Pritish Kamath

126 papers A* 33A 8B 2C 2Journal 76Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Computational Hardness of Private Coreset. CoRR Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi
2026	J	`jnl`	Denoising the US Census: Succinct Block Hierarchical Regression. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon
2025	A	`conf`	Balls-and-Bins Sampling for DP-SGD. AISTATS Lynn Chua, Badih Ghazi, Charlie Harrison, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2025	A*	`conf`	Empirical Privacy Variance. ICML Yuzheng Hu, Fan Wu, Ruicheng Xian, Yuhang Liu, Lydia Zakynthinou, Pritish Kamath, Chiyuan Zhang, David A. Forsyth
2025	J	`jnl`	Empirical Privacy Variance. CoRR Yuzheng Hu, Fan Wu, Ruicheng Xian, Yuhang Liu, Lydia Zakynthinou, Pritish Kamath, Chiyuan Zhang, David A. Forsyth
2025	J	`jnl`	How Unique is Whose Web Browser? The role of demographics in browser fingerprinting among US users. Proc. Priv. Enhancing Technol. Alex Berke, Badih Ghazi, Enrico Bacis, Pritish Kamath, Ravi Kumar, Robin Lassonde, Pasin Manurangsi, Umar Syed
2025	J	`jnl`	On the Differential Privacy and Interactivity of Privacy Sandbox Reports. Proc. Priv. Enhancing Technol. Badih Ghazi, Charlie Harrison, Arpana Hosabettu, Pritish Kamath, Alexander Knop, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Mariana Raykova, Vikas Sahu, Phillipp Schoppmann
2025	A*	`conf`	PREM: Privately Answering Statistical Queries with Relative Error. COLT Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Sushant Sachdeva
2025	J	`jnl`	PREM: Privately Answering Statistical Queries with Relative Error. CoRR Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Sushant Sachdeva
2025	J	`jnl`	Private Hyperparameter Tuning with Ex-Post Guarantee. CoRR Badih Ghazi, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang
2025	J	`jnl`	Scaling Embedding Layers in Language Models. CoRR Da Yu, Edith Cohen, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Daogao Liu, Chiyuan Zhang
2025	A*	`conf`	Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy. ICLR Yangsibo Huang, Daogao Liu, Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Milad Nasr, Amer Sinha, Chiyuan Zhang
2025	J	`jnl`	Urania: Differentially Private Insights into AI Use. CoRR Daogao Liu, Edith Cohen, Badih Ghazi, Peter Kairouz, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Adam Sealfon, Da Yu, Chiyuan Zhang
2025	J	`jnl`	VaultGemma: A Differentially Private Gemma Model. CoRR Amer Sinha, Thomas Mesnard, Ryan McKenna, Daogao Liu, Christopher A. Choquette-Choo, Yangsibo Huang, Da Yu, Georgios Kaissis, Zachary Charles, Ruibo Liu, Lynn Chua, Pritish Kamath, Pasin Manurangsi, Steve He, Chiyuan Zhang, Badih Ghazi, Borja de Balle Pigem, Prem Eruvbetine, Tris Warkentin, Armand Joulin, Ravi Kumar
2024	J	`jnl`	Balls-and-Bins Sampling for DP-SGD. CoRR Lynn Chua, Badih Ghazi, Charlie Harrison, Ethan Leeman, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2024	J	`jnl`	Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models. CoRR Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chulin Xie, Chiyuan Zhang
2024	A*	`conf`	Differentially Private Optimization with Sparse Gradients. NeurIPS Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2024	J	`jnl`	Differentially Private Optimization with Sparse Gradients. CoRR Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2024	A*	`conf`	How Private are DP-SGD Implementations? ICML Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2024	J	`jnl`	How Private is DP-SGD? CoRR Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2024	J	`jnl`	How Unique is Whose Web Browser? The role of demographics in browser fingerprinting among US users. CoRR Alex Berke, Enrico Bacis, Badih Ghazi, Pritish Kamath, Ravi Kumar, Robin Lassonde, Pasin Manurangsi, Umar Syed
2024	A*	`conf`	Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization. ICML Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon
2024	J	`jnl`	Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon
2024	A*	`conf`	LabelDP-Pro: Learning with Label Differential Privacy via Projections. ICLR Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang
2024	A*	`conf`	Learning Neural Networks with Sparse Activations. COLT Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath, Raghu Meka
2024	J	`jnl`	Learning Neural Networks with Sparse Activations. CoRR Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath, Raghu Meka
2024	J	`jnl`	Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning. CoRR Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Daogao Liu, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2024	J	`jnl`	On Computing Pairwise Statistics with Local Differential Privacy. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon
2024	A*	`conf`	On Convex Optimization with Semi-Sensitive Features. COLT Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
2024	J	`jnl`	On Convex Optimization with Semi-Sensitive Features. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
2024	J	`jnl`	On the Differential Privacy and Interactivity of Privacy Sandbox Reports. CoRR Badih Ghazi, Charlie Harrison, Arpana Hosabettu, Pritish Kamath, Alexander Knop, S. Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Vikas Sahu
2024	A*	`conf`	Scalable DP-SGD: Shuffling vs. Poisson Subsampling. NeurIPS Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2024	J	`jnl`	Scalable DP-SGD: Shuffling vs. Poisson Subsampling. CoRR Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2024	J	`jnl`	Summary Reports Optimization in the Privacy Sandbox Attribution Reporting API. Proc. Priv. Enhancing Technol. Hidayet Aksu, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon, Avinash V. Varadarajan
2024	—	`conf`	Training Differentially Private Ad Prediction Models With Semi-Sensitive Features. AdKDD@KDD 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
2024	J	`jnl`	Training Differentially Private Ad Prediction Models with Semi-Sensitive Features. CoRR 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
2024	J	`jnl`	Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy. CoRR Yangsibo Huang, Daogao Liu, Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Milad Nasr, Amer Sinha, Chiyuan Zhang
2023	A*	`conf`	On Computing Pairwise Statistics with Local Differential Privacy. NeurIPS Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon
2023	A*	`conf`	On Differentially Private Counting on Trees. ICALP Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Kewen Wu
2023	A*	`conf`	On User-Level Private Convex Optimization. ICML Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
2023	J	`jnl`	On User-Level Private Convex Optimization. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Raghu Meka, Pasin Manurangsi, Chiyuan Zhang
2023	A*	`conf`	Optimal Unbiased Randomizers for Regression with Label Differential Privacy. NeurIPS Ashwinkumar Badanidiyuru Varadaraja, Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang
2023	J	`jnl`	Optimal Unbiased Randomizers for Regression with Label Differential Privacy. CoRR Ashwinkumar Badanidiyuru, Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang
2023	—	`conf`	Optimizing Hierarchical Queries for the Attribution Reporting API. AdKDD@KDD Matthew Dawson, Badih Ghazi, Pritish Kamath, Kapil Kumar, Ravi Kumar, Bo Luan, Pasin Manurangsi, Nishanth Mundru, Harikesh Nair, Adam Sealfon, Shengyu Zhu
2023	J	`jnl`	Optimizing Hierarchical Queries for the Attribution Reporting API. CoRR Matthew Dawson, Badih Ghazi, Pritish Kamath, Kapil Kumar, Ravi Kumar, Bo Luan, Pasin Manurangsi, Nishanth Mundru, Harikesh Nair, Adam Sealfon, Shengyu Zhu
2023	—	`conf`	Private Ad Modeling with DP-SGD. AdKDD@KDD Carson Denison, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang
2023	A*	`conf`	Regression with Label Differential Privacy. ICLR Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang
2023	J	`jnl`	Separating Computational and Statistical Differential Privacy (Under Plausible Assumptions). CoRR Badih Ghazi, Rahul Ilango, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2023	A*	`conf`	Sparsity-Preserving Differentially Private Training of Large Embedding Models. NeurIPS Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2023	J	`jnl`	Sparsity-Preserving Differentially Private Training of Large Embedding Models. CoRR Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
2023	J	`jnl`	Summary Reports Optimization in the Privacy Sandbox Attribution Reporting API. CoRR Hidayet Aksu, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon, Avinash V. Varadarajan
2023	J	`jnl`	Supervised Bayesian specification inference from demonstrations. Int. J. Robotics Res. Ankit Shah, Pritish Kamath, Shen Li, Patrick L. Craven, Kevin J. Landers, Kevin Oden, Julie Shah
2023	A*	`conf`	Ticketed Learning-Unlearning Schemes. COLT Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang
2023	J	`jnl`	Ticketed Learning-Unlearning Schemes. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Ayush Sekhari, Chiyuan Zhang
2023	A*	`conf`	Towards Separating Computational and Statistical Differential Privacy. FOCS Badih Ghazi, Rahul Ilango, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2023	A*	`conf`	User-Level Differential Privacy With Few Examples Per User. NeurIPS Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
2023	J	`jnl`	User-Level Differential Privacy With Few Examples Per User. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Raghu Meka, Chiyuan Zhang
2022	A*	`conf`	Anonymized Histograms in Intermediate Privacy Models. NeurIPS Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2022	J	`jnl`	Anonymized Histograms in Intermediate Privacy Models. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2022	J	`jnl`	Circuits Resilient to Short-Circuit Errors. Electron. Colloquium Comput. Complex. Klim Efremenko, Bernhard Haeupler, Yael Kalai, Pritish Kamath, Gillat Kol, Nicolas Resch, Raghuvansh Saxena
2022	A*	`conf`	Circuits resilient to short-circuit errors. STOC Klim Efremenko, Bernhard Haeupler, Yael Tauman Kalai, Pritish Kamath, Gillat Kol, Nicolas Resch, Raghuvansh R. Saxena
2022	J	`jnl`	Connect the Dots: Tighter Discrete Approximations of Privacy Loss Distributions. CoRR Vadym Doroshenko, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2022	J	`jnl`	Connect the Dots: Tighter Discrete Approximations of Privacy Loss Distributions. Proc. Priv. Enhancing Technol. Vadym Doroshenko, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2022	A*	`conf`	Do More Negative Samples Necessarily Hurt In Contrastive Learning? ICML Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath
2022	J	`jnl`	Do More Negative Samples Necessarily Hurt in Contrastive Learning? CoRR Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath
2022	A*	`conf`	Faster Privacy Accounting via Evolving Discretization. ICML Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2022	J	`jnl`	Faster Privacy Accounting via Evolving Discretization. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2022	J	`jnl`	Limits on the Efficiency of (Ring) LWE-Based Non-interactive Key Exchange. J. Cryptol. Siyao Guo, Pritish Kamath, Alon Rosen, Katerina Sotiraki
2022	J	`jnl`	On Differentially Private Counting on Trees. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Kewen Wu
2022	J	`jnl`	Private Ad Modeling with DP-SGD. CoRR Carson Denison, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang
2022	A*	`conf`	Private Isotonic Regression. NeurIPS Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2022	J	`jnl`	Private Isotonic Regression. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
2022	J	`jnl`	Regression with Label Differential Privacy. CoRR Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Avinash V. Varadarajan, Chiyuan Zhang
2022	A*	`conf`	Understanding the Eluder Dimension. NeurIPS Gene Li, Pritish Kamath, Dylan J. Foster, Nati Srebro
2021	A	`conf`	Does Invariant Risk Minimization Capture Invariance? AISTATS Pritish Kamath, Akilesh Tangella, Danica J. Sutherland, Nathan Srebro
2021	J	`jnl`	Does Invariant Risk Minimization Capture Invariance? CoRR Pritish Kamath, Akilesh Tangella, Danica J. Sutherland, Nathan Srebro
2021	J	`jnl`	Eluder Dimension and Generalized Rank. CoRR Gene Li, Pritish Kamath, Dylan J. Foster, Nathan Srebro
2021	A*	`conf`	On the Power of Differentiable Learning versus PAC and SQ Learning. NeurIPS Emmanuel Abbe, Pritish Kamath, Eran Malach, Colin Sandon, Nathan Srebro
2021	J	`jnl`	On the Power of Differentiable Learning versus PAC and SQ Learning. CoRR Emmanuel Abbe, Pritish Kamath, Eran Malach, Colin Sandon, Nathan Srebro
2021	A*	`conf`	Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels. ICML Eran Malach, Pritish Kamath, Emmanuel Abbe, Nathan Srebro
2021	J	`jnl`	Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels. CoRR Eran Malach, Pritish Kamath, Emmanuel Abbe, Nathan Srebro
2021	J	`jnl`	Supervised Bayesian Specification Inference from Demonstrations. CoRR Ankit J. Shah, Pritish Kamath, Shen Li, Patrick L. Craven, Kevin J. Landers, Kevin Oden, Julie Shah
2020	A*	`conf`	Approximate is Good Enough: Probabilistic Variants of Dimensional and Margin Complexity. COLT Pritish Kamath, Omar Montasser, Nathan Srebro
2020	J	`jnl`	Approximate is Good Enough: Probabilistic Variants of Dimensional and Margin Complexity. CoRR Pritish Kamath, Omar Montasser, Nathan Srebro
2020	—	`conf`	Limits on the Efficiency of (Ring) LWE Based Non-interactive Key Exchange. Public Key Cryptography (1) Siyao Guo, Pritish Kamath, Alon Rosen, Katerina Sotiraki
2020	J	`jnl`	Limits on the Efficiency of (Ring) LWE based Non-Interactive Key Exchange. IACR Cryptol. ePrint Arch. Siyao Guo, Pritish Kamath, Alon Rosen, Katerina Sotiraki
2020	J	`jnl`	Monotone Circuit Lower Bounds from Resolution. Theory Comput. Ankit Garg, Mika Göös, Pritish Kamath, Dmitry Sokolov
2020	A	`conf`	On the Complexity of Modulo-q Arguments and the Chevalley - Warning Theorem. CCC Mika Göös, Pritish Kamath, Katerina Sotiraki, Manolis Zampetakis
2020	J	`jnl`	Optimality of Correlated Sampling Strategies. Theory Comput. Mohammad Bavarian, Badih Ghazi, Elad Haramaty, Pritish Kamath, Ronald L. Rivest, Madhu Sudan
2019	A	`conf`	Adventures in Monotone Complexity and TFNP. ITCS Mika Göös, Pritish Kamath, Robert Robere, Dmitry Sokolov
2019	J	`jnl`	Correction to: Query-to-Communication Lifting for P NP. Comput. Complex. Mika Göös, Pritish Kamath, Toniann Pitassi, Thomas Watson
2019	J	`jnl`	On the Complexity of Modulo-q Arguments and the Chevalley-Warning Theorem. CoRR Mika Göös, Pritish Kamath, Katerina Sotiraki, Manolis Zampetakis
2019	J	`jnl`	Query-to-Communication Lifting for P NP. Comput. Complex. Mika Göös, Pritish Kamath, Toniann Pitassi, Thomas Watson
2018	J	`jnl`	Adventures in Monotone Complexity and TFNP. Electron. Colloquium Comput. Complex. Mika Göös, Pritish Kamath, Robert Robere, Dmitry Sokolov
2018	A*	`conf`	Bayesian Inference of Temporal Task Specifications from Demonstrations. NeurIPS Ankit Shah, Pritish Kamath, Julie A. Shah, Shen Li
2018	A	`conf`	Dimension Reduction for Polynomials over Gaussian Space and Applications. CCC Badih Ghazi, Pritish Kamath, Prasad Raghavendra
2018	A*	`conf`	Monotone circuit lower bounds from resolution. STOC Ankit Garg, Mika Göös, Pritish Kamath, Dmitry Sokolov
2017	A	`conf`	Compression in a Distributed Setting. ITCS Badih Ghazi, Elad Haramaty, Pritish Kamath, Madhu Sudan
2017	J	`jnl`	Dimension Reduction for Polynomials over Gaussian Space and Applications. CoRR Badih Ghazi, Pritish Kamath, Prasad Raghavendra
2017	J	`jnl`	Dimension Reduction for Polynomials over Gaussian Space and Applications. Electron. Colloquium Comput. Complex. Badih Ghazi, Pritish Kamath, Prasad Raghavendra
2017	J	`jnl`	Improved Bounds for Universal One-Bit Compressive Sensing. CoRR Jayadev Acharya, Arnab Bhattacharyya, Pritish Kamath
2017	B	`conf`	Improved bounds for universal one-bit compressive sensing. ISIT Jayadev Acharya, Arnab Bhattacharyya, Pritish Kamath
2017	J	`jnl`	Monotone Circuit Lower Bounds from Resolution. Electron. Colloquium Comput. Complex. Ankit Garg, Mika Göös, Pritish Kamath, Dmitry Sokolov
2017	A	`conf`	Query-to-Communication Lifting for P^NP. CCC Mika Göös, Pritish Kamath, Toniann Pitassi, Thomas Watson
2017	J	`jnl`	Query-to-Communication Lifting for P^NP. Electron. Colloquium Comput. Complex. Mika Göös, Pritish Kamath, Toniann Pitassi, Thomas Watson
2017	J	`jnl`	Unexpected power of low-depth arithmetic circuits. Commun. ACM Ankit Gupta, Pritish Kamath, Neeraj Kayal, Ramprasad Saptharishi
2016	J	`jnl`	Arithmetic Circuits: A Chasm at Depth 3. SIAM J. Comput. Ankit Gupta, Pritish Kamath, Neeraj Kayal, Ramprasad Saptharishi
2016	A*	`conf`	Communication Complexity of Permutation-Invariant Functions. SODA Badih Ghazi, Pritish Kamath, Madhu Sudan
2016	J	`jnl`	Decidability of Non-Interactive Simulation of Joint Distributions. CoRR Badih Ghazi, Pritish Kamath, Madhu Sudan
2016	J	`jnl`	Decidability of Non-Interactive Simulation of Joint Distributions. Electron. Colloquium Comput. Complex. Badih Ghazi, Pritish Kamath, Madhu Sudan
2016	A*	`conf`	Decidability of Non-interactive Simulation of Joint Distributions. FOCS Badih Ghazi, Pritish Kamath, Madhu Sudan
2016	J	`jnl`	The Optimality of Correlated Sampling. CoRR Mohammad Bavarian, Badih Ghazi, Elad Haramaty, Pritish Kamath, Ronald L. Rivest, Madhu Sudan
2016	J	`jnl`	The Optimality of Correlated Sampling. Electron. Colloquium Comput. Complex. Mohammad Bavarian, Badih Ghazi, Elad Haramaty, Pritish Kamath, Ronald L. Rivest, Madhu Sudan
2015	J	`jnl`	Communication Complexity of Permutation-Invariant Functions. CoRR Badih Ghazi, Pritish Kamath, Madhu Sudan
2015	J	`jnl`	Communication Complexity of Permutation-Invariant Functions. Electron. Colloquium Comput. Complex. Badih Ghazi, Pritish Kamath, Madhu Sudan
2015	—	`conf`	Communication with Partial Noiseless Feedback. APPROX-RANDOM Bernhard Haeupler, Pritish Kamath, Ameya Velingker
2014	J	`jnl`	Approaching the Chasm at Depth Four. J. ACM Ankit Gupta, Pritish Kamath, Neeraj Kayal, Ramprasad Saptharishi
2013	A	`conf`	Approaching the Chasm at Depth Four. CCC Ankit Gupta, Pritish Kamath, Neeraj Kayal, Ramprasad Saptharishi
2013	A*	`conf`	Arithmetic Circuits: A Chasm at Depth Three. FOCS Ankit Gupta, Pritish Kamath, Neeraj Kayal, Ramprasad Saptharishi
2013	J	`jnl`	Arithmetic circuits: A chasm at depth three. Electron. Colloquium Comput. Complex. Ankit Gupta, Pritish Kamath, Neeraj Kayal, Ramprasad Saptharishi
2012	J	`jnl`	An exponential lower bound for homogeneous depth four arithmetic circuits with bounded bottom fanin. Electron. Colloquium Comput. Complex. Ankit Gupta, Pritish Kamath, Neeraj Kayal, Ramprasad Saptharishi
2012	J	`jnl`	Faster Algorithms for Alternating Refinement Relations CoRR Krishnendu Chatterjee, Siddhesh Chaubal, Pritish Kamath
2012	B	`conf`	Faster Algorithms for Alternating Refinement Relations. CSL Krishnendu Chatterjee, Siddhesh Chaubal, Pritish Kamath
2012	J	`jnl`	Preservation under Substructures modulo Bounded Cores CoRR Abhisekh Sankaran, Bharat Adsul, Vivek Madan, Pritish Kamath, Supratik Chakraborty
2012	C	`conf`	Preservation under Substructures modulo Bounded Cores. WoLLIC Abhisekh Sankaran, Bharat Adsul, Vivek Madan, Pritish Kamath, Supratik Chakraborty
2011	C	`conf`	Using Dominances for Solving the Protein Family Identification Problem. WABI Noël Malod-Dognin, Mathilde Le Boudic-Jamin, Pritish Kamath, Rumen Andonov