar, Bo Luan, Pasin Manurangsi, Nishanth Mundru, Harikesh Nair, Adam Sealfon, Shengyu Zhu

Proceedings of the Workshop on Data Mining for Online Advertising (AdKDD 2023) co-located with the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023), 2023

2022

Connect the Dots: Tighter Discrete Approximations of Privacy Loss Distributions.

Vadym Doroshenko, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

Proc. Priv. Enhancing Technol., 2022

Limits on the Efficiency of (Ring) LWE-Based Non-interactive Key Exchange.

Siyao Guo, Pritish Kamath, Alon Rosen, Katerina Sotiraki

J. Cryptol., 2022

Circuits Resilient to Short-Circuit Errors.

Klim Efremenko, Bernhard Haeupler, Yael Kalai, Pritish Kamath, Gillat Kol, Nicolas Resch, Raghuvansh Saxena

Electron. Colloquium Comput. Complex., 2022

Understanding the Eluder Dimension.

Gene Li, Pritish Kamath, Dylan J. Foster, Nati Srebro

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Private Isotonic Regression.

Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Anonymized Histograms in Intermediate Privacy Models.

Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Faster Privacy Accounting via Evolving Discretization.

Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

Proceedings of the International Conference on Machine Learning, 2022

Do More Negative Samples Necessarily Hurt In Contrastive Learning?

Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath

Proceedings of the International Conference on Machine Learning, 2022

2021

Eluder Dimension and Generalized Rank.

Gene Li, Pritish Kamath, Dylan J. Foster, Nathan Srebro

CoRR, 2021

On the Power of Differentiable Learning versus PAC and SQ Learning.

Emmanuel Abbe, Pritish Kamath, Eran Malach, Colin Sandon, Nathan Srebro

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels.

Eran Malach, Pritish Kamath, Emmanuel Abbe, Nathan Srebro

Proceedings of the 38th International Conference on Machine Learning, 2021

Does Invariant Risk Minimization Capture Invariance?

Pritish Kamath, Akilesh Tangella, Danica J. Sutherland, Nathan Srebro

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Optimality of Correlated Sampling Strategies.

Mohammad Bavarian, Badih Ghazi, Elad Haramaty, Pritish Kamath, Ronald L. Rivest, Madhu Sudan

Theory Comput., 2020

Approximate is Good Enough: Probabilistic Variants of Dimensional and Margin Complexity.

Pritish Kamath, Omar Montasser, Nathan Srebro

Proceedings of the Conference on Learning Theory, 2020

On the Complexity of Modulo-q Arguments and the Chevalley - Warning Theorem.

Mika Göös, Pritish Kamath, Katerina Sotiraki, Manolis Zampetakis

Proceedings of the 35th Computational Complexity Conference, 2020

2019

Correction to: Query-to-Communication Lifting for P NP.

Mika Göös, Pritish Kamath, Toniann Pitassi, Thomas Watson

Comput. Complex., 2019

Query-to-Communication Lifting for P NP.

Mika Göös, Pritish Kamath, Toniann Pitassi, Thomas Watson

Comput. Complex., 2019

2018

Adventures in Monotone Complexity and TFNP.

Mika Göös, Pritish Kamath, Robert Robere, Dmitry Sokolov

Electron. Colloquium Comput. Complex., 2018

Bayesian Inference of Temporal Task Specifications from Demonstrations.

Ankit Shah, Pritish Kamath, Julie A. Shah, Shen Li

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Dimension Reduction for Polynomials over Gaussian Space and Applications.

Badih Ghazi, Pritish Kamath, Prasad Raghavendra

Electron. Colloquium Comput. Complex., 2017

Monotone Circuit Lower Bounds from Resolution.

Ankit Garg, Mika Göös, Pritish Kamath, Dmitry Sokolov

Electron. Colloquium Comput. Complex., 2017

Unexpected power of low-depth arithmetic circuits.

Ankit Gupta, Pritish Kamath, Neeraj Kayal, Ramprasad Saptharishi

Commun. ACM, 2017

Improved bounds for universal one-bit compressive sensing.

Jayadev Acharya, Arnab Bhattacharyya, Pritish Kamath

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Compression in a Distributed Setting.

Badih Ghazi, Elad Haramaty, Pritish Kamath, Madhu Sudan

Proceedings of the 8th Innovations in Theoretical Computer Science Conference, 2017

2016

Arithmetic Circuits: A Chasm at Depth 3.

Ankit Gupta, Pritish Kamath, Neeraj Kayal, Ramprasad Saptharishi

SIAM J. Comput., 2016

Decidability of Non-Interactive Simulation of Joint Distributions.

Badih Ghazi, Pritish Kamath, Madhu Sudan

Electron. Colloquium Comput. Complex., 2016

The Optimality of Correlated Sampling.

Mohammad Bavarian, Badih Ghazi, Elad Haramaty, Pritish Kamath, Ronald L. Rivest, Madhu Sudan

Electron. Colloquium Comput. Complex., 2016

2015

Communication Complexity of Permutation-Invariant Functions.

Badih Ghazi, Pritish Kamath, Madhu Sudan

Electron. Colloquium Comput. Complex., 2015

Communication with Partial Noiseless Feedback.

Bernhard Haeupler, Pritish Kamath, Ameya Velingker

Proceedings of the Approximation, 2015

2014

Approaching the Chasm at Depth Four.

Ankit Gupta, Pritish Kamath, Neeraj Kayal, Ramprasad Saptharishi

J. ACM, 2014

2013

Arithmetic circuits: A chasm at depth three.

Ankit Gupta, Pritish Kamath, Neeraj Kayal, Ramprasad Saptharishi

Electron. Colloquium Comput. Complex., 2013

2012

An exponential lower bound for homogeneous depth four arithmetic circuits with bounded bottom fanin.

Ankit Gupta, Pritish Kamath, Neeraj Kayal, Ramprasad Saptharishi

Electron. Colloquium Comput. Complex., 2012

Preservation under Substructures modulo Bounded Cores.

Abhisekh Sankaran, Bharat Adsul, Vivek Madan, Pritish Kamath, Supratik Chakraborty

Proceedings of the Logic, Language, Information and Computation, 2012

Faster Algorithms for Alternating Refinement Relations.

Krishnendu Chatterjee, Siddhesh Chaubal, Pritish Kamath

Proceedings of the Computer Science Logic (CSL'12), 2012

2011

Using Dominances for Solving the Protein Family Identification Problem.

Noël Malod-Dognin, Mathilde Le Boudic-Jamin, Pritish Kamath, Rumen Andonov

Proceedings of the Algorithms in Bioinformatics - 11th International Workshop, 2011