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
Janardhan (Jana) Kulkarni
Principal Researcher
Publications
Publications by Year
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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
January 2025
-
Towards Foundation Models for Mixed Integer Linear Programming
Sirui Li, Janardhan (Jana) Kulkarni, Ishai Menache, Cathy Wu, Beibin Li
October 2024
Optimal online discrepancy minimization
Janardhan (Jana) Kulkarni, Victor Reis, Thomas Rothvoss
STOC'24 | June 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
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
Privately Aligning Language Models with Reinforcement Learning
Fan Wu, Huseyin Inan, Arturs Backurs, Varun Chandrasekaran, Janardhan (Jana) Kulkarni, Robert Sim
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
Workload-Aware Hardware Accelerator Mining for Distributed Deep Learning Training
Muhammad Adnan, Amar Phanishayee,, Janardhan (Jana) Kulkarni, Prashant J. Nair, Divya Mahajan
arXiv:2404.14632 | April 2024
Published by Microsoft
Differentially Private Training of Mixture of Experts Models
Pierre Tholoniat, Huseyin A. Inan, Janardhan (Jana) Kulkarni, Robert Sim
PPAI-24: The 5th AAAI Workshop on Privacy-Preserving Artificial Intelligence | February 2024
-
TinyGSM: achieving >80% on GSM8k with small language models
Bingbin Liu, Sébastien Bubeck, Ronen Eldan, Janardhan (Jana) Kulkarni, Yuanzhi Li, Anh Nguyen, Rachel Ward, Yi Zhang
3nd MATH-AI Workshop at NeurIPS'23 | December 2023
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
Assessing Privacy Risks in Language Models: A Case Study on Summarization Tasks
Ruixiang Tang, Gord Lueck, Rodolfo Quispe, Huseyin A. Inan, Janardhan (Jana) Kulkarni, Xia Hu
Empirical Methods in Natural Language Processing (EMNLP 2023) | October 2023
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan (Jana) Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian
International Conference on Learning Representations (ICLR) 2023 | May 2023
-
Differentially Private Model Compression
Fatemehsadat Mireshghallah, Arturs Backurs, Huseyin Inan, Lukas Wutschitz, Janardhan (Jana) Kulkarni
NeurIPS 2022 | November 2022
When does differentially private learning not suffer in high dimensions?
Xuechen Li, Daogao Liu, Tatsunori Hashimoto, Huseyin Inan, Janardhan (Jana) Kulkarni, Yin Tat Lee, Abhradeep Guha Thakurta
NeurIPS'22 | November 2022
Looking Beyond GPUs for DNN Scheduling on Multi-Tenant Clusters
Jayashree Mohan, Amar Phanishayee, Janardhan (Jana) Kulkarni, Vijay Chidambaram
USENIX Symposium on Operating Systems Design and Implementation (OSDI 2022) | July 2022
Online Edge Coloring via Tree Recurrences and Correlation Decay
Janardhan (Jana) Kulkarni, Yang Liu, Yang Liu, Yang Liu, Ashwin Sah, Mehtaab Sawhney, Jakub Tarnawski
STOC 2022 | 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
On the Hardness of Scheduling With Non-Uniform Communication Delays
Sami Davies, Janardhan (Jana) Kulkarni, Thomas Rothvoss, Sai Sandeep, Jakub Tarnawski, Yihao Zhang
SODA 2022 | January 2022
-
Differentially private n-gram extraction
Kunho Kim, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Sergey Yekhanin
NeurIPS 2021 | December 2021
Synergy: Resource Sensitive DNN Scheduling in Multi-Tenant Clusters
Jayashree Mohan, Amar Phanishayee, Janardhan (Jana) Kulkarni, Vijay Chidambaram
October 2021
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting
Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan (Jana) Kulkarni
2021 International Conference on Machine Learning | July 2021
Scheduling Opportunistic Links in Two-Tiered Reconfigurable Datacenters
Janardhan (Jana) Kulkarni, Stefan Schmid, Paweł Schmidt
ACM Symposium on Parallelism in Algorithms and Architectures (SPAA) 2021 | July 2021
Consistent k-Median: Simpler, Better and Robust
Xiangyu Guo, Janardhan (Jana) Kulkarni, Shi Li, Jiayi Xian
International Conference on Artificial Intelligence and Statistics (AISTATS) 2021 | April 2021
Private Non-smooth Empirical Risk Minimization and Stochastic Convex Optimization in Subquadratic Steps
Janardhan (Jana) Kulkarni, Yin Tat Lee, Daogao Liu
NeurIPS 2021 | March 2021
Differentially Private Correlation Clustering
Mark Bun, Marek Eliás, Janardhan (Jana) Kulkarni
2021 International Conference on Machine Learning | February 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
Scheduling with Communication Delays via LP Hierarchies and Clustering II: Weighted Completion Times on Related Machines
Sami Davies, Janardhan (Jana) Kulkarni, Thomas Rothvoss, Jakub Tarnawski, Yihao Zhang
SODA 2021 | January 2021
-
On the Facility Location Problem in Online and Dynamic Models
Xiangyu Guo, Janardhan (Jana) Kulkarni, Shi Li, Jiayi Xian
APPROX-RANDOM | August 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).
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
Privately Learning Markov Random Fields
Huanyu Zhang, Gautam Kamath, Janardhan (Jana) Kulkarni, Zhiwei Steven Wu
ICML 2020 | July 2020
Scheduling with Communication Delays via LP Hierarchies and Clustering
Sami Davies, Janardhan (Jana) Kulkarni, Thomas Rothvoss, Jakub Tarnawski, Yihao Zhang
FOCS 2020 | April 2020
Hierarchy-Based Algorithms for Minimizing Makespan under Precedence and Communication Constraints
Janardhan (Jana) Kulkarni, Shi Li, Jakub Tarnawski, Minwei Ye
SODA 2020 | January 2020
Differentially private release of synthetic graphs
Marek Eliáš, Michael Kapralov, Janardhan (Jana) Kulkarni, Yin Tat Lee
2020 Symposium on Discrete Algorithms | January 2020
-
Locally Private Gaussian Estimation
Matthew Joseph, Janardhan (Jana) Kulkarni, Jieming Mao, Zhiwei Steven Wu
November 2019
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors
Joshua Allen, Bolin Ding, Janardhan (Jana) Kulkarni, Harsha Nori, Olga Ohrimenko, Sergey Yekhanin
NeurIPS 2019 | August 2019
-
Collecting Telemetry Data Privately
Bolin Ding, Janardhan (Jana) Kulkarni, Sergey Yekhanin
Advances in Neural Information Processing Systems 30 | December 2017
Truth and Regret in Online Scheduling
Shuchi Chawla, Nikhil Devanur, Janardhan (Jana) Kulkarni, Rad Niazadeh
March 2017
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Morpheus: Towards Automated SLOs for Enterprise Clusters
Sangeetha Abdu Jyothi, Carlo Curino, Ishai Menache, Shravan Matthur Narayanamurthy, Alexey Tumanov, Jonathan Yaniv, Ruslan Mavlyutov, Íñigo Goiri, Subru Krishnan, Janardhan (Jana) Kulkarni, Sriram Rao
2016 International Symposium on Operating Systems Design and Implementation (OSDI) | November 2016
Graphene: Packing and Dependency-aware Scheduling for Data-Parallel Clusters
Robert Grandl, Srikanth Kandula, Sriram Rao, Aditya Akella, Janardhan (Jana) Kulkarni
Operating Systems Design and Implementation | October 2016
ProjecToR: Agile Reconfigurable Data Center Interconnect
Manya Ghobadi, Ratul Mahajan, Amar Phanishayee, Nikhil Devanur, Janardhan (Jana) Kulkarni, Gireeja Ranade, Pierre-Alexandre Blanche, Houman Rastegarfar, Madeleine Glick, Daniel Kilper
ACM SIGCOMM 2016 | August 2016
Fair Online Scheduling for Selfish Jobs on Heterogeneous Machines
SPAA '16 Proceedings of the 28th ACM Symposium on Parallelism in Algorithms and Architectures | July 2016
Do the Hard Stuff First: Scheduling Dependent Computations in Data Analytics Clusters
Robert Grandl, Srikanth Kandula, Sriram Rao, Aditya Akella, Janardhan (Jana) Kulkarni
MSR-TR-2016-19 | February 2016
Published by Microsoft
A Competitive Flow Time Algorithm for Heterogeneous Clusters Under Polytope Constraints
Sunjin Im, Janardhan (Jana) Kulkarni, Benjamin Moseley, Kamesh Munagala
January 2016
Competitive Analysis of Constrained Queueing Systems
Sungjin Im, Janardhan (Jana) Kulkarni, Kamesh Munagala
43rd International Colloquium on Automata, Languages, and Programming (ICALP 2016) | January 2016
-
Competitive Flow-Time Algorithms For Polyhedral Scheduling
Sungjin Im, Janardhan (Jana) Kulkarni, Kamesh Munagala
Foundations of Computer Science (FOCS), 2015 IEEE 56th Annual Symposium on | December 2015
Dynamic Coordination Games
Janardhan (Jana) Kulkarni, Vahab Mirrokni
Newsletter ACM SIGMETRICS Performance Evaluation Review | December 2015
Temporal Fairness of Round Robin
Sungjin Im, Janardhan (Jana) Kulkarni, Benjamin Moseley
Proceeding SPAA '15 Proceedings of the 27th ACM symposium on Parallelism in Algorithms and Architectures | June 2015
Robust Price of Anarchy Bounds via LP and Fenchel Duality
Janardhan (Jana) Kulkarni, Vahab Mirrokni
Proceeding SODA '15 Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms | January 2015
-
Tight Bounds for Online Vector Scheduling
Sungjin Im, Nathaniel Kell, Janardhan (Jana) Kulkarni, Debmalya Panigrahi
December 2014
Coordination Mechanisms for Selfish Routing over Time on a Tree
Sayan Bhattacharya, Janardhan (Jana) Kulkarni, Vahab Mirrokni
July 2014
Competitive Algorithms from Competitive Equilibria: Non-Clairvoyant Scheduling under Polyhedral Constraints
Sungjin Im, Janardhan (Jana) Kulkarni, Kamesh Munagala
May 2014
SELFISHMIGRATE: A Scalable Algorithm for Non-clairvoyantly Scheduling Heterogeneous Processors
Sungjin Im, Janardhan (Jana) Kulkarni, Kamesh Munagala, Kirk Pruhs
May 2014
Minimizing Flow-Time on Unrelated Machines
Nikhil Bansal, Janardhan (Jana) Kulkarni
February 2014
-
Online Non-clairvoyant Scheduling to Simultaneously Minimize All Convex Functions
Kyle Fox, Sungjin Im, Janardhan (Jana) Kulkarni, Benjamin Moseley
August 2013
Coordination Mechanisms from (almost) all Scheduling Policies
ITCS '14 Proceedings of the 5th conference on Innovations in theoretical computer science | August 2013
Near-optimal multi-unit auctions with ordered bidders
Sayan Bhattacharya, Elias Koutsoupias, Janardhan (Jana) Kulkarni, Stefano Leonardi, Tim Roughgarden, Xiaoming Xu
EC '13 Proceedings of the fourteenth ACM conference on Electronic commerce | June 2013
Constant-Competitive Prior-Free Auction with Ordered Bidders
Sayan Bhattacharya, Janardhan (Jana) Kulkarni, Xiaoming Xu
January 2013
-
Cost-Aware Scheduling
September 2012
-
On Allocations with Negative Externalities
Sayan Bhattacharya, Janardhan (Jana) Kulkarni, Kamesh Munagala, Xiaoming Xu
WINE'11 Proceedings of the 7th international conference on Internet and Network Economics | December 2011
-
New epsilon-net constructions
Janardhan (Jana) Kulkarni, Sathish Govindarajan
August 2010
-
On the Decidability of Model-Checking Information Flow Properties
Deepak D'Souza, Raveendra Holla, Janardhan (Jana) Kulkarni, Barbara Sprick
December 2008
Publications by Research Area
-
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
January 2025
Towards Foundation Models for Mixed Integer Linear Programming
Sirui Li, Janardhan (Jana) Kulkarni, Ishai Menache, Cathy Wu, Beibin Li
October 2024
Privately Aligning Language Models with Reinforcement Learning
Fan Wu, Huseyin Inan, Arturs Backurs, Varun Chandrasekaran, Janardhan (Jana) Kulkarni, Robert Sim
ICLR 2024 | May 2024
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
TinyGSM: achieving >80% on GSM8k with small language models
Bingbin Liu, Sébastien Bubeck, Ronen Eldan, Janardhan (Jana) Kulkarni, Yuanzhi Li, Anh Nguyen, Rachel Ward, Yi Zhang
3nd MATH-AI Workshop at NeurIPS'23 | December 2023
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
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan (Jana) Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian
International Conference on Learning Representations (ICLR) 2023 | May 2023
Differentially Private Model Compression
Fatemehsadat Mireshghallah, Arturs Backurs, Huseyin Inan, Lukas Wutschitz, Janardhan (Jana) Kulkarni
NeurIPS 2022 | November 2022
Looking Beyond GPUs for DNN Scheduling on Multi-Tenant Clusters
Jayashree Mohan, Amar Phanishayee, Janardhan (Jana) Kulkarni, Vijay Chidambaram
USENIX Symposium on Operating Systems Design and Implementation (OSDI 2022) | July 2022
Synergy: Resource Sensitive DNN Scheduling in Multi-Tenant Clusters
Jayashree Mohan, Amar Phanishayee, Janardhan (Jana) Kulkarni, Vijay Chidambaram
October 2021
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting
Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan (Jana) Kulkarni
2021 International Conference on Machine Learning | July 2021
Private Non-smooth Empirical Risk Minimization and Stochastic Convex Optimization in Subquadratic Steps
Janardhan (Jana) Kulkarni, Yin Tat Lee, Daogao Liu
NeurIPS 2021 | March 2021
Privately Learning Markov Random Fields
Huanyu Zhang, Gautam Kamath, Janardhan (Jana) Kulkarni, Zhiwei Steven Wu
ICML 2020 | July 2020
Truth and Regret in Online Scheduling
Shuchi Chawla, Nikhil Devanur, Janardhan (Jana) Kulkarni, Rad Niazadeh
March 2017
-
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
January 2025
Optimal online discrepancy minimization
Janardhan (Jana) Kulkarni, Victor Reis, Thomas Rothvoss
STOC'24 | June 2024
Privately Aligning Language Models with Reinforcement Learning
Fan Wu, Huseyin Inan, Arturs Backurs, Varun Chandrasekaran, 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
Differentially Private Training of Mixture of Experts Models
Pierre Tholoniat, Huseyin A. Inan, Janardhan (Jana) Kulkarni, Robert Sim
PPAI-24: The 5th AAAI Workshop on Privacy-Preserving Artificial Intelligence | February 2024
Assessing Privacy Risks in Language Models: A Case Study on Summarization Tasks
Ruixiang Tang, Gord Lueck, Rodolfo Quispe, Huseyin A. Inan, Janardhan (Jana) Kulkarni, Xia Hu
Empirical Methods in Natural Language Processing (EMNLP 2023) | October 2023
Differentially Private Model Compression
Fatemehsadat Mireshghallah, Arturs Backurs, Huseyin Inan, Lukas Wutschitz, Janardhan (Jana) Kulkarni
NeurIPS 2022 | November 2022
When does differentially private learning not suffer in high dimensions?
Xuechen Li, Daogao Liu, Tatsunori Hashimoto, Huseyin Inan, Janardhan (Jana) Kulkarni, Yin Tat Lee, Abhradeep Guha Thakurta
NeurIPS'22 | November 2022
Online Edge Coloring via Tree Recurrences and Correlation Decay
Janardhan (Jana) Kulkarni, Yang Liu, Yang Liu, Yang Liu, Ashwin Sah, Mehtaab Sawhney, Jakub Tarnawski
STOC 2022 | 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
On the Hardness of Scheduling With Non-Uniform Communication Delays
Sami Davies, Janardhan (Jana) Kulkarni, Thomas Rothvoss, Sai Sandeep, Jakub Tarnawski, Yihao Zhang
SODA 2022 | January 2022
Differentially private n-gram extraction
Kunho Kim, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Sergey Yekhanin
NeurIPS 2021 | December 2021
Scheduling Opportunistic Links in Two-Tiered Reconfigurable Datacenters
Janardhan (Jana) Kulkarni, Stefan Schmid, Paweł Schmidt
ACM Symposium on Parallelism in Algorithms and Architectures (SPAA) 2021 | July 2021
Consistent k-Median: Simpler, Better and Robust
Xiangyu Guo, Janardhan (Jana) Kulkarni, Shi Li, Jiayi Xian
International Conference on Artificial Intelligence and Statistics (AISTATS) 2021 | April 2021
Private Non-smooth Empirical Risk Minimization and Stochastic Convex Optimization in Subquadratic Steps
Janardhan (Jana) Kulkarni, Yin Tat Lee, Daogao Liu
NeurIPS 2021 | March 2021
Differentially Private Correlation Clustering
Mark Bun, Marek Eliás, Janardhan (Jana) Kulkarni
2021 International Conference on Machine Learning | February 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
Scheduling with Communication Delays via LP Hierarchies and Clustering II: Weighted Completion Times on Related Machines
Sami Davies, Janardhan (Jana) Kulkarni, Thomas Rothvoss, Jakub Tarnawski, Yihao Zhang
SODA 2021 | January 2021
On the Facility Location Problem in Online and Dynamic Models
Xiangyu Guo, Janardhan (Jana) Kulkarni, Shi Li, Jiayi Xian
APPROX-RANDOM | August 2020
Privately Learning Markov Random Fields
Huanyu Zhang, Gautam Kamath, Janardhan (Jana) Kulkarni, Zhiwei Steven Wu
ICML 2020 | July 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).
Scheduling with Communication Delays via LP Hierarchies and Clustering
Sami Davies, Janardhan (Jana) Kulkarni, Thomas Rothvoss, Jakub Tarnawski, Yihao Zhang
FOCS 2020 | April 2020
Hierarchy-Based Algorithms for Minimizing Makespan under Precedence and Communication Constraints
Janardhan (Jana) Kulkarni, Shi Li, Jakub Tarnawski, Minwei Ye
SODA 2020 | January 2020
Differentially private release of synthetic graphs
Marek Eliáš, Michael Kapralov, Janardhan (Jana) Kulkarni, Yin Tat Lee
2020 Symposium on Discrete Algorithms | January 2020
Collecting Telemetry Data Privately
Bolin Ding, Janardhan (Jana) Kulkarni, Sergey Yekhanin
Advances in Neural Information Processing Systems 30 | December 2017
Truth and Regret in Online Scheduling
Shuchi Chawla, Nikhil Devanur, Janardhan (Jana) Kulkarni, Rad Niazadeh
March 2017
Fair Online Scheduling for Selfish Jobs on Heterogeneous Machines
SPAA '16 Proceedings of the 28th ACM Symposium on Parallelism in Algorithms and Architectures | July 2016
Competitive Analysis of Constrained Queueing Systems
Sungjin Im, Janardhan (Jana) Kulkarni, Kamesh Munagala
43rd International Colloquium on Automata, Languages, and Programming (ICALP 2016) | January 2016
A Competitive Flow Time Algorithm for Heterogeneous Clusters Under Polytope Constraints
Sunjin Im, Janardhan (Jana) Kulkarni, Benjamin Moseley, Kamesh Munagala
January 2016
Competitive Flow-Time Algorithms For Polyhedral Scheduling
Sungjin Im, Janardhan (Jana) Kulkarni, Kamesh Munagala
Foundations of Computer Science (FOCS), 2015 IEEE 56th Annual Symposium on | December 2015
Dynamic Coordination Games
Janardhan (Jana) Kulkarni, Vahab Mirrokni
Newsletter ACM SIGMETRICS Performance Evaluation Review | December 2015
Temporal Fairness of Round Robin
Sungjin Im, Janardhan (Jana) Kulkarni, Benjamin Moseley
Proceeding SPAA '15 Proceedings of the 27th ACM symposium on Parallelism in Algorithms and Architectures | June 2015
Robust Price of Anarchy Bounds via LP and Fenchel Duality
Janardhan (Jana) Kulkarni, Vahab Mirrokni
Proceeding SODA '15 Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms | January 2015
Tight Bounds for Online Vector Scheduling
Sungjin Im, Nathaniel Kell, Janardhan (Jana) Kulkarni, Debmalya Panigrahi
December 2014
Coordination Mechanisms for Selfish Routing over Time on a Tree
Sayan Bhattacharya, Janardhan (Jana) Kulkarni, Vahab Mirrokni
July 2014
Competitive Algorithms from Competitive Equilibria: Non-Clairvoyant Scheduling under Polyhedral Constraints
Sungjin Im, Janardhan (Jana) Kulkarni, Kamesh Munagala
May 2014
SELFISHMIGRATE: A Scalable Algorithm for Non-clairvoyantly Scheduling Heterogeneous Processors
Sungjin Im, Janardhan (Jana) Kulkarni, Kamesh Munagala, Kirk Pruhs
May 2014
Minimizing Flow-Time on Unrelated Machines
Nikhil Bansal, Janardhan (Jana) Kulkarni
February 2014
Online Non-clairvoyant Scheduling to Simultaneously Minimize All Convex Functions
Kyle Fox, Sungjin Im, Janardhan (Jana) Kulkarni, Benjamin Moseley
August 2013
Coordination Mechanisms from (almost) all Scheduling Policies
ITCS '14 Proceedings of the 5th conference on Innovations in theoretical computer science | August 2013
Near-optimal multi-unit auctions with ordered bidders
Sayan Bhattacharya, Elias Koutsoupias, Janardhan (Jana) Kulkarni, Stefano Leonardi, Tim Roughgarden, Xiaoming Xu
EC '13 Proceedings of the fourteenth ACM conference on Electronic commerce | June 2013
Constant-Competitive Prior-Free Auction with Ordered Bidders
Sayan Bhattacharya, Janardhan (Jana) Kulkarni, Xiaoming Xu
January 2013
Cost-Aware Scheduling
September 2012
On Allocations with Negative Externalities
Sayan Bhattacharya, Janardhan (Jana) Kulkarni, Kamesh Munagala, Xiaoming Xu
WINE'11 Proceedings of the 7th international conference on Internet and Network Economics | December 2011
New epsilon-net constructions
Janardhan (Jana) Kulkarni, Sathish Govindarajan
August 2010
On the Decidability of Model-Checking Information Flow Properties
Deepak D'Souza, Raveendra Holla, Janardhan (Jana) Kulkarni, Barbara Sprick
December 2008
-
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
January 2025
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
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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Workload-Aware Hardware Accelerator Mining for Distributed Deep Learning Training
Muhammad Adnan, Amar Phanishayee,, Janardhan (Jana) Kulkarni, Prashant J. Nair, Divya Mahajan
arXiv:2404.14632 | April 2024
Published by Microsoft
Looking Beyond GPUs for DNN Scheduling on Multi-Tenant Clusters
Jayashree Mohan, Amar Phanishayee, Janardhan (Jana) Kulkarni, Vijay Chidambaram
USENIX Symposium on Operating Systems Design and Implementation (OSDI 2022) | July 2022
Synergy: Resource Sensitive DNN Scheduling in Multi-Tenant Clusters
Jayashree Mohan, Amar Phanishayee, Janardhan (Jana) Kulkarni, Vijay Chidambaram
October 2021
Morpheus: Towards Automated SLOs for Enterprise Clusters
Sangeetha Abdu Jyothi, Carlo Curino, Ishai Menache, Shravan Matthur Narayanamurthy, Alexey Tumanov, Jonathan Yaniv, Ruslan Mavlyutov, Íñigo Goiri, Subru Krishnan, Janardhan (Jana) Kulkarni, Sriram Rao
2016 International Symposium on Operating Systems Design and Implementation (OSDI) | November 2016
Graphene: Packing and Dependency-aware Scheduling for Data-Parallel Clusters
Robert Grandl, Srikanth Kandula, Sriram Rao, Aditya Akella, Janardhan (Jana) Kulkarni
Operating Systems Design and Implementation | October 2016
ProjecToR: Agile Reconfigurable Data Center Interconnect
Manya Ghobadi, Ratul Mahajan, Amar Phanishayee, Nikhil Devanur, Janardhan (Jana) Kulkarni, Gireeja Ranade, Pierre-Alexandre Blanche, Houman Rastegarfar, Madeleine Glick, Daniel Kilper
ACM SIGCOMM 2016 | August 2016
Do the Hard Stuff First: Scheduling Dependent Computations in Data Analytics Clusters
Robert Grandl, Srikanth Kandula, Sriram Rao, Aditya Akella, Janardhan (Jana) Kulkarni
MSR-TR-2016-19 | February 2016
Published by Microsoft
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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
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
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan (Jana) Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian
International Conference on Learning Representations (ICLR) 2023 | May 2023
Private Non-smooth Empirical Risk Minimization and Stochastic Convex Optimization in Subquadratic Steps
Janardhan (Jana) Kulkarni, Yin Tat Lee, Daogao Liu
NeurIPS 2021 | March 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
Privately Learning Markov Random Fields
Huanyu Zhang, Gautam Kamath, Janardhan (Jana) Kulkarni, Zhiwei Steven Wu
ICML 2020 | July 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).
Locally Private Gaussian Estimation
Matthew Joseph, Janardhan (Jana) Kulkarni, Jieming Mao, Zhiwei Steven Wu
November 2019
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors
Joshua Allen, Bolin Ding, Janardhan (Jana) Kulkarni, Harsha Nori, Olga Ohrimenko, Sergey Yekhanin
NeurIPS 2019 | August 2019
Collecting Telemetry Data Privately
Bolin Ding, Janardhan (Jana) Kulkarni, Sergey Yekhanin
Advances in Neural Information Processing Systems 30 | December 2017
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Collecting Telemetry Data Privately
Bolin Ding, Janardhan (Jana) Kulkarni, Sergey Yekhanin
Advances in Neural Information Processing Systems 30 | December 2017
Publications by Type
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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
January 2025
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Towards Foundation Models for Mixed Integer Linear Programming
Sirui Li, Janardhan (Jana) Kulkarni, Ishai Menache, Cathy Wu, Beibin Li
October 2024
Synergy: Resource Sensitive DNN Scheduling in Multi-Tenant Clusters
Jayashree Mohan, Amar Phanishayee, Janardhan (Jana) Kulkarni, Vijay Chidambaram
October 2021
Locally Private Gaussian Estimation
Matthew Joseph, Janardhan (Jana) Kulkarni, Jieming Mao, Zhiwei Steven Wu
November 2019
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Optimal online discrepancy minimization
Janardhan (Jana) Kulkarni, Victor Reis, Thomas Rothvoss
STOC'24 | June 2024
Privately Aligning Language Models with Reinforcement Learning
Fan Wu, Huseyin Inan, Arturs Backurs, Varun Chandrasekaran, Janardhan (Jana) Kulkarni, Robert Sim
ICLR 2024 | May 2024
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
Differentially Private Training of Mixture of Experts Models
Pierre Tholoniat, Huseyin A. Inan, Janardhan (Jana) Kulkarni, Robert Sim
PPAI-24: The 5th AAAI Workshop on Privacy-Preserving Artificial Intelligence | February 2024
TinyGSM: achieving >80% on GSM8k with small language models
Bingbin Liu, Sébastien Bubeck, Ronen Eldan, Janardhan (Jana) Kulkarni, Yuanzhi Li, Anh Nguyen, Rachel Ward, Yi Zhang
3nd MATH-AI Workshop at NeurIPS'23 | December 2023
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
Assessing Privacy Risks in Language Models: A Case Study on Summarization Tasks
Ruixiang Tang, Gord Lueck, Rodolfo Quispe, Huseyin A. Inan, Janardhan (Jana) Kulkarni, Xia Hu
Empirical Methods in Natural Language Processing (EMNLP 2023) | October 2023
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan (Jana) Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian
International Conference on Learning Representations (ICLR) 2023 | May 2023
Differentially Private Model Compression
Fatemehsadat Mireshghallah, Arturs Backurs, Huseyin Inan, Lukas Wutschitz, Janardhan (Jana) Kulkarni
NeurIPS 2022 | November 2022
When does differentially private learning not suffer in high dimensions?
Xuechen Li, Daogao Liu, Tatsunori Hashimoto, Huseyin Inan, Janardhan (Jana) Kulkarni, Yin Tat Lee, Abhradeep Guha Thakurta
NeurIPS'22 | November 2022
Looking Beyond GPUs for DNN Scheduling on Multi-Tenant Clusters
Jayashree Mohan, Amar Phanishayee, Janardhan (Jana) Kulkarni, Vijay Chidambaram
USENIX Symposium on Operating Systems Design and Implementation (OSDI 2022) | July 2022
Online Edge Coloring via Tree Recurrences and Correlation Decay
Janardhan (Jana) Kulkarni, Yang Liu, Yang Liu, Yang Liu, Ashwin Sah, Mehtaab Sawhney, Jakub Tarnawski
STOC 2022 | 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
On the Hardness of Scheduling With Non-Uniform Communication Delays
Sami Davies, Janardhan (Jana) Kulkarni, Thomas Rothvoss, Sai Sandeep, Jakub Tarnawski, Yihao Zhang
SODA 2022 | January 2022
Differentially private n-gram extraction
Kunho Kim, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Sergey Yekhanin
NeurIPS 2021 | December 2021
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting
Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan (Jana) Kulkarni
2021 International Conference on Machine Learning | July 2021
Scheduling Opportunistic Links in Two-Tiered Reconfigurable Datacenters
Janardhan (Jana) Kulkarni, Stefan Schmid, Paweł Schmidt
ACM Symposium on Parallelism in Algorithms and Architectures (SPAA) 2021 | July 2021
Consistent k-Median: Simpler, Better and Robust
Xiangyu Guo, Janardhan (Jana) Kulkarni, Shi Li, Jiayi Xian
International Conference on Artificial Intelligence and Statistics (AISTATS) 2021 | April 2021
Private Non-smooth Empirical Risk Minimization and Stochastic Convex Optimization in Subquadratic Steps
Janardhan (Jana) Kulkarni, Yin Tat Lee, Daogao Liu
NeurIPS 2021 | March 2021
Differentially Private Correlation Clustering
Mark Bun, Marek Eliás, Janardhan (Jana) Kulkarni
2021 International Conference on Machine Learning | February 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
Scheduling with Communication Delays via LP Hierarchies and Clustering II: Weighted Completion Times on Related Machines
Sami Davies, Janardhan (Jana) Kulkarni, Thomas Rothvoss, Jakub Tarnawski, Yihao Zhang
SODA 2021 | January 2021
On the Facility Location Problem in Online and Dynamic Models
Xiangyu Guo, Janardhan (Jana) Kulkarni, Shi Li, Jiayi Xian
APPROX-RANDOM | August 2020
Privately Learning Markov Random Fields
Huanyu Zhang, Gautam Kamath, Janardhan (Jana) Kulkarni, Zhiwei Steven Wu
ICML 2020 | July 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).
Scheduling with Communication Delays via LP Hierarchies and Clustering
Sami Davies, Janardhan (Jana) Kulkarni, Thomas Rothvoss, Jakub Tarnawski, Yihao Zhang
FOCS 2020 | April 2020
Hierarchy-Based Algorithms for Minimizing Makespan under Precedence and Communication Constraints
Janardhan (Jana) Kulkarni, Shi Li, Jakub Tarnawski, Minwei Ye
SODA 2020 | January 2020
Differentially private release of synthetic graphs
Marek Eliáš, Michael Kapralov, Janardhan (Jana) Kulkarni, Yin Tat Lee
2020 Symposium on Discrete Algorithms | January 2020
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors
Joshua Allen, Bolin Ding, Janardhan (Jana) Kulkarni, Harsha Nori, Olga Ohrimenko, Sergey Yekhanin
NeurIPS 2019 | August 2019
Collecting Telemetry Data Privately
Bolin Ding, Janardhan (Jana) Kulkarni, Sergey Yekhanin
Advances in Neural Information Processing Systems 30 | December 2017
Morpheus: Towards Automated SLOs for Enterprise Clusters
Sangeetha Abdu Jyothi, Carlo Curino, Ishai Menache, Shravan Matthur Narayanamurthy, Alexey Tumanov, Jonathan Yaniv, Ruslan Mavlyutov, Íñigo Goiri, Subru Krishnan, Janardhan (Jana) Kulkarni, Sriram Rao
2016 International Symposium on Operating Systems Design and Implementation (OSDI) | November 2016
Graphene: Packing and Dependency-aware Scheduling for Data-Parallel Clusters
Robert Grandl, Srikanth Kandula, Sriram Rao, Aditya Akella, Janardhan (Jana) Kulkarni
Operating Systems Design and Implementation | October 2016
ProjecToR: Agile Reconfigurable Data Center Interconnect
Manya Ghobadi, Ratul Mahajan, Amar Phanishayee, Nikhil Devanur, Janardhan (Jana) Kulkarni, Gireeja Ranade, Pierre-Alexandre Blanche, Houman Rastegarfar, Madeleine Glick, Daniel Kilper
ACM SIGCOMM 2016 | August 2016
Fair Online Scheduling for Selfish Jobs on Heterogeneous Machines
SPAA '16 Proceedings of the 28th ACM Symposium on Parallelism in Algorithms and Architectures | July 2016
Competitive Analysis of Constrained Queueing Systems
Sungjin Im, Janardhan (Jana) Kulkarni, Kamesh Munagala
43rd International Colloquium on Automata, Languages, and Programming (ICALP 2016) | January 2016
A Competitive Flow Time Algorithm for Heterogeneous Clusters Under Polytope Constraints
Sunjin Im, Janardhan (Jana) Kulkarni, Benjamin Moseley, Kamesh Munagala
January 2016
Competitive Flow-Time Algorithms For Polyhedral Scheduling
Sungjin Im, Janardhan (Jana) Kulkarni, Kamesh Munagala
Foundations of Computer Science (FOCS), 2015 IEEE 56th Annual Symposium on | December 2015
Temporal Fairness of Round Robin
Sungjin Im, Janardhan (Jana) Kulkarni, Benjamin Moseley
Proceeding SPAA '15 Proceedings of the 27th ACM symposium on Parallelism in Algorithms and Architectures | June 2015
Robust Price of Anarchy Bounds via LP and Fenchel Duality
Janardhan (Jana) Kulkarni, Vahab Mirrokni
Proceeding SODA '15 Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms | January 2015
Coordination Mechanisms for Selfish Routing over Time on a Tree
Sayan Bhattacharya, Janardhan (Jana) Kulkarni, Vahab Mirrokni
July 2014
Online Non-clairvoyant Scheduling to Simultaneously Minimize All Convex Functions
Kyle Fox, Sungjin Im, Janardhan (Jana) Kulkarni, Benjamin Moseley
August 2013
Coordination Mechanisms from (almost) all Scheduling Policies
ITCS '14 Proceedings of the 5th conference on Innovations in theoretical computer science | August 2013
Near-optimal multi-unit auctions with ordered bidders
Sayan Bhattacharya, Elias Koutsoupias, Janardhan (Jana) Kulkarni, Stefano Leonardi, Tim Roughgarden, Xiaoming Xu
EC '13 Proceedings of the fourteenth ACM conference on Electronic commerce | June 2013
On Allocations with Negative Externalities
Sayan Bhattacharya, Janardhan (Jana) Kulkarni, Kamesh Munagala, Xiaoming Xu
WINE'11 Proceedings of the 7th international conference on Internet and Network Economics | December 2011
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Workload-Aware Hardware Accelerator Mining for Distributed Deep Learning Training
Muhammad Adnan, Amar Phanishayee,, Janardhan (Jana) Kulkarni, Prashant J. Nair, Divya Mahajan
arXiv:2404.14632 | April 2024
Published by Microsoft
Do the Hard Stuff First: Scheduling Dependent Computations in Data Analytics Clusters
Robert Grandl, Srikanth Kandula, Sriram Rao, Aditya Akella, Janardhan (Jana) Kulkarni
MSR-TR-2016-19 | February 2016
Published by Microsoft
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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
Truth and Regret in Online Scheduling
Shuchi Chawla, Nikhil Devanur, Janardhan (Jana) Kulkarni, Rad Niazadeh
March 2017
Dynamic Coordination Games
Janardhan (Jana) Kulkarni, Vahab Mirrokni
Newsletter ACM SIGMETRICS Performance Evaluation Review | December 2015
Tight Bounds for Online Vector Scheduling
Sungjin Im, Nathaniel Kell, Janardhan (Jana) Kulkarni, Debmalya Panigrahi
December 2014
Competitive Algorithms from Competitive Equilibria: Non-Clairvoyant Scheduling under Polyhedral Constraints
Sungjin Im, Janardhan (Jana) Kulkarni, Kamesh Munagala
May 2014
SELFISHMIGRATE: A Scalable Algorithm for Non-clairvoyantly Scheduling Heterogeneous Processors
Sungjin Im, Janardhan (Jana) Kulkarni, Kamesh Munagala, Kirk Pruhs
May 2014
Minimizing Flow-Time on Unrelated Machines
Nikhil Bansal, Janardhan (Jana) Kulkarni
February 2014
Constant-Competitive Prior-Free Auction with Ordered Bidders
Sayan Bhattacharya, Janardhan (Jana) Kulkarni, Xiaoming Xu
January 2013
Cost-Aware Scheduling
September 2012
New epsilon-net constructions
Janardhan (Jana) Kulkarni, Sathish Govindarajan
August 2010
On the Decidability of Model-Checking Information Flow Properties
Deepak D'Souza, Raveendra Holla, Janardhan (Jana) Kulkarni, Barbara Sprick
December 2008