On the Emergence of Thinking in LLMs I: Searching for the Right Intuition
Guanghao Ye, Khiem Duc Pham, Xinzhi Zhang, Sivakanth Gopi, Baolin Peng, Beibin Li, Janardhan (Jana) Kulkarni, Huseyin Inan
February 2025
Sivakanth Gopi
Chercheur principal
Papiers de Collaboration
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A Geometric Perspective on the Injective Norm of Sums of Random Tensors
Afonso S. Bandeira, Sivakanth Gopi, Haotian Jiang, Kevin Lucca, Thomas Rothvoss
STOC 2025 | January 2025
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DiscQuant: A Quantization Method for Neural Networks Inspired by Discrepancy Theory
Jerry Chee, Arturs Backurs, Rainie Heck, Li Zhang, Janardhan (Jana) Kulkarni, Thomas Rothvoss, Sivakanth Gopi
COLT 2025 | January 2025
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Ranking with Multiple Objectives
Nikhil Devanur, Sivakanth Gopi
October 2024
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Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin
ICML 2024 | July 2024
Spotlight
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Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Harsha Nori, Sergey Yekhanin
ICLR 2024 | May 2024
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Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
Xinyu Tang, Richard Shin, Huseyin Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Robert Sim
ICLR 2024 | May 2024
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Rigidity matroids and linear algebraic matroids with applications to matrix completion and tensor codes
Joshua Brakensiek, Manik Dhar, Jiyang Gao, Sivakanth Gopi, Matt Larson
May 2024
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Selective Pre-training for Private Fine-tuning
Da Yu, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang
TMLR | May 2024
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Training Private and Efficient Language Models with Synthetic Data from LLMs
Da Yu, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Janardhan (Jana) Kulkarni, Zinan Lin, Chulin Xie, Huishuai Zhang, Wanrong Zhang
NeurIPS 2023 SoLaR Workshop | December 2023
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AG codes achieve list decoding capacity over contant-sized fields
Joshua Brakensiek, Manik Dhar, Sivakanth Gopi, Zihan Zhang
STOC 2024 | October 2023
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Generalized GM-MDS: Polynomial Codes are Higher Order MDS
Joshua Brakensiek, Manik Dhar, Sivakanth Gopi
STOC 2024 | October 2023
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Textbooks Are All You Need
Suriya Gunasekar, Yi Zhang, Jyoti Aneja, Caio Cesar, Teodoro Mendes, Allie Del Giorno, Sivakanth Gopi, Mojan Javaheripi, Piero Kauffmann, Gustavo de Rosa, Olli Saarikivi, Adil Salim, Shital Shah, Harkirat Singh Behl, Xin Wang, Sébastien Bubeck, Ronen Eldan, Adam Tauman Kalai, Yin Tat Lee, Yuanzhi Li
June 2023
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Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler
Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Rouqi Shen, Kevin Tian
COLT 2023 | February 2023
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A construction of Maximally Recoverable LRCs for small number of local groups
Manik Dhar, Sivakanth Gopi
ISIT 2023 | December 2022
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Improved Field Size Bounds for Higher Order MDS Codes
Joshua Brakensiek, Manik Dhar, Sivakanth Gopi
ISIT 2023 | December 2022
-
Private Convex Optimization in General Norms
Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Rouqi Shen, Kevin Tian
SODA 2023 | July 2022
-
Generic Reed-Solomon codes achieve list-decoding capacity
Joshua Brakensiek, Sivakanth Gopi, Visu Makam
STOC 2023 | June 2022
-
Differentially private fine-tuning of language models
Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Gautam Kamath, Janardhan (Jana) Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang
ICLR 2022 | April 2022
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Private Convex Optimization via Exponential Mechanism
Sivakanth Gopi, Yin Tat Lee, Daogao Liu
COLT 2022 | March 2022
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Differentially private n-gram extraction
Kunho Kim, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Sergey Yekhanin
NeurIPS 2021 | December 2021
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Lower Bounds for Maximally Recoverable Tensor Code and Higher Order MDS Codes
Joshua Brakensiek, Sivakanth Gopi, Visu Makam
IEEE Transactions on Information Theory | July 2021
-
Trellis BMA: coded trace reconstruction on IDS channels for DNA storage
Sundara Rajan Srinivasavaradhan, Sivakanth Gopi, Henry Pfister, Sergey Yekhanin
International Symposium on Information Theory (ISIT) | July 2021
-
Numerical Composition of Differential Privacy
Sivakanth Gopi, Yin Tat Lee, Lukas Wutschitz
NeurIPS 2021 | June 2021
Spotlight at NeurIPS 2021.
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Fast and Memory Efficient Differentially Private-SGD via JL Projections
Zhiqi Bu, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Yin Tat Lee, Judy Hanwen Shen, Uthaipon Tantipongpipat
NeurIPS 2021 | February 2021
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Improved Maximally Recoverable LRCs using Skew Polynomials
Sivakanth Gopi, Venkatesan Guruswami
IEEE Transactions on Information Theory | December 2020
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Differentially Private Set Union
Sivakanth Gopi, Pankaj Gulhane, Janardhan (Jana) Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin
International Conference on Machine Learning 2020 | July 2020
Contributed talk at TPDP 2020. Also appeared in the Journal of Privacy and Confidentiality (JPC).
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Locally Private Hypothesis Selection
Sivakanth Gopi, Gautam Kamath, Janardhan (Jana) Kulkarni, Aleksandar Nikolov, Zhiwei Steven Wu, Huanyu Zhang
Conference on Learning Theory (COLT) 2020 | July 2020
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CSPs with Global Modular Constraints: Algorithms and Hardness via Polynomial Representations
Joshua Brakensiek, Sivakanth Gopi, Venkatesan Guruswami
Symposium on Theory of Computing (STOC) 2019 | February 2019
-
Maximally Recoverable LRCs: A field size lower bound and constructions for few heavy parities
Sivakanth Gopi, Venkatesan Guruswami, Sergey Yekhanin
Symposium on Discrete Algorithms (SODA) 2019 | January 2019
-
-
-
Gaussian width bounds with applications to arithmetic progressions in random settings
Jop Briet, Sivakanth Gopi
International Mathematics Research Notices (IMRN) | October 2018
-
Spanoids – an abstraction of spanning structures, and a barrier for LCCs
Zeev Dvir, Sivakanth Gopi, A. Wigderson
SIAM J. Comput. | September 2018, Vol 49: pp. 465-496
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Locality in Coding Theory
June 2018
Thèse de doctorat : Princeton University | June 2018
-
-
-
Locally Testable and Locally Correctable Codes approaching the Gilbert-Varshamov Bound
Sivakanth Gopi, Swastik Kopparty, R. Oliveira, Noga Ron-Zewi, Shubhangi Saraf
IEEE Transactions on Information Theory | January 2017, Vol 64(8): pp. 5813-5831
Conference version appeared in SODA 2017.
-
Lower bounds for 2-query LCCs over large alphabet
Sivakanth Gopi, Arnab Bhattacharyya, Avishay Tal
RANDOM 2017 | January 2017
-
Outlaw distributions and locally decodable codes
Jop Briet, Zeev Dvir, Sivakanth Gopi
Innovations in Theoretical Computer Science (ITCS) 2017 | January 2017
-
-
-
2-Server PIR with sub-polynomial communication
Zeev Dvir, Sivakanth Gopi
Journal of the ACM (JACM) | November 2016, Vol 63(4)
Best Paper Award in STOC 2015
Conference version appeared in STOC 2015 where it was a cowinner of the best paper award.
-
Competitive analysis of the top-K ranking problem
Xi Chen, Sivakanth Gopi, Jieming Mao, Jon Schneider
IEEE Transactions on Information Theory | May 2016, Vol abs/1605.03933(64)
Conference version appeared in SODA 2017.
-
-
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Lower Bounds for Constant Query Affine-Invariant LCCs and LTCs
Arnab Bhattacharyya, Sivakanth Gopi
ACM Transactions on Computation Theory (TOCT) | November 2015, Vol 9(2): pp. 1-17
Conference version appeared in CCC 2016.
-
-
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On the Number of Rich Lines in Truly High Dimensional Sets
Zeev Dvir, Sivakanth Gopi
Symposium on Computational Geometry (SoCG) 2015 | December 2014
-
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One-bit Compressed Sensing: Provable Support and Vector Recovery
Sivakanth Gopi, Praneeth Netrapalli, Prateek Jain, Aditya Nori
International Conference on Machine Learning (ICML) | June 2013
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Stability of Linear Threshold Functions
May 2013
Undergraduate Thesis, IIT Bombay
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Synthesis from incompatible specifications
Pavol Cerny, Sivakanth Gopi, Thomas A. Henzinger, Arjun Radhakrishna, Nishant Totla
2012 Embedded Software | October 2012
Nominated for the Best Paper award
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On the Emergence of Thinking in LLMs I: Searching for the Right Intuition
Guanghao Ye, Khiem Duc Pham, Xinzhi Zhang, Sivakanth Gopi, Baolin Peng, Beibin Li, Janardhan (Jana) Kulkarni, Huseyin Inan
February 2025
-
DiscQuant: A Quantization Method for Neural Networks Inspired by Discrepancy Theory
Jerry Chee, Arturs Backurs, Rainie Heck, Li Zhang, Janardhan (Jana) Kulkarni, Thomas Rothvoss, Sivakanth Gopi
COLT 2025 | January 2025
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Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin
ICML 2024 | July 2024
Spotlight
-
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
Xinyu Tang, Richard Shin, Huseyin Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Robert Sim
ICLR 2024 | May 2024
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Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Harsha Nori, Sergey Yekhanin
ICLR 2024 | May 2024
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Training Private and Efficient Language Models with Synthetic Data from LLMs
Da Yu, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Janardhan (Jana) Kulkarni, Zinan Lin, Chulin Xie, Huishuai Zhang, Wanrong Zhang
NeurIPS 2023 SoLaR Workshop | December 2023
-
Textbooks Are All You Need
Suriya Gunasekar, Yi Zhang, Jyoti Aneja, Caio Cesar, Teodoro Mendes, Allie Del Giorno, Sivakanth Gopi, Mojan Javaheripi, Piero Kauffmann, Gustavo de Rosa, Olli Saarikivi, Adil Salim, Shital Shah, Harkirat Singh Behl, Xin Wang, Sébastien Bubeck, Ronen Eldan, Adam Tauman Kalai, Yin Tat Lee, Yuanzhi Li
June 2023
-
One-bit Compressed Sensing: Provable Support and Vector Recovery
Sivakanth Gopi, Praneeth Netrapalli, Prateek Jain, Aditya Nori
International Conference on Machine Learning (ICML) | June 2013
-
-
-
DiscQuant: A Quantization Method for Neural Networks Inspired by Discrepancy Theory
Jerry Chee, Arturs Backurs, Rainie Heck, Li Zhang, Janardhan (Jana) Kulkarni, Thomas Rothvoss, Sivakanth Gopi
COLT 2025 | January 2025
-
Ranking with Multiple Objectives
Nikhil Devanur, Sivakanth Gopi
October 2024
-
Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin
ICML 2024 | July 2024
Spotlight
-
Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Harsha Nori, Sergey Yekhanin
ICLR 2024 | May 2024
-
Selective Pre-training for Private Fine-tuning
Da Yu, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang
TMLR | May 2024
-
AG codes achieve list decoding capacity over contant-sized fields
Joshua Brakensiek, Manik Dhar, Sivakanth Gopi, Zihan Zhang
STOC 2024 | October 2023
-
Generalized GM-MDS: Polynomial Codes are Higher Order MDS
Joshua Brakensiek, Manik Dhar, Sivakanth Gopi
STOC 2024 | October 2023
-
Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler
Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Rouqi Shen, Kevin Tian
COLT 2023 | February 2023
-
A construction of Maximally Recoverable LRCs for small number of local groups
Manik Dhar, Sivakanth Gopi
ISIT 2023 | December 2022
-
Improved Field Size Bounds for Higher Order MDS Codes
Joshua Brakensiek, Manik Dhar, Sivakanth Gopi
ISIT 2023 | December 2022
-
Private Convex Optimization in General Norms
Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Rouqi Shen, Kevin Tian
SODA 2023 | July 2022
-
Generic Reed-Solomon codes achieve list-decoding capacity
Joshua Brakensiek, Sivakanth Gopi, Visu Makam
STOC 2023 | June 2022
-
Differentially private fine-tuning of language models
Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Gautam Kamath, Janardhan (Jana) Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang
ICLR 2022 | April 2022
-
Private Convex Optimization via Exponential Mechanism
Sivakanth Gopi, Yin Tat Lee, Daogao Liu
COLT 2022 | March 2022
-
Differentially private n-gram extraction
Kunho Kim, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Sergey Yekhanin
NeurIPS 2021 | December 2021
-
Lower Bounds for Maximally Recoverable Tensor Code and Higher Order MDS Codes
Joshua Brakensiek, Sivakanth Gopi, Visu Makam
IEEE Transactions on Information Theory | July 2021
-
Trellis BMA: coded trace reconstruction on IDS channels for DNA storage
Sundara Rajan Srinivasavaradhan, Sivakanth Gopi, Henry Pfister, Sergey Yekhanin
International Symposium on Information Theory (ISIT) | July 2021
-
Numerical Composition of Differential Privacy
Sivakanth Gopi, Yin Tat Lee, Lukas Wutschitz
NeurIPS 2021 | June 2021
Spotlight at NeurIPS 2021.
-
Fast and Memory Efficient Differentially Private-SGD via JL Projections
Zhiqi Bu, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Yin Tat Lee, Judy Hanwen Shen, Uthaipon Tantipongpipat
NeurIPS 2021 | February 2021
-
Improved Maximally Recoverable LRCs using Skew Polynomials
Sivakanth Gopi, Venkatesan Guruswami
IEEE Transactions on Information Theory | December 2020
-
Locally Private Hypothesis Selection
Sivakanth Gopi, Gautam Kamath, Janardhan (Jana) Kulkarni, Aleksandar Nikolov, Zhiwei Steven Wu, Huanyu Zhang
Conference on Learning Theory (COLT) 2020 | July 2020
-
Differentially Private Set Union
Sivakanth Gopi, Pankaj Gulhane, Janardhan (Jana) Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin
International Conference on Machine Learning 2020 | July 2020
Contributed talk at TPDP 2020. Also appeared in the Journal of Privacy and Confidentiality (JPC).
-
CSPs with Global Modular Constraints: Algorithms and Hardness via Polynomial Representations
Joshua Brakensiek, Sivakanth Gopi, Venkatesan Guruswami
Symposium on Theory of Computing (STOC) 2019 | February 2019
-
Maximally Recoverable LRCs: A field size lower bound and constructions for few heavy parities
Sivakanth Gopi, Venkatesan Guruswami, Sergey Yekhanin
Symposium on Discrete Algorithms (SODA) 2019 | January 2019
-
Locality in Coding Theory
June 2018
Thèse de doctorat : Princeton University | June 2018
-
Locally Testable and Locally Correctable Codes approaching the Gilbert-Varshamov Bound
Sivakanth Gopi, Swastik Kopparty, R. Oliveira, Noga Ron-Zewi, Shubhangi Saraf
IEEE Transactions on Information Theory | January 2017, Vol 64(8): pp. 5813-5831
Conference version appeared in SODA 2017.
-
Competitive analysis of the top-K ranking problem
Xi Chen, Sivakanth Gopi, Jieming Mao, Jon Schneider
IEEE Transactions on Information Theory | May 2016, Vol abs/1605.03933(64)
Conference version appeared in SODA 2017.
-
On the Number of Rich Lines in Truly High Dimensional Sets
Zeev Dvir, Sivakanth Gopi
Symposium on Computational Geometry (SoCG) 2015 | December 2014
-
One-bit Compressed Sensing: Provable Support and Vector Recovery
Sivakanth Gopi, Praneeth Netrapalli, Prateek Jain, Aditya Nori
International Conference on Machine Learning (ICML) | June 2013
-
Stability of Linear Threshold Functions
May 2013
Undergraduate Thesis, IIT Bombay
-
-
-
A Geometric Perspective on the Injective Norm of Sums of Random Tensors
Afonso S. Bandeira, Sivakanth Gopi, Haotian Jiang, Kevin Lucca, Thomas Rothvoss
STOC 2025 | January 2025
-
DiscQuant: A Quantization Method for Neural Networks Inspired by Discrepancy Theory
Jerry Chee, Arturs Backurs, Rainie Heck, Li Zhang, Janardhan (Jana) Kulkarni, Thomas Rothvoss, Sivakanth Gopi
COLT 2025 | January 2025
-
Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin
ICML 2024 | July 2024
Spotlight
-
Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Harsha Nori, Sergey Yekhanin
ICLR 2024 | May 2024
-
Rigidity matroids and linear algebraic matroids with applications to matrix completion and tensor codes
Joshua Brakensiek, Manik Dhar, Jiyang Gao, Sivakanth Gopi, Matt Larson
May 2024
-
AG codes achieve list decoding capacity over contant-sized fields
Joshua Brakensiek, Manik Dhar, Sivakanth Gopi, Zihan Zhang
STOC 2024 | October 2023
-
Generalized GM-MDS: Polynomial Codes are Higher Order MDS
Joshua Brakensiek, Manik Dhar, Sivakanth Gopi
STOC 2024 | October 2023
-
Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler
Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Rouqi Shen, Kevin Tian
COLT 2023 | February 2023
-
A construction of Maximally Recoverable LRCs for small number of local groups
Manik Dhar, Sivakanth Gopi
ISIT 2023 | December 2022
-
Improved Field Size Bounds for Higher Order MDS Codes
Joshua Brakensiek, Manik Dhar, Sivakanth Gopi
ISIT 2023 | December 2022
-
Private Convex Optimization in General Norms
Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Rouqi Shen, Kevin Tian
SODA 2023 | July 2022
-
Generic Reed-Solomon codes achieve list-decoding capacity
Joshua Brakensiek, Sivakanth Gopi, Visu Makam
STOC 2023 | June 2022
-
Private Convex Optimization via Exponential Mechanism
Sivakanth Gopi, Yin Tat Lee, Daogao Liu
COLT 2022 | March 2022
-
Lower Bounds for Maximally Recoverable Tensor Code and Higher Order MDS Codes
Joshua Brakensiek, Sivakanth Gopi, Visu Makam
IEEE Transactions on Information Theory | July 2021
-
Trellis BMA: coded trace reconstruction on IDS channels for DNA storage
Sundara Rajan Srinivasavaradhan, Sivakanth Gopi, Henry Pfister, Sergey Yekhanin
International Symposium on Information Theory (ISIT) | July 2021
-
Numerical Composition of Differential Privacy
Sivakanth Gopi, Yin Tat Lee, Lukas Wutschitz
NeurIPS 2021 | June 2021
Spotlight at NeurIPS 2021.
-
Fast and Memory Efficient Differentially Private-SGD via JL Projections
Zhiqi Bu, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Yin Tat Lee, Judy Hanwen Shen, Uthaipon Tantipongpipat
NeurIPS 2021 | February 2021
-
Improved Maximally Recoverable LRCs using Skew Polynomials
Sivakanth Gopi, Venkatesan Guruswami
IEEE Transactions on Information Theory | December 2020
-
Locally Private Hypothesis Selection
Sivakanth Gopi, Gautam Kamath, Janardhan (Jana) Kulkarni, Aleksandar Nikolov, Zhiwei Steven Wu, Huanyu Zhang
Conference on Learning Theory (COLT) 2020 | July 2020
-
Differentially Private Set Union
Sivakanth Gopi, Pankaj Gulhane, Janardhan (Jana) Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin
International Conference on Machine Learning 2020 | July 2020
Contributed talk at TPDP 2020. Also appeared in the Journal of Privacy and Confidentiality (JPC).
-
CSPs with Global Modular Constraints: Algorithms and Hardness via Polynomial Representations
Joshua Brakensiek, Sivakanth Gopi, Venkatesan Guruswami
Symposium on Theory of Computing (STOC) 2019 | February 2019
-
Maximally Recoverable LRCs: A field size lower bound and constructions for few heavy parities
Sivakanth Gopi, Venkatesan Guruswami, Sergey Yekhanin
Symposium on Discrete Algorithms (SODA) 2019 | January 2019
-
Gaussian width bounds with applications to arithmetic progressions in random settings
Jop Briet, Sivakanth Gopi
International Mathematics Research Notices (IMRN) | October 2018
-
Spanoids – an abstraction of spanning structures, and a barrier for LCCs
Zeev Dvir, Sivakanth Gopi, A. Wigderson
SIAM J. Comput. | September 2018, Vol 49: pp. 465-496
-
Locality in Coding Theory
June 2018
Thèse de doctorat : Princeton University | June 2018
-
Locally Testable and Locally Correctable Codes approaching the Gilbert-Varshamov Bound
Sivakanth Gopi, Swastik Kopparty, R. Oliveira, Noga Ron-Zewi, Shubhangi Saraf
IEEE Transactions on Information Theory | January 2017, Vol 64(8): pp. 5813-5831
Conference version appeared in SODA 2017.
-
Outlaw distributions and locally decodable codes
Jop Briet, Zeev Dvir, Sivakanth Gopi
Innovations in Theoretical Computer Science (ITCS) 2017 | January 2017
-
Lower bounds for 2-query LCCs over large alphabet
Sivakanth Gopi, Arnab Bhattacharyya, Avishay Tal
RANDOM 2017 | January 2017
-
2-Server PIR with sub-polynomial communication
Zeev Dvir, Sivakanth Gopi
Journal of the ACM (JACM) | November 2016, Vol 63(4)
Best Paper Award in STOC 2015
Conference version appeared in STOC 2015 where it was a cowinner of the best paper award.
-
Lower Bounds for Constant Query Affine-Invariant LCCs and LTCs
Arnab Bhattacharyya, Sivakanth Gopi
ACM Transactions on Computation Theory (TOCT) | November 2015, Vol 9(2): pp. 1-17
Conference version appeared in CCC 2016.
-
On the Number of Rich Lines in Truly High Dimensional Sets
Zeev Dvir, Sivakanth Gopi
Symposium on Computational Geometry (SoCG) 2015 | December 2014
-
Stability of Linear Threshold Functions
May 2013
Undergraduate Thesis, IIT Bombay
-
-
-
Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin
ICML 2024 | July 2024
Spotlight
-
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
Xinyu Tang, Richard Shin, Huseyin Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Robert Sim
ICLR 2024 | May 2024
-
Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Harsha Nori, Sergey Yekhanin
ICLR 2024 | May 2024
-
Selective Pre-training for Private Fine-tuning
Da Yu, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang
TMLR | May 2024
-
Private Convex Optimization in General Norms
Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Rouqi Shen, Kevin Tian
SODA 2023 | July 2022
-
Private Convex Optimization via Exponential Mechanism
Sivakanth Gopi, Yin Tat Lee, Daogao Liu
COLT 2022 | March 2022
-
Numerical Composition of Differential Privacy
Sivakanth Gopi, Yin Tat Lee, Lukas Wutschitz
NeurIPS 2021 | June 2021
Spotlight at NeurIPS 2021.
-
Fast and Memory Efficient Differentially Private-SGD via JL Projections
Zhiqi Bu, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Yin Tat Lee, Judy Hanwen Shen, Uthaipon Tantipongpipat
NeurIPS 2021 | February 2021
-
Locally Private Hypothesis Selection
Sivakanth Gopi, Gautam Kamath, Janardhan (Jana) Kulkarni, Aleksandar Nikolov, Zhiwei Steven Wu, Huanyu Zhang
Conference on Learning Theory (COLT) 2020 | July 2020
-
Differentially Private Set Union
Sivakanth Gopi, Pankaj Gulhane, Janardhan (Jana) Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin
International Conference on Machine Learning 2020 | July 2020
Contributed talk at TPDP 2020. Also appeared in the Journal of Privacy and Confidentiality (JPC).
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2-Server PIR with sub-polynomial communication
Zeev Dvir, Sivakanth Gopi
Journal of the ACM (JACM) | November 2016, Vol 63(4)
Best Paper Award in STOC 2015
Conference version appeared in STOC 2015 where it was a cowinner of the best paper award.
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Synthesis from incompatible specifications
Pavol Cerny, Sivakanth Gopi, Thomas A. Henzinger, Arjun Radhakrishna, Nishant Totla
2012 Embedded Software | October 2012
Nominated for the Best Paper award
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On the Emergence of Thinking in LLMs I: Searching for the Right Intuition
Guanghao Ye, Khiem Duc Pham, Xinzhi Zhang, Sivakanth Gopi, Baolin Peng, Beibin Li, Janardhan (Jana) Kulkarni, Huseyin Inan
February 2025
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Ranking with Multiple Objectives
Nikhil Devanur, Sivakanth Gopi
October 2024
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Rigidity matroids and linear algebraic matroids with applications to matrix completion and tensor codes
Joshua Brakensiek, Manik Dhar, Jiyang Gao, Sivakanth Gopi, Matt Larson
May 2024
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A Geometric Perspective on the Injective Norm of Sums of Random Tensors
Afonso S. Bandeira, Sivakanth Gopi, Haotian Jiang, Kevin Lucca, Thomas Rothvoss
STOC 2025 | January 2025
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DiscQuant: A Quantization Method for Neural Networks Inspired by Discrepancy Theory
Jerry Chee, Arturs Backurs, Rainie Heck, Li Zhang, Janardhan (Jana) Kulkarni, Thomas Rothvoss, Sivakanth Gopi
COLT 2025 | January 2025
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Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin
ICML 2024 | July 2024
Spotlight
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Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
Xinyu Tang, Richard Shin, Huseyin Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Robert Sim
ICLR 2024 | May 2024
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Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Harsha Nori, Sergey Yekhanin
ICLR 2024 | May 2024
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Training Private and Efficient Language Models with Synthetic Data from LLMs
Da Yu, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Janardhan (Jana) Kulkarni, Zinan Lin, Chulin Xie, Huishuai Zhang, Wanrong Zhang
NeurIPS 2023 SoLaR Workshop | December 2023
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AG codes achieve list decoding capacity over contant-sized fields
Joshua Brakensiek, Manik Dhar, Sivakanth Gopi, Zihan Zhang
STOC 2024 | October 2023
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Generalized GM-MDS: Polynomial Codes are Higher Order MDS
Joshua Brakensiek, Manik Dhar, Sivakanth Gopi
STOC 2024 | October 2023
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Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler
Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Rouqi Shen, Kevin Tian
COLT 2023 | February 2023
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A construction of Maximally Recoverable LRCs for small number of local groups
Manik Dhar, Sivakanth Gopi
ISIT 2023 | December 2022
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Improved Field Size Bounds for Higher Order MDS Codes
Joshua Brakensiek, Manik Dhar, Sivakanth Gopi
ISIT 2023 | December 2022
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Private Convex Optimization in General Norms
Sivakanth Gopi, Yin Tat Lee, Daogao Liu, Rouqi Shen, Kevin Tian
SODA 2023 | July 2022
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Generic Reed-Solomon codes achieve list-decoding capacity
Joshua Brakensiek, Sivakanth Gopi, Visu Makam
STOC 2023 | June 2022
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Differentially private fine-tuning of language models
Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Gautam Kamath, Janardhan (Jana) Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang
ICLR 2022 | April 2022
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Private Convex Optimization via Exponential Mechanism
Sivakanth Gopi, Yin Tat Lee, Daogao Liu
COLT 2022 | March 2022
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Differentially private n-gram extraction
Kunho Kim, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Sergey Yekhanin
NeurIPS 2021 | December 2021
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Trellis BMA: coded trace reconstruction on IDS channels for DNA storage
Sundara Rajan Srinivasavaradhan, Sivakanth Gopi, Henry Pfister, Sergey Yekhanin
International Symposium on Information Theory (ISIT) | July 2021
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Numerical Composition of Differential Privacy
Sivakanth Gopi, Yin Tat Lee, Lukas Wutschitz
NeurIPS 2021 | June 2021
Spotlight at NeurIPS 2021.
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Fast and Memory Efficient Differentially Private-SGD via JL Projections
Zhiqi Bu, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Yin Tat Lee, Judy Hanwen Shen, Uthaipon Tantipongpipat
NeurIPS 2021 | February 2021
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Locally Private Hypothesis Selection
Sivakanth Gopi, Gautam Kamath, Janardhan (Jana) Kulkarni, Aleksandar Nikolov, Zhiwei Steven Wu, Huanyu Zhang
Conference on Learning Theory (COLT) 2020 | July 2020
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Differentially Private Set Union
Sivakanth Gopi, Pankaj Gulhane, Janardhan (Jana) Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin
International Conference on Machine Learning 2020 | July 2020
Contributed talk at TPDP 2020. Also appeared in the Journal of Privacy and Confidentiality (JPC).
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CSPs with Global Modular Constraints: Algorithms and Hardness via Polynomial Representations
Joshua Brakensiek, Sivakanth Gopi, Venkatesan Guruswami
Symposium on Theory of Computing (STOC) 2019 | February 2019
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Maximally Recoverable LRCs: A field size lower bound and constructions for few heavy parities
Sivakanth Gopi, Venkatesan Guruswami, Sergey Yekhanin
Symposium on Discrete Algorithms (SODA) 2019 | January 2019
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Outlaw distributions and locally decodable codes
Jop Briet, Zeev Dvir, Sivakanth Gopi
Innovations in Theoretical Computer Science (ITCS) 2017 | January 2017
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Lower bounds for 2-query LCCs over large alphabet
Sivakanth Gopi, Arnab Bhattacharyya, Avishay Tal
RANDOM 2017 | January 2017
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On the Number of Rich Lines in Truly High Dimensional Sets
Zeev Dvir, Sivakanth Gopi
Symposium on Computational Geometry (SoCG) 2015 | December 2014
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One-bit Compressed Sensing: Provable Support and Vector Recovery
Sivakanth Gopi, Praneeth Netrapalli, Prateek Jain, Aditya Nori
International Conference on Machine Learning (ICML) | June 2013
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Synthesis from incompatible specifications
Pavol Cerny, Sivakanth Gopi, Thomas A. Henzinger, Arjun Radhakrishna, Nishant Totla
2012 Embedded Software | October 2012
Nominated for the Best Paper award
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Textbooks Are All You Need
Suriya Gunasekar, Yi Zhang, Jyoti Aneja, Caio Cesar, Teodoro Mendes, Allie Del Giorno, Sivakanth Gopi, Mojan Javaheripi, Piero Kauffmann, Gustavo de Rosa, Olli Saarikivi, Adil Salim, Shital Shah, Harkirat Singh Behl, Xin Wang, Sébastien Bubeck, Ronen Eldan, Adam Tauman Kalai, Yin Tat Lee, Yuanzhi Li
June 2023
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Stability of Linear Threshold Functions
May 2013
Undergraduate Thesis, IIT Bombay
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Selective Pre-training for Private Fine-tuning
Da Yu, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang
TMLR | May 2024
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Lower Bounds for Maximally Recoverable Tensor Code and Higher Order MDS Codes
Joshua Brakensiek, Sivakanth Gopi, Visu Makam
IEEE Transactions on Information Theory | July 2021
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Improved Maximally Recoverable LRCs using Skew Polynomials
Sivakanth Gopi, Venkatesan Guruswami
IEEE Transactions on Information Theory | December 2020
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Gaussian width bounds with applications to arithmetic progressions in random settings
Jop Briet, Sivakanth Gopi
International Mathematics Research Notices (IMRN) | October 2018
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Spanoids – an abstraction of spanning structures, and a barrier for LCCs
Zeev Dvir, Sivakanth Gopi, A. Wigderson
SIAM J. Comput. | September 2018, Vol 49: pp. 465-496
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Locally Testable and Locally Correctable Codes approaching the Gilbert-Varshamov Bound
Sivakanth Gopi, Swastik Kopparty, R. Oliveira, Noga Ron-Zewi, Shubhangi Saraf
IEEE Transactions on Information Theory | January 2017, Vol 64(8): pp. 5813-5831
Conference version appeared in SODA 2017.
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2-Server PIR with sub-polynomial communication
Zeev Dvir, Sivakanth Gopi
Journal of the ACM (JACM) | November 2016, Vol 63(4)
Best Paper Award in STOC 2015
Conference version appeared in STOC 2015 where it was a cowinner of the best paper award.
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Competitive analysis of the top-K ranking problem
Xi Chen, Sivakanth Gopi, Jieming Mao, Jon Schneider
IEEE Transactions on Information Theory | May 2016, Vol abs/1605.03933(64)
Conference version appeared in SODA 2017.
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Lower Bounds for Constant Query Affine-Invariant LCCs and LTCs
Arnab Bhattacharyya, Sivakanth Gopi
ACM Transactions on Computation Theory (TOCT) | November 2015, Vol 9(2): pp. 1-17
Conference version appeared in CCC 2016.
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Locality in Coding Theory
June 2018
Thèse de doctorat : Princeton University | June 2018
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