Sanjay Krishnan
Sanjay Krishnan
Verified email at cs.uchicago.edu - Homepage
TitleCited byYear
Communication-efficient distributed dual coordinate ascent
M Jaggi, V Smith, M Takác, J Terhorst, S Krishnan, T Hofmann, MI Jordan
Advances in neural information processing systems, 3068-3076, 2014
1842014
A sample-and-clean framework for fast and accurate query processing on dirty data
J Wang, S Krishnan, MJ Franklin, K Goldberg, T Kraska, T Milo
Proceedings of the 2014 ACM SIGMOD international conference on Management of …, 2014
832014
ActiveClean: interactive data cleaning for statistical modeling
S Krishnan, J Wang, E Wu, MJ Franklin, K Goldberg
Proceedings of the VLDB Endowment 9 (12), 948-959, 2016
54*2016
Data cleaning: Overview and emerging challenges
X Chu, IF Ilyas, S Krishnan, J Wang
Proceedings of the 2016 International Conference on Management of Data, 2201 …, 2016
522016
Fine-grained partitioning for aggressive data skipping
L Sun, MJ Franklin, S Krishnan, RS Xin
Proceedings of the 2014 ACM SIGMOD international conference on Management of …, 2014
472014
Learning accurate kinematic control of cable-driven surgical robots using data cleaning and gaussian process regression
J Mahler, S Krishnan, M Laskey, S Sen, A Murali, B Kehoe, S Patil, ...
2014 IEEE International Conference on Automation Science and Engineering …, 2014
442014
A methodology for learning, analyzing, and mitigating social influence bias in recommender systems
S Krishnan, J Patel, MJ Franklin, K Goldberg
Proceedings of the 8th ACM Conference on Recommender systems, 137-144, 2014
36*2014
Transition state clustering: Unsupervised surgical trajectory segmentation for robot learning
S Krishnan, A Garg, S Patil, C Lea, G Hager, P Abbeel, K Goldberg
Robotics Research, 91-110, 2018
322018
Effect of user mobility on the performance of device-to-device networks with distributed caching
S Krishnan, HS Dhillon
IEEE Wireless Communications Letters 6 (2), 194-197, 2017
312017
Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations
M Laskey, C Chuck, J Lee, J Mahler, S Krishnan, K Jamieson, A Dragan, ...
2017 IEEE International Conference on Robotics and Automation (ICRA), 358-365, 2017
302017
Wisteria: Nurturing scalable data cleaning infrastructure
D Haas, S Krishnan, J Wang, MJ Franklin, E Wu
Proceedings of the VLDB Endowment 8 (12), 2004-2007, 2015
282015
Multi-level discovery of deep options
R Fox, S Krishnan, I Stoica, K Goldberg
arXiv preprint arXiv:1703.08294, 2017
272017
Tsc-dl: Unsupervised trajectory segmentation of multi-modal surgical demonstrations with deep learning
A Murali, A Garg, S Krishnan, FT Pokorny, P Abbeel, T Darrell, K Goldberg
2016 IEEE International Conference on Robotics and Automation (ICRA), 4150-4157, 2016
242016
Transition state clustering: Unsupervised surgical trajectory segmentation for robot learning
S Krishnan, A Garg, S Patil, C Lea, G Hager, P Abbeel, K Goldberg
The International Journal of Robotics Research 36 (13-14), 1595-1618, 2017
23*2017
Stale view cleaning: Getting fresh answers from stale materialized views
S Krishnan, J Wang, MJ Franklin, K Goldberg, T Kraska
Proceedings of the VLDB Endowment 8 (12), 1370-1381, 2015
222015
Comparing three online civic engagement platforms using the “spectrum of public participation” framework
M Nelimarkka, B Nonnecke, S Krishnan, T Aitamurto, D Catterson, ...
Proceedings of the Oxford Internet, Policy, and Politics Conference (IPP), 25-26, 2014
222014
Towards reliable interactive data cleaning: a user survey and recommendations
S Krishnan, D Haas, MJ Franklin, E Wu
Proceedings of the Workshop on Human-In-the-Loop Data Analytics, 9, 2016
202016
SampleClean: Fast and Reliable Analytics on Dirty Data.
S Krishnan, J Wang, MJ Franklin, K Goldberg, T Kraska, T Milo, E Wu
IEEE Data Eng. Bull. 38 (3), 59-75, 2015
202015
Distributed caching in device-to-device networks: A stochastic geometry perspective
S Krishnan, HS Dhillon
2015 49th Asilomar Conference on Signals, Systems and Computers, 1280-1284, 2015
192015
Ddco: Discovery of deep continuous options for robot learning from demonstrations
S Krishnan, R Fox, I Stoica, K Goldberg
arXiv preprint arXiv:1710.05421, 2017
182017
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