Janardhan Kulkarni

According to our database, Janardhan Kulkarni authored at least 79 papers between 2008 and 2024.

Collaborative distances:

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

2024

Online Edge Coloring via Tree Recurrences and Correlation Decay.

Janardhan Kulkarni, Yang P. Liu, Ashwin Sah, Mehtaab S. Sawhney, Jakub Tarnawski

SIAM J. Comput., February, 2024

Differentially Private Training of Mixture of Experts Models.

Pierre Tholoniat, Huseyin A. Inan, Janardhan Kulkarni, Robert Sim

CoRR, 2024

2023

TinyGSM: achieving >80% on GSM8k with small language models.

Bingbin Liu, Sébastien Bubeck, Ronen Eldan, Janardhan Kulkarni, Yuanzhi Li, Anh Nguyen, Rachel Ward, Yi Zhang

CoRR, 2023

Classification with Partially Private Features.

Zeyu Shen, Anilesh K. Krishnaswamy, Janardhan Kulkarni, Kamesh Munagala

CoRR, 2023

Privately Aligning Language Models with Reinforcement Learning.

Fan Wu, Huseyin A. Inan, Arturs Backurs, Varun Chandrasekaran, Janardhan Kulkarni, Robert Sim

CoRR, 2023

Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation.

Xinyu Tang, Richard Shin, Huseyin A. Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Robert Sim

CoRR, 2023

Optimal Online Discrepancy Minimization.

Janardhan Kulkarni, Victor Reis, Thomas Rothvoss

CoRR, 2023

Differentially Private Synthetic Data via Foundation Model APIs 1: Images.

Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Harsha Nori, Sergey Yekhanin

CoRR, 2023

Selective Pre-training for Private Fine-tuning.

Da Yu, Sivakanth Gopi, Janardhan Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang

CoRR, 2023

Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping.

Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Assessing Privacy Risks in Language Models: A Case Study on Summarization Tasks.

Ruixiang Tang, Gord Lueck, Rodolfo Quispe, Huseyin A. Inan, Janardhan Kulkarni, Xia Hu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022

Introduction to the Special Issue on ACM-SIAM Symposium on Discrete Algorithms (SODA) 2020.

Gautam Kamath, Sepehr Assadi, Anne Driemel, Janardhan Kulkarni

ACM Trans. Algorithms, 2022

Fully Dynamic (Δ +1)-Coloring in <i>O</i>(1) Update Time.

Sayan Bhattacharya, Fabrizio Grandoni, Janardhan Kulkarni, Quanquan C. Liu, Shay Solomon

ACM Trans. Algorithms, 2022

Per-Instance Privacy Accounting for Differentially Private Stochastic Gradient Descent.

Da Yu, Gautam Kamath, Janardhan Kulkarni, Tie-Yan Liu, Jian Yin, Huishuai Zhang

CoRR, 2022

On the Hardness of Scheduling With Non-Uniform Communication Delays.

Sami Davies, Janardhan Kulkarni, Thomas Rothvoss, Sai Sandeep, Jakub Tarnawski, Yihao Zhang

Proceedings of the 2022 ACM-SIAM Symposium on Discrete Algorithms, 2022

Looking Beyond GPUs for DNN Scheduling on Multi-Tenant Clusters.

Jayashree Mohan, Amar Phanishayee, Janardhan Kulkarni, Vijay Chidambaram

Proceedings of the 16th USENIX Symposium on Operating Systems Design and Implementation, 2022

Differentially Private Model Compression.

Fatemehsadat Mireshghallah, Arturs Backurs, Huseyin A. Inan, Lukas Wutschitz, Janardhan Kulkarni

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

When Does Differentially Private Learning Not Suffer in High Dimensions?

Xuechen Li, Daogao Liu, Tatsunori B. Hashimoto, Huseyin A. Inan, Janardhan Kulkarni, Yin Tat Lee, Abhradeep Guha Thakurta

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

Differentially Private Fine-tuning of Language Models.

Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin A. Inan, Gautam Kamath, Janardhan Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Differentially Private Set Union.

Sivakanth Gopi, Pankaj Gulhane, Janardhan Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin

J. Priv. Confidentiality, 2021

Synergy: Resource Sensitive DNN Scheduling in Multi-Tenant Clusters.

Jayashree Mohan, Amar Phanishayee, Janardhan Kulkarni, Vijay Chidambaram

CoRR, 2021

Private Non-smooth Empirical Risk Minimization and Stochastic Convex Optimization in Subquadratic Steps.

Janardhan Kulkarni, Yin Tat Lee, Daogao Liu

CoRR, 2021

Scheduling Opportunistic Links in Two-Tiered Reconfigurable Datacenters.

Janardhan Kulkarni, Stefan Schmid, Pawel Schmidt

Proceedings of the SPAA '21: 33rd ACM Symposium on Parallelism in Algorithms and Architectures, 2021

Scheduling with Communication Delays via LP Hierarchies and Clustering II: Weighted Completion Times on Related Machines.

Sami Davies, Janardhan Kulkarni, Thomas Rothvoss, Jakub Tarnawski, Yihao Zhang

Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms, 2021

Private Non-smooth ERM and SCO in Subquadratic Steps.

Janardhan Kulkarni, Yin Tat Lee, Daogao Liu

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

Differentially Private n-gram Extraction.

Kunho Kim, Sivakanth Gopi, Janardhan Kulkarni, Sergey Yekhanin

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

Fast and Memory Efficient Differentially Private-SGD via JL Projections.

Zhiqi Bu, Sivakanth Gopi, Janardhan Kulkarni, Yin Tat Lee, Judy Hanwen Shen, Uthaipon Tantipongpipat

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

Accuracy, Interpretability, and Differential Privacy via Explainable Boosting.

Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan Kulkarni

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

Differentially Private Correlation Clustering.

Mark Bun, Marek Eliás, Janardhan Kulkarni

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

Consistent k-Median: Simpler, Better and Robust.

Xiangyu Guo, Janardhan Kulkarni, Shi Li, Jiayi Xian

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

2020

Prior-free multi-unit auctions with ordered bidders.

Sayan Bhattacharya, Elias Koutsoupias, Janardhan Kulkarni, Stefano Leonardi, Tim Roughgarden, Xiaoming Xu

Theor. Comput. Sci., 2020

The Power of Recourse: Better Algorithms for Facility Location in Online and Dynamic Models.

Xiangyu Guo, Janardhan Kulkarni, Shi Li, Jiayi Xian

CoRR, 2020

Hierarchy-Based Algorithms for Minimizing Makespan under Precedence and Communication Constraints.

Janardhan Kulkarni, Shi Li, Jakub Tarnawski, Minwei Ye

Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020

Differentially Private Release of Synthetic Graphs.

Marek Eliás, Michael Kapralov, Janardhan Kulkarni, Yin Tat Lee

Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020

Parallel Batch-Dynamic Graphs: Algorithms and Lower Bounds.

Laxman Dhulipala, David Durfee, Janardhan Kulkarni, Richard Peng, Saurabh Sawlani, Xiaorui Sun

Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020

An Improved Algorithm for Incremental Cycle Detection and Topological Ordering in Sparse Graphs.

Sayan Bhattacharya, Janardhan Kulkarni

Proceedings of the 2020 ACM-SIAM Symposium on Discrete Algorithms, 2020

Privately Learning Markov Random Fields.

Huanyu Zhang, Gautam Kamath, Janardhan Kulkarni, Zhiwei Steven Wu

Proceedings of the 37th International Conference on Machine Learning, 2020

Scheduling with Communication Delays via LP Hierarchies and Clustering.

Sami Davies, Janardhan Kulkarni, Thomas Rothvoss, Jakub Tarnawski, Yihao Zhang

Proceedings of the 61st IEEE Annual Symposium on Foundations of Computer Science, 2020

Locally Private Hypothesis Selection.

Sivakanth Gopi, Gautam Kamath, Janardhan Kulkarni, Aleksandar Nikolov, Zhiwei Steven Wu, Huanyu Zhang

Proceedings of the Conference on Learning Theory, 2020

On the Facility Location Problem in Online and Dynamic Models.

Xiangyu Guo, Janardhan Kulkarni, Shi Li, Jiayi Xian

Proceedings of the Approximation, 2020

2019

Tight Bounds for Online Vector Scheduling.

Sungjin Im, Nathaniel Kell, Janardhan Kulkarni, Debmalya Panigrahi

SIAM J. Comput., 2019

Fully Dynamic (Δ+1)-Coloring in Constant Update Time.

Sayan Bhattacharya, Fabrizio Grandoni, Janardhan Kulkarni, Quanquan C. Liu, Shay Solomon

CoRR, 2019

Online Geometric Discrepancy for Stochastic Arrivals with Applications to Envy Minimization.

Haotian Jiang, Janardhan Kulkarni, Sahil Singla

CoRR, 2019

Non-clairvoyantly Scheduling to Minimize Convex Functions.

Kyle Fox, Sungjin Im, Janardhan Kulkarni, Benjamin Moseley

Algorithmica, 2019

Lift and Project Algorithms for Precedence Constrained Scheduling to Minimize Completion Time.

Shashwat Garg, Janardhan Kulkarni, Shi Li

Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2019

A Polynomial Time Constant Approximation For Minimizing Total Weighted Flow-time.

Uriel Feige, Janardhan Kulkarni, Shi Li

Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2019

Deterministically Maintaining a (2 + ∊)-Approximate Minimum Vertex Cover in O(1/∊2) Amortized Update Time.

Sayan Bhattacharya, Janardhan Kulkarni

Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2019

Locally Private Gaussian Estimation.

Matthew Joseph, Janardhan Kulkarni, Jieming Mao, Zhiwei Steven Wu

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors.

Joshua Allen, Bolin Ding, Janardhan Kulkarni, Harsha Nori, Olga Ohrimenko, Sergey Yekhanin

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Competitive Algorithms from Competitive Equilibria: Non-Clairvoyant Scheduling under Polyhedral Constraints.

Sungjin Im, Janardhan Kulkarni, Kamesh Munagala

J. ACM, 2018

Deterministically Maintaining a (2+ε)-Approximate Minimum Vertex Cover in O(1/ε²) Amortized Update Time.

Sayan Bhattacharya, Janardhan Kulkarni

CoRR, 2018

A Unified Rounding Algorithm For Unrelated Machines Scheduling Problems.

Nikhil R. Devanur, Janardhan Kulkarni

Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures, 2018

Flow-time Optimization for Concurrent Open-Shop and Precedence Constrained Scheduling Models.

Janardhan Kulkarni, Shi Li

Proceedings of the Approximation, 2018

2017

Truth and Regret in Online Scheduling.

Shuchi Chawla, Nikhil R. Devanur, Janardhan Kulkarni, Rad Niazadeh

Proceedings of the 2017 ACM Conference on Economics and Computation, 2017

Collecting Telemetry Data Privately.

Bolin Ding, Janardhan Kulkarni, Sergey Yekhanin

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Minimum Birkhoff-von Neumann Decomposition.

Janardhan Kulkarni, Euiwoong Lee, Mohit Singh

Proceedings of the Integer Programming and Combinatorial Optimization, 2017

2016

Do the Hard Stuff First: Scheduling Dependent Computations in Data-Analytics Clusters.

Robert Grandl, Srikanth Kandula, Sriram Rao, Aditya Akella, Janardhan Kulkarni

CoRR, 2016

Fair Online Scheduling for Selfish Jobs on Heterogeneous Machines.

Sungjin Im, Janardhan Kulkarni

Proceedings of the 28th ACM Symposium on Parallelism in Algorithms and Architectures, 2016

ProjecToR: Agile Reconfigurable Data Center Interconnect.

Monia Ghobadi, Ratul Mahajan, Amar Phanishayee, Nikhil R. Devanur, Janardhan Kulkarni, Gireeja Ranade, Pierre-Alexandre Blanche, Houman Rastegarfar, Madeleine Glick, Daniel C. Kilper

Proceedings of the ACM SIGCOMM 2016 Conference, Florianopolis, Brazil, August 22-26, 2016, 2016

Morpheus: Towards Automated SLOs for Enterprise Clusters.

Sangeetha Abdu Jyothi, Carlo Curino, Ishai Menache, Shravan Matthur Narayanamurthy, Alexey Tumanov, Jonathan Yaniv, Ruslan Mavlyutov, Iñigo Goiri, Subru Krishnan, Janardhan Kulkarni, Sriram Rao

Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation, 2016

GRAPHENE: Packing and Dependency-Aware Scheduling for Data-Parallel Clusters.

Robert Grandl, Srikanth Kandula, Sriram Rao, Aditya Akella, Janardhan Kulkarni

Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation, 2016

Competitive Analysis of Constrained Queueing Systems.

Sungjin Im, Janardhan Kulkarni, Kamesh Munagala

Proceedings of the 43rd International Colloquium on Automata, Languages, and Programming, 2016

A Competitive Flow Time Algorithm for Heterogeneous Clusters Under Polytope Constraints.

Sungjin Im, Janardhan Kulkarni, Benjamin Moseley, Kamesh Munagala

Proceedings of the Approximation, 2016

2015

Dynamic Coordination Mechanisms: [Extended Abstract].

Janardhan Kulkarni, Vahab S. Mirrokni

SIGMETRICS Perform. Evaluation Rev., 2015

Minimizing Flow-Time on Unrelated Machines.

Nikhil Bansal, Janardhan Kulkarni

Proceedings of the Forty-Seventh Annual ACM on Symposium on Theory of Computing, 2015

Temporal Fairness of Round Robin: Competitive Analysis for Lk-norms of Flow Time.

Sungjin Im, Janardhan Kulkarni, Benjamin Moseley

Proceedings of the 27th ACM on Symposium on Parallelism in Algorithms and Architectures, 2015

Robust Price of Anarchy Bounds via LP and Fenchel Duality.

Janardhan Kulkarni, Vahab S. Mirrokni

Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 2015

Competitive Flow Time Algorithms for Polyhedral Scheduling.

Sungjin Im, Janardhan Kulkarni, Kamesh Munagala

Proceedings of the IEEE 56th Annual Symposium on Foundations of Computer Science, 2015

2014

Coordination mechanisms from (almost) all scheduling policies.

Sayan Bhattacharya, Sungjin Im, Janardhan Kulkarni, Kamesh Munagala

Proceedings of the Innovations in Theoretical Computer Science, 2014

Coordination Mechanisms for Selfish Routing over Time on a Tree.

Sayan Bhattacharya, Janardhan Kulkarni, Vahab S. Mirrokni

Proceedings of the Automata, Languages, and Programming - 41st International Colloquium, 2014

SelfishMigrate: A Scalable Algorithm for Non-clairvoyantly Scheduling Heterogeneous Processors.

Sungjin Im, Janardhan Kulkarni, Kamesh Munagala, Kirk Pruhs

Proceedings of the 55th IEEE Annual Symposium on Foundations of Computer Science, 2014

2013

Near-optimal multi-unit auctions with ordered bidders.

Sayan Bhattacharya, Elias Koutsoupias, Janardhan Kulkarni, Stefano Leonardi, Tim Roughgarden, Xiaoming Xu

Proceedings of the fourteenth ACM Conference on Electronic Commerce, 2013

Online Non-clairvoyant Scheduling to Simultaneously Minimize All Convex Functions.

Kyle Fox, Sungjin Im, Janardhan Kulkarni, Benjamin Moseley

Proceedings of the Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, 2013

2012

Constant-Competitive Prior-Free Auction with Ordered Bidders

Sayan Bhattacharya, Janardhan Kulkarni, Xiaoming Xu

CoRR, 2012

Algorithms for Cost-Aware Scheduling.

Janardhan Kulkarni, Kamesh Munagala

Proceedings of the Approximation and Online Algorithms - 10th International Workshop, 2012

2011

On Allocations with Negative Externalities.

Sayan Bhattacharya, Janardhan Kulkarni, Kamesh Munagala, Xiaoming Xu

Proceedings of the Internet and Network Economics - 7th International Workshop, 2011

2010

New epsilon-net constructions.

Janardhan Kulkarni, Sathish Govindarajan

Proceedings of the 22nd Annual Canadian Conference on Computational Geometry, 2010

Small strong epsilon nets.

Pradeesha Ashok, Sathish Govindarajan, Janardhan Kulkarni

Proceedings of the 22nd Annual Canadian Conference on Computational Geometry, 2010

2008

On the Decidability of Model-Checking Information Flow Properties.

Deepak D'Souza, Raveendra Holla, Janardhan Kulkarni, Raghavendra K. Ramesh, Barbara Sprick

Proceedings of the Information Systems Security, 4th International Conference, 2008