Janardhan Kulkarni

132 papers A* 44A 2B 6Misc 1Journal 69Unranked 10
YearRankTypeTitle / Venue / Authors
2026 J jnl
Early Discoveries of Algorithmist I: Promise of Provable Algorithm Synthesis at Scale.
CoRR
Janardhan Kulkarni
2025 J jnl
Contextual Integrity in LLMs via Reasoning and Reinforcement Learning.
CoRR
Guangchen Lan, Huseyin A. Inan, Sahar Abdelnabi, Janardhan Kulkarni, Lukas Wutschitz, Reza Shokri, Christopher G. Brinton, Robert Sim
2025 A* conf
DiscQuant: A Quantization Method for Neural Networks Inspired by Discrepancy Theory.
COLT
Jerry Chee, Arturs Backurs, Rainie Heck, Li Zhang, Janardhan Kulkarni, Thomas Rothvoss, Sivakanth Gopi
2025 J jnl
DiscQuant: A Quantization Method for Neural Networks Inspired by Discrepancy Theory.
CoRR
Jerry Chee, Arturs Backurs, Rainie Heck, Li Zhang, Janardhan Kulkarni, Thomas Rothvoss, Sivakanth Gopi
2025 J jnl
Dyna-Mind: Learning to Simulate from Experience for Better AI Agents.
CoRR
Xiao Yu, Baolin Peng, Michel Galley, Hao Cheng, Qianhui Wu, Janardhan Kulkarni, Suman Nath, Zhou Yu, Jianfeng Gao
2025 J jnl
On the Emergence of Thinking in LLMs I: Searching for the Right Intuition.
CoRR
Guanghao Ye, Khiem Duc Pham, Xinzhi Zhang, Sivakanth Gopi, Baolin Peng, Beibin Li, Janardhan Kulkarni, Huseyin A. Inan
2025 J jnl
OptiMind: Teaching LLMs to Think Like Optimization Experts.
CoRR
Zeyi Chen, Xinzhi Zhang, Humishka Zope, Hugo Barbalho, Konstantina Mellou, Marco Molinaro, Janardhan Kulkarni, Ishai Menache, Sirui Li
2025 J jnl
SAS: Simulated Attention Score.
CoRR
Chuanyang Zheng, Jiankai Sun, Yihang Gao, Yuehao Wang, Peihao Wang, Jing Xiong, Liliang Ren, Hao Cheng, Janardhan Kulkarni, Yelong Shen, Atlas Wang, Mac Schwager, Anderson Schneider, Xiaodong Liu, Jianfeng Gao
2025 J jnl
Simulating Environments with Reasoning Models for Agent Training.
CoRR
Yuetai Li, Huseyin A. Inan, Xiang Yue, Wei-Ning Chen, Lukas Wutschitz, Janardhan Kulkarni, Radha Poovendran, Robert Sim, Saravan Rajmohan
2025 A* conf
Towards Foundation Models for Mixed Integer Linear Programming.
ICLR
Sirui Li, Janardhan Kulkarni, Ishai Menache, Cathy Wu, Beibin Li
2024 J jnl
Differentially Private Fine-tuning of Language Models.
J. Priv. Confidentiality
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
2024 A* conf
Differentially Private Synthetic Data via Foundation Model APIs 1: Images.
ICLR
Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Harsha Nori, Sergey Yekhanin
2024 J jnl
Differentially Private Training of Mixture of Experts Models.
CoRR
Pierre Tholoniat, Huseyin A. Inan, Janardhan Kulkarni, Robert Sim
2024 J jnl
Online Edge Coloring via Tree Recurrences and Correlation Decay.
SIAM J. Comput.
Janardhan Kulkarni, Yang P. Liu, Ashwin Sah, Mehtaab S. Sawhney, Jakub Tarnawski
2024 A* conf
Optimal Online Discrepancy Minimization.
STOC
Janardhan Kulkarni, Victor Reis, Thomas Rothvoss
2024 A* conf
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation.
ICLR
Xinyu Tang, Richard Shin, Huseyin A. Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Robert Sim
2024 A* conf
Privately Aligning Language Models with Reinforcement Learning.
ICLR
Fan Wu, Huseyin A. Inan, Arturs Backurs, Varun Chandrasekaran, Janardhan Kulkarni, Robert Sim
2024 J jnl
Selective Pre-training for Private Fine-tuning.
Trans. Mach. Learn. Res.
Da Yu, Sivakanth Gopi, Janardhan Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang
2024 J jnl
Towards Foundation Models for Mixed Integer Linear Programming.
CoRR
Sirui Li, Janardhan Kulkarni, Ishai Menache, Cathy Wu, Beibin Li
2024 J jnl
Workload-Aware Hardware Accelerator Mining for Distributed Deep Learning Training.
CoRR
Muhammad Adnan, Amar Phanishayee, Janardhan Kulkarni, Prashant J. Nair, Divya Mahajan
2023 — conf
Assessing Privacy Risks in Language Models: A Case Study on Summarization Tasks.
EMNLP (Findings)
Ruixiang Tang, Gord Lueck, Rodolfo Quispe, Huseyin A. Inan, Janardhan Kulkarni, Xia Hu
2023 J jnl
Assessing Privacy Risks in Language Models: A Case Study on Summarization Tasks.
CoRR
Ruixiang Tang, Gord Lueck, Rodolfo Quispe, Huseyin A. Inan, Janardhan Kulkarni, Xia Hu
2023 J jnl
Classification with Partially Private Features.
CoRR
Zeyu Shen, Anilesh K. Krishnaswamy, Janardhan Kulkarni, Kamesh Munagala
2023 J jnl
Differentially Private Synthetic Data via Foundation Model APIs 1: Images.
CoRR
Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Harsha Nori, Sergey Yekhanin
2023 A* conf
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping.
ICLR
Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian
2023 J jnl
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent.
Trans. Mach. Learn. Res.
Da Yu, Gautam Kamath, Janardhan Kulkarni, Tie-Yan Liu, Jian Yin, Huishuai Zhang
2023 J jnl
Optimal Online Discrepancy Minimization.
CoRR
Janardhan Kulkarni, Victor Reis, Thomas Rothvoss
2023 J jnl
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation.
CoRR
Xinyu Tang, Richard Shin, Huseyin A. Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Robert Sim
2023 J jnl
Privately Aligning Language Models with Reinforcement Learning.
CoRR
Fan Wu, Huseyin A. Inan, Arturs Backurs, Varun Chandrasekaran, Janardhan Kulkarni, Robert Sim
2023 J jnl
Selective Pre-training for Private Fine-tuning.
CoRR
Da Yu, Sivakanth Gopi, Janardhan Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang
2023 J jnl
TinyGSM: achieving >80% on GSM8k with small language models.
CoRR
Bingbin Liu, Sébastien Bubeck, Ronen Eldan, Janardhan Kulkarni, Yuanzhi Li, Anh Nguyen, Rachel Ward, Yi Zhang
2022 A* conf
Differentially Private Fine-tuning of Language Models.
ICLR
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
2022 A* conf
Differentially Private Model Compression.
NeurIPS
Fatemehsadat Mireshghallah, Arturs Backurs, Huseyin A. Inan, Lukas Wutschitz, Janardhan Kulkarni
2022 J jnl
Differentially Private Model Compression.
CoRR
Fatemehsadat Mireshghallah, Arturs Backurs, Huseyin A. Inan, Lukas Wutschitz, Janardhan Kulkarni
2022 J jnl
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping.
CoRR
Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian
2022 J jnl
Fully Dynamic (Δ +1)-Coloring in
ACM Trans. Algorithms
Sayan Bhattacharya, Fabrizio Grandoni, Janardhan Kulkarni, Quanquan C. Liu, Shay Solomon
2022 J jnl
Introduction to the Special Issue on ACM-SIAM Symposium on Discrete Algorithms (SODA) 2020.
ACM Trans. Algorithms
Gautam Kamath, Sepehr Assadi, Anne Driemel, Janardhan Kulkarni
2022 A* conf
Looking Beyond GPUs for DNN Scheduling on Multi-Tenant Clusters.
OSDI
Jayashree Mohan, Amar Phanishayee, Janardhan Kulkarni, Vijay Chidambaram
2022 A* conf
On the Hardness of Scheduling With Non-Uniform Communication Delays.
SODA
Sami Davies, Janardhan Kulkarni, Thomas Rothvoss, Sai Sandeep, Jakub Tarnawski, Yihao Zhang
2022 A* conf
Online edge coloring via tree recurrences and correlation decay.
STOC
Janardhan Kulkarni, Yang P. Liu, Ashwin Sah, Mehtaab Sawhney, Jakub Tarnawski
2022 J jnl
Per-Instance Privacy Accounting for Differentially Private Stochastic Gradient Descent.
CoRR
Da Yu, Gautam Kamath, Janardhan Kulkarni, Tie-Yan Liu, Jian Yin, Huishuai Zhang
2022 A* conf
When Does Differentially Private Learning Not Suffer in High Dimensions?
NeurIPS
Xuechen Li, Daogao Liu, Tatsunori B. Hashimoto, Huseyin A. Inan, Janardhan Kulkarni, Yin Tat Lee, Abhradeep Guha Thakurta
2022 J jnl
When Does Differentially Private Learning Not Suffer in High Dimensions?
CoRR
Xuechen Li, Daogao Liu, Tatsunori Hashimoto, Huseyin A. Inan, Janardhan Kulkarni, Yin Tat Lee, Abhradeep Guha Thakurta
2021 A* conf
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting.
ICML
Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan Kulkarni
2021 J jnl
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting.
CoRR
Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan Kulkarni
2021 A conf
Consistent k-Median: Simpler, Better and Robust.
AISTATS
Xiangyu Guo, Janardhan Kulkarni, Shi Li, Jiayi Xian
2021 A* conf
Differentially Private Correlation Clustering.
ICML
Mark Bun, Marek Eliás, Janardhan Kulkarni
2021 J jnl
Differentially Private Correlation Clustering.
CoRR
Mark Bun, Marek Eliás, Janardhan Kulkarni
2021 J jnl
Differentially Private Fine-tuning of Language Models.
CoRR
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
2021 J jnl
Differentially Private Set Union.
J. Priv. Confidentiality
Sivakanth Gopi, Pankaj Gulhane, Janardhan Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin
2021 A* conf
Differentially Private n-gram Extraction.
NeurIPS
Kunho Kim, Sivakanth Gopi, Janardhan Kulkarni, Sergey Yekhanin
2021 J jnl
Differentially Private n-gram Extraction.
CoRR
Kunho Kim, Sivakanth Gopi, Janardhan Kulkarni, Sergey Yekhanin
2021 A* conf
Fast and Memory Efficient Differentially Private-SGD via JL Projections.
NeurIPS
Zhiqi Bu, Sivakanth Gopi, Janardhan Kulkarni, Yin Tat Lee, Judy Hanwen Shen, Uthaipon Tantipongpipat
2021 J jnl
Fast and Memory Efficient Differentially Private-SGD via JL Projections.
CoRR
Zhiqi Bu, Sivakanth Gopi, Janardhan Kulkarni, Yin Tat Lee, Judy Hanwen Shen, Uthaipon Tantipongpipat
2021 J jnl
On the Hardness of Scheduling With Non-Uniform Communication Delays.
CoRR
Sami Davies, Janardhan Kulkarni, Thomas Rothvoss, Sai Sandeep, Jakub Tarnawski, Yihao Zhang
2021 J jnl
Online Edge Coloring via Tree Recurrences and Correlation Decay.
CoRR
Janardhan Kulkarni, Yang P. Liu, Ashwin Sah, Mehtaab Sawhney, Jakub Tarnawski
2021 A* conf
Private Non-smooth ERM and SCO in Subquadratic Steps.
NeurIPS
Janardhan Kulkarni, Yin Tat Lee, Daogao Liu
2021 J jnl
Private Non-smooth Empirical Risk Minimization and Stochastic Convex Optimization in Subquadratic Steps.
CoRR
Janardhan Kulkarni, Yin Tat Lee, Daogao Liu
2021 B conf
Scheduling Opportunistic Links in Two-Tiered Reconfigurable Datacenters.
SPAA
Janardhan Kulkarni, Stefan Schmid, Pawel Schmidt
2021 A* conf
Scheduling with Communication Delays via LP Hierarchies and Clustering II: Weighted Completion Times on Related Machines.
SODA
Sami Davies, Janardhan Kulkarni, Thomas Rothvoss, Jakub Tarnawski, Yihao Zhang
2021 J jnl
Synergy: Resource Sensitive DNN Scheduling in Multi-Tenant Clusters.
CoRR
Jayashree Mohan, Amar Phanishayee, Janardhan Kulkarni, Vijay Chidambaram
2020 A* conf
An Improved Algorithm for Incremental Cycle Detection and Topological Ordering in Sparse Graphs.
SODA
Sayan Bhattacharya, Janardhan Kulkarni
2020 J jnl
Consistent k-Median: Simpler, Better and Robust.
CoRR
Xiangyu Guo, Janardhan Kulkarni, Shi Li, Jiayi Xian
2020 A* conf
Differentially Private Release of Synthetic Graphs.
SODA
Marek Eliás, Michael Kapralov, Janardhan Kulkarni, Yin Tat Lee
2020 A* conf
Differentially Private Set Union.
ICML
Sivakanth Gopi, Pankaj Gulhane, Janardhan Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin
2020 J jnl
Differentially Private Set Union.
CoRR
Sivakanth Gopi, Pankaj Gulhane, Janardhan Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin
2020 A* conf
Hierarchy-Based Algorithms for Minimizing Makespan under Precedence and Communication Constraints.
SODA
Janardhan Kulkarni, Shi Li, Jakub Tarnawski, Minwei Ye
2020 J jnl
Hierarchy-Based Algorithms for Minimizing Makespan under Precedence and Communication Constraints.
CoRR
Janardhan Kulkarni, Shi Li, Jakub Tarnawski, Minwei Ye
2020 A* conf
Locally Private Hypothesis Selection.
COLT
Sivakanth Gopi, Gautam Kamath, Janardhan Kulkarni, Aleksandar Nikolov, Zhiwei Steven Wu, Huanyu Zhang
2020 J jnl
Locally Private Hypothesis Selection.
CoRR
Sivakanth Gopi, Gautam Kamath, Janardhan Kulkarni, Aleksandar Nikolov, Zhiwei Steven Wu, Huanyu Zhang
2020 — conf
On the Facility Location Problem in Online and Dynamic Models.
APPROX-RANDOM
Xiangyu Guo, Janardhan Kulkarni, Shi Li, Jiayi Xian
2020 A* conf
Parallel Batch-Dynamic Graphs: Algorithms and Lower Bounds.
SODA
Laxman Dhulipala, David Durfee, Janardhan Kulkarni, Richard Peng, Saurabh Sawlani, Xiaorui Sun
2020 J jnl
Prior-free multi-unit auctions with ordered bidders.
Theor. Comput. Sci.
Sayan Bhattacharya, Elias Koutsoupias, Janardhan Kulkarni, Stefano Leonardi, Tim Roughgarden, Xiaoming Xu
2020 A* conf
Privately Learning Markov Random Fields.
ICML
Huanyu Zhang, Gautam Kamath, Janardhan Kulkarni, Zhiwei Steven Wu
2020 J jnl
Privately Learning Markov Random Fields.
CoRR
Huanyu Zhang, Gautam Kamath, Janardhan Kulkarni, Zhiwei Steven Wu
2020 J jnl
Scheduling Opportunistic Links in Two-Tiered Reconfigurable Datacenters.
CoRR
Janardhan Kulkarni, Stefan Schmid, Pawel Schmidt
2020 A* conf
Scheduling with Communication Delays via LP Hierarchies and Clustering.
FOCS
Sami Davies, Janardhan Kulkarni, Thomas Rothvoss, Jakub Tarnawski, Yihao Zhang
2020 J jnl
Scheduling with Communication Delays via LP Hierarchies and Clustering.
CoRR
Sami Davies, Janardhan Kulkarni, Thomas Rothvoss, Jakub Tarnawski, Yihao Zhang
2020 J jnl
The Power of Recourse: Better Algorithms for Facility Location in Online and Dynamic Models.
CoRR
Xiangyu Guo, Janardhan Kulkarni, Shi Li, Jiayi Xian
2019 A* conf
A Polynomial Time Constant Approximation For Minimizing Total Weighted Flow-time.
SODA
Uriel Feige, Janardhan Kulkarni, Shi Li
2019 A* conf
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors.
NeurIPS
Joshua Allen, Bolin Ding, Janardhan Kulkarni, Harsha Nori, Olga Ohrimenko, Sergey Yekhanin
2019 A* conf
Deterministically Maintaining a (2 + ∊)-Approximate Minimum Vertex Cover in O(1/∊2) Amortized Update Time.
SODA
Sayan Bhattacharya, Janardhan Kulkarni
2019 J jnl
Fully Dynamic (Δ+1)-Coloring in Constant Update Time.
CoRR
Sayan Bhattacharya, Fabrizio Grandoni, Janardhan Kulkarni, Quanquan C. Liu, Shay Solomon
2019 A* conf
Lift and Project Algorithms for Precedence Constrained Scheduling to Minimize Completion Time.
SODA
Shashwat Garg, Janardhan Kulkarni, Shi Li
2019 A* conf
Locally Private Gaussian Estimation.
NeurIPS
Matthew Joseph, Janardhan Kulkarni, Jieming Mao, Zhiwei Steven Wu
2019 J jnl
Non-clairvoyantly Scheduling to Minimize Convex Functions.
Algorithmica
Kyle Fox, Sungjin Im, Janardhan Kulkarni, Benjamin Moseley
2019 J jnl
Online Geometric Discrepancy for Stochastic Arrivals with Applications to Envy Minimization.
CoRR
Haotian Jiang, Janardhan Kulkarni, Sahil Singla
2019 J jnl
Parallel Batch-Dynamic Graphs: Algorithms and Lower Bounds.
CoRR
David Durfee, Laxman Dhulipala, Janardhan Kulkarni, Richard Peng, Saurabh Sawlani, Xiaorui Sun
2019 J jnl
Tight Bounds for Online Vector Scheduling.
SIAM J. Comput.
Sungjin Im, Nathaniel Kell, Janardhan Kulkarni, Debmalya Panigrahi
2018 J jnl
A Polynomial Time Constant Approximation For Minimizing Total Weighted Flow-time.
CoRR
Uriel Feige, Janardhan Kulkarni, Shi Li
2018 B conf
A Unified Rounding Algorithm For Unrelated Machines Scheduling Problems.
SPAA
Nikhil R. Devanur, Janardhan Kulkarni
2018 J jnl
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors.
CoRR
Joshua Allen, Bolin Ding, Janardhan Kulkarni, Harsha Nori, Olga Ohrimenko, Sergey Yekhanin
2018 J jnl
An Improved Algorithm for Incremental Cycle Detection and Topological Ordering in Sparse Graphs.
CoRR
Sayan Bhattacharya, Janardhan Kulkarni
2018 J jnl
Competitive Algorithms from Competitive Equilibria: Non-Clairvoyant Scheduling under Polyhedral Constraints.
J. ACM
Sungjin Im, Janardhan Kulkarni, Kamesh Munagala
2018 J jnl
Deterministically Maintaining a (2+ε)-Approximate Minimum Vertex Cover in O(1/ε
CoRR
Sayan Bhattacharya, Janardhan Kulkarni
2018 J jnl
Flow-time Optimization For Concurrent Open-Shop and Precedence Constrained Scheduling Models.
CoRR
Janardhan Kulkarni, Shi Li
2018 — conf
Flow-time Optimization for Concurrent Open-Shop and Precedence Constrained Scheduling Models.
APPROX-RANDOM
Janardhan Kulkarni, Shi Li
2018 J jnl
Locally Private Gaussian Estimation.
CoRR
Matthew Joseph, Janardhan Kulkarni, Jieming Mao, Zhiwei Steven Wu
2017 — conf
Collecting Telemetry Data Privately.
NIPS
Bolin Ding, Janardhan Kulkarni, Sergey Yekhanin
2017 J jnl
Collecting Telemetry Data Privately.
CoRR
Bolin Ding, Janardhan Kulkarni, Sergey Yekhanin
2017 B conf
Minimum Birkhoff-von Neumann Decomposition.
IPCO
Janardhan Kulkarni, Euiwoong Lee, Mohit Singh
2017 A* conf
Truth and Regret in Online Scheduling.
EC
Shuchi Chawla, Nikhil R. Devanur, Janardhan Kulkarni, Rad Niazadeh
2017 J jnl
Truth and Regret in Online Scheduling.
CoRR
Shuchi Chawla, Nikhil R. Devanur, Janardhan Kulkarni, Rad Niazadeh
2016 — conf
A Competitive Flow Time Algorithm for Heterogeneous Clusters Under Polytope Constraints.
APPROX-RANDOM
Sungjin Im, Janardhan Kulkarni, Benjamin Moseley, Kamesh Munagala
2016 A* conf
Competitive Analysis of Constrained Queueing Systems.
ICALP
Sungjin Im, Janardhan Kulkarni, Kamesh Munagala
2016 J jnl
Do the Hard Stuff First: Scheduling Dependent Computations in Data-Analytics Clusters.
CoRR
Robert Grandl, Srikanth Kandula, Sriram Rao, Aditya Akella, Janardhan Kulkarni
2016 B conf
Fair Online Scheduling for Selfish Jobs on Heterogeneous Machines.
SPAA
Sungjin Im, Janardhan Kulkarni
2016 A* conf
GRAPHENE: Packing and Dependency-Aware Scheduling for Data-Parallel Clusters.
OSDI
Robert Grandl, Srikanth Kandula, Sriram Rao, Aditya Akella, Janardhan Kulkarni
2016 A* conf
Morpheus: Towards Automated SLOs for Enterprise Clusters.
OSDI
Sangeetha Abdu Jyothi, Carlo Curino, Ishai Menache, Shravan Matthur Narayanamurthy, Alexey Tumanov, Jonathan Yaniv, Ruslan Mavlyutov, Iñigo Goiri, Subru Krishnan, Janardhan Kulkarni, Sriram Rao
2016 A* conf
ProjecToR: Agile Reconfigurable Data Center Interconnect.
SIGCOMM
Monia Ghobadi, Ratul Mahajan, Amar Phanishayee, Nikhil R. Devanur, Janardhan Kulkarni, Gireeja Ranade, Pierre-Alexandre Blanche, Houman Rastegarfar, Madeleine Glick, Daniel C. Kilper
2015 A* conf
Competitive Flow Time Algorithms for Polyhedral Scheduling.
FOCS
Sungjin Im, Janardhan Kulkarni, Kamesh Munagala
2015 J jnl
Dynamic Coordination Mechanisms: [Extended Abstract].
SIGMETRICS Perform. Evaluation Rev.
Janardhan Kulkarni, Vahab S. Mirrokni
2015 A* conf
Minimizing Flow-Time on Unrelated Machines.
STOC
Nikhil Bansal, Janardhan Kulkarni
2015 A* conf
Robust Price of Anarchy Bounds via LP and Fenchel Duality.
SODA
Janardhan Kulkarni, Vahab S. Mirrokni
2015 B conf
Temporal Fairness of Round Robin: Competitive Analysis for Lk-norms of Flow Time.
SPAA
Sungjin Im, Janardhan Kulkarni, Benjamin Moseley
2015 A* conf
Tight Bounds for Online Vector Scheduling.
FOCS
Sungjin Im, Nathaniel Kell, Janardhan Kulkarni, Debmalya Panigrahi
2014 J jnl
Competitive Algorithms from Competitive Equilibria: Non-Clairvoyant Scheduling under Polyhedral Constraints.
CoRR
Sungjin Im, Janardhan Kulkarni, Kamesh Munagala
2014 A* conf
Competitive algorithms from competitive equilibria: non-clairvoyant scheduling under polyhedral constraints.
STOC
Sungjin Im, Janardhan Kulkarni, Kamesh Munagala
2014 — conf
Coordination Mechanisms for Selfish Routing over Time on a Tree.
ICALP (1)
Sayan Bhattacharya, Janardhan Kulkarni, Vahab S. Mirrokni
2014 A conf
Coordination mechanisms from (almost) all scheduling policies.
ITCS
Sayan Bhattacharya, Sungjin Im, Janardhan Kulkarni, Kamesh Munagala
2014 J jnl
Minimizing Flow-Time on Unrelated Machines.
CoRR
Nikhil Bansal, Janardhan Kulkarni
2014 J jnl
SELFISHMIGRATE: A Scalable Algorithm for Non-clairvoyantly Scheduling Heterogeneous Processors.
CoRR
Sungjin Im, Janardhan Kulkarni, Kamesh Munagala, Kirk Pruhs
2014 A* conf
SelfishMigrate: A Scalable Algorithm for Non-clairvoyantly Scheduling Heterogeneous Processors.
FOCS
Sungjin Im, Janardhan Kulkarni, Kamesh Munagala, Kirk Pruhs
2014 J jnl
Tight Bounds for Online Vector Scheduling.
CoRR
Sungjin Im, Nathaniel Kell, Janardhan Kulkarni, Debmalya Panigrahi
2013 A* conf
Near-optimal multi-unit auctions with ordered bidders.
EC
Sayan Bhattacharya, Elias Koutsoupias, Janardhan Kulkarni, Stefano Leonardi, Tim Roughgarden, Xiaoming Xu
2013 — conf
Online Non-clairvoyant Scheduling to Simultaneously Minimize All Convex Functions.
APPROX-RANDOM
Kyle Fox, Sungjin Im, Janardhan Kulkarni, Benjamin Moseley
2012 B conf
Algorithms for Cost-Aware Scheduling.
WAOA
Janardhan Kulkarni, Kamesh Munagala
2012 J jnl
Constant-Competitive Prior-Free Auction with Ordered Bidders
CoRR
Sayan Bhattacharya, Janardhan Kulkarni, Xiaoming Xu
2011 — conf
On Allocations with Negative Externalities.
WINE
Sayan Bhattacharya, Janardhan Kulkarni, Kamesh Munagala, Xiaoming Xu
2010 — conf
New epsilon-net constructions.
CCCG
Janardhan Kulkarni, Sathish Govindarajan
2010 — conf
Small strong epsilon nets.
CCCG
Pradeesha Ashok, Sathish Govindarajan, Janardhan Kulkarni
2008 Misc conf
On the Decidability of Model-Checking Information Flow Properties.
ICISS
Deepak D'Souza, Raveendra Holla, Janardhan Kulkarni, Raghavendra K. Ramesh, Barbara Sprick