S. Krishnan

Most-cited papers

Data Cleaning: Overview and Emerging Challenges
Xu Chu, Ihab F. Ilyas, S. Krishnan, Jiannan Wang
2016SIGMOD Conference582 citations
Semantic Scholar
Communication-Efficient Distributed Dual Coordinate Ascent
Martin Jaggi, Virginia Smith, Martin Takác, Jonathan Terhorst +3 more
2014Neural Information Processing Systems364 citations
Semantic Scholar
ActiveClean: Interactive Data Cleaning For Statistical Modeling
S. Krishnan, Jiannan Wang, Eugene Wu, M. Franklin +1 more
2016Proceedings of the VLDB Endowment312 citations
Semantic Scholar
Learning to Optimize Join Queries With Deep Reinforcement Learning
S. Krishnan, Zong-Heng Yang, Ken Goldberg, Joseph M Hellerstein +1 more
2018arXiv.org265 citations
Semantic Scholar
Deep Unsupervised Cardinality Estimation
Zong-Heng Yang, Eric Liang, Amog Kamsetty, Chenggang Wu +6 more
2019Proceedings of the VLDB Endowment263 citations Open access
Semantic Scholar
Transition state clustering: Unsupervised surgical trajectory segmentation for robot learning
S. Krishnan, Animesh Garg, S. Patil, Colin S. Lea +3 more
2017International Symposium of Robotics Research160 citations Open access
Semantic Scholar
Multilateral surgical pattern cutting in 2D orthotropic gauze with deep reinforcement learning policies for tensioning
Brijen Thananjeyan, Animesh Garg, S. Krishnan, Carolyn L. Chen +2 more
2017IEEE International Conference on Robotics and Automation148 citations
Semantic Scholar
Multi-Level Discovery of Deep Options
Roy Fox, S. Krishnan, Ion Stoica, Ken Goldberg
2017arXiv.org136 citations
Semantic Scholar
A sample-and-clean framework for fast and accurate query processing on dirty data
Jiannan Wang, S. Krishnan, M. Franklin, Ken Goldberg +2 more
2014SIGMOD Conference127 citations
Semantic Scholar
Fine-grained partitioning for aggressive data skipping
Liwen Sun, M. Franklin, S. Krishnan, R. Xin
2014SIGMOD Conference126 citations
Semantic Scholar
BoostClean: Automated Error Detection and Repair for Machine Learning
S. Krishnan, M. Franklin, Ken Goldberg, Eugene Wu
2017arXiv.org123 citations
Semantic Scholar
A methodology for learning, analyzing, and mitigating social influence bias in recommender systems
S. Krishnan, Jay Patel, M. Franklin, Ken Goldberg
2014ACM Conference on Recommender Systems97 citations
Semantic Scholar
DDCO: Discovery of Deep Continuous Options for Robot Learning from Demonstrations
S. Krishnan, Roy Fox, Ion Stoica, Ken Goldberg
2017Conference on Robot Learning91 citations
Semantic Scholar
PALM: Machine Learning Explanations For Iterative Debugging
S. Krishnan, Eugene Wu
2017HILDA@SIGMOD87 citations
Semantic Scholar
Learning accurate kinematic control of cable-driven surgical robots using data cleaning and Gaussian Process Regression
Jeffrey Mahler, S. Krishnan, Michael Laskey, Siddarth Sen +7 more
20142014 IEEE International Conference on Automation Science and Engineering (CASE)85 citations
Semantic Scholar
Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations
Michael Laskey, Caleb Chuck, Jonathan N. Lee, Jeffrey Mahler +4 more
2016IEEE International Conference on Robotics and Automation80 citations Open access
Semantic Scholar
SWIRL: A sequential windowed inverse reinforcement learning algorithm for robot tasks with delayed rewards
S. Krishnan, Animesh Garg, Richard Liaw, Brijen Thananjeyan +3 more
2018Int. J. Robotics Res.79 citations
Semantic Scholar
Fast and Reliable Autonomous Surgical Debridement with Cable-Driven Robots Using a Two-Phase Calibration Procedure
Daniel Seita, S. Krishnan, Roy Fox, Stephen McKinley +2 more
2017IEEE International Conference on Robotics and Automation78 citations Open access
Semantic Scholar
TSC-DL: Unsupervised trajectory segmentation of multi-modal surgical demonstrations with Deep Learning
Adithyavairavan Murali, Animesh Garg, S. Krishnan, Florian T. Pokorny +3 more
2016IEEE International Conference on Robotics and Automation78 citations
Semantic Scholar
ActiveClean: An Interactive Data Cleaning Framework For Modern Machine Learning
S. Krishnan, M. Franklin, Ken Goldberg, Jiannan Wang +1 more
2016SIGMOD Conference72 citations Open access
Semantic Scholar
Towards reliable interactive data cleaning: a user survey and recommendations
S. Krishnan, D. Haas, M. Franklin, Eugene Wu
2016HILDA '1672 citations
Semantic Scholar
Band-limited Training and Inference for Convolutional Neural Networks
Adam Dziedzic, John Paparrizos, S. Krishnan, Aaron J. Elmore +1 more
2019International Conference on Machine Learning69 citations
Semantic Scholar
AlphaClean: Automatic Generation of Data Cleaning Pipelines
S. Krishnan, Eugene Wu
2019arXiv.org64 citations
Semantic Scholar
VergeDB: A Database for IoT Analytics on Edge Devices
John Paparrizos, Chunwei Liu, Bruno Barbarioli, John Hwang +4 more
2021Conference on Innovative Data Systems Research63 citations
Semantic Scholar
SampleClean: Fast and Reliable Analytics on Dirty Data
S. Krishnan, Jiannan Wang, M. Franklin, Ken Goldberg +3 more
2015IEEE Data Engineering Bulletin61 citations
Semantic Scholar
Comparing Three Online Civic Engagement Platforms using the “ Spectrum of Public Participation ” Framework
Matti Nelimarkka, Brandie Nonnecke, S. Krishnan, Tanja Aitamurto +9 more
201451 citations
Semantic Scholar
HIRL: Hierarchical Inverse Reinforcement Learning for Long-Horizon Tasks with Delayed Rewards
S. Krishnan, Animesh Garg, Richard Liaw, Lauren Miller +2 more
2016arXiv.org45 citations
Semantic Scholar
Opportunistic View Materialization with Deep Reinforcement Learning
Xi Liang, Aaron J. Elmore, S. Krishnan
2019arXiv.org43 citations
Semantic Scholar
Wisteria: Nurturing Scalable Data Cleaning Infrastructure
D. Haas, S. Krishnan, Jiannan Wang, M. Franklin +1 more
2015Proceedings of the VLDB Endowment43 citations
Semantic Scholar
PrivateClean: Data Cleaning and Differential Privacy
S. Krishnan, Jiannan Wang, M. Franklin, Ken Goldberg +1 more
2016SIGMOD Conference38 citations
Semantic Scholar
Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing
Xi Liang, Stavros Sintos, Zechao Shang, S. Krishnan
2021SIGMOD Conference35 citations Open access
Semantic Scholar
Learning 2D Surgical Camera Motion From Demonstrations
Jessica J. Ji, S. Krishnan, Vatsal Patel, Danyal Fer +1 more
20182018 IEEE 14th International Conference on Automation Science and Engineering (CASE)31 citations
Semantic Scholar
Parametrized Hierarchical Procedures for Neural Programming
Roy Fox, Richard Shin, S. Krishnan, Ken Goldberg +2 more
2018International Conference on Learning Representations30 citations
Semantic Scholar
ActiveClean: Interactive Data Cleaning While Learning Convex Loss Models
S. Krishnan, Jiannan Wang, Eugene Wu, M. Franklin +1 more
2016arXiv.org29 citations
Semantic Scholar
Artificial Intelligence in Resource-Constrained and Shared Environments
S. Krishnan, Aaron J. Elmore, M. Franklin, John Paparrizos +3 more
2019ACM SIGOPS Operating Systems Review28 citations
Semantic Scholar
Stale View Cleaning: Getting Fresh Answers from Stale Materialized Views
S. Krishnan, Jiannan Wang, M. Franklin, Ken Goldberg +1 more
2015Proceedings of the VLDB Endowment28 citations Open access
Semantic Scholar
DeepLens: Towards a Visual Data Management System
S. Krishnan, Adam Dziedzic, Aaron J. Elmore
2018Conference on Innovative Data Systems Research26 citations
Semantic Scholar
Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning
Richard Liaw, S. Krishnan, Animesh Garg, D. Crankshaw +2 more
2017arXiv.org26 citations
Semantic Scholar
SPRK: A low-cost stewart platform for motion study in surgical robotics
Vatsal Patel, S. Krishnan, A. Goncalves, Ken Goldberg
2017International Symposium on Medical Robotics22 citations Open access
Semantic Scholar
A Data Quality Metric (DQM): How to Estimate the Number of Undetected Errors in Data Sets
Yeounoh Chung, S. Krishnan, Tim Kraska
2016Proceedings of the VLDB Endowment22 citations
Semantic Scholar
Machine Learning Enabled Spectrum Sharing in Dense LTE-U/Wi-Fi Coexistence Scenarios
Adam Dziedzic, Vanlin Sathya, Muhammad Iqbal Rochman, M. Ghosh +1 more
2020IEEE Open Journal of Vehicular Technology20 citations Open access
Semantic Scholar
Selectivity Estimation with Deep Likelihood Models
Zong-Heng Yang, Eric Liang, Amog Kamsetty, Chenggang Wu +6 more
2019arXiv.org18 citations
Semantic Scholar
Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models
A. Tanwani, Jonathan N. Lee, Brijen Thananjeyan, Michael Laskey +4 more
2018Workshop on the Algorithmic Foundations of Robotics18 citations Open access
Semantic Scholar
Intermittent Query Processing
Dixin Tang, Zechao Shang, Aaron J. Elmore, S. Krishnan +1 more
2019Proceedings of the VLDB Endowment17 citations
Semantic Scholar
Statistical data cleaning for deep learning of automation tasks from demonstrations
Caleb Chuck, Michael Laskey, S. Krishnan, Ruta Joshi +2 more
2017CASE16 citations
Semantic Scholar
Declarative Data Serving: The Future of Machine Learning Inference on the Edge
Ted Shaowang, Nilesh Jain, Dennis Matthews, S. Krishnan
2021Proceedings of the VLDB Endowment15 citations
Semantic Scholar
Fast and Reliable Missing Data Contingency Analysis with Predicate-Constraints
Xi Liang, Zechao Shang, S. Krishnan, Aaron J. Elmore +1 more
2020SIGMOD Conference15 citations Open access
Semantic Scholar
Understanding and optimizing packed neural network training for hyper-parameter tuning
Rui Liu, S. Krishnan, Aaron J. Elmore, M. Franklin
2020DEEM@SIGMOD15 citations Open access
Semantic Scholar
Thrifty Query Execution via Incrementability
Dixin Tang, Zechao Shang, Aaron J. Elmore, S. Krishnan +1 more
2020SIGMOD Conference14 citations Open access
Semantic Scholar
CrocodileDB: Efficient Database Execution through Intelligent Deferment
Zechao Shang, Xi Liang, Dixin Tang, Cong Ding +3 more
2020Conference on Innovative Data Systems Research13 citations
Semantic Scholar