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2018
[b1]
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Sanjay Krishnan:
Hierarchical Deep Reinforcement Learning For Robotics and Data Science. University of California, Berkeley, USA, 2018

Journal Articles

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2024
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Gabriel Mersy, Zhuo Wang, Stavros Sintos, Sanjay Krishnan:
Optimizing Collections of Bloom Filters within a Space Budget. Proc. VLDB Endow. 17(11): 3551-3564 (2024)
2023
[j17]
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Shinan Liu, Tarun Mangla, Ted Shaowang, Jinjin Zhao, John Paparrizos, Sanjay Krishnan, Nick Feamster:
AMIR: Active Multimodal Interaction Recognition from Video and Network Traffic in Connected Environments. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 7(1): 21:1-21:26 (2023)
[j16]
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Bruno Barbarioli, Gabriel Mersy, Stavros Sintos, Sanjay Krishnan:
Hierarchical Residual Encoding for Multiresolution Time Series Compression. Proc. ACM Manag. Data 1(1): 99:1-99:26 (2023)
[j15]
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Raul Castro Fernandez, Aaron J. Elmore, Michael J. Franklin, Sanjay Krishnan, Chenhao Tan:
How Large Language Models Will Disrupt Data Management. Proc. VLDB Endow. 16(11): 3302-3309 (2023)
2022
[j14]
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Siyuan Xia, Zhiru Zhu, Chris Zhu, Jinjin Zhao, Kyle Chard, Aaron J. Elmore, Ian T. Foster, Michael J. Franklin, Sanjay Krishnan, Raul Castro Fernandez:
Data Station: Delegated, Trustworthy, and Auditable Computation to Enable Data-Sharing Consortia with a Data Escrow. Proc. VLDB Endow. 15(11): 3172-3185 (2022)
2021
[j13]
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Ted Shaowang, Nilesh Jain, Dennis Matthews, Sanjay Krishnan:
Declarative Data Serving: The Future of Machine Learning Inference on the Edge. Proc. VLDB Endow. 14(11): 2555-2562 (2021)
2020
[j12]
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Dixin Tang, Zechao Shang, Aaron J. Elmore, Sanjay Krishnan, Michael J. Franklin:
CrocodileDB in Action: Resource-Efficient Query Execution by Exploiting Time Slackness. Proc. VLDB Endow. 13(12): 2937-2940 (2020)
2019
[j11]
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Sanjay Krishnan, Animesh Garg, Richard Liaw, Brijen Thananjeyan, Lauren Miller, Florian T. Pokorny, Ken Goldberg:
SWIRL: A sequential windowed inverse reinforcement learning algorithm for robot tasks with delayed rewards. Int. J. Robotics Res. 38(2-3) (2019)
[j10]
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Dixin Tang, Zechao Shang, Aaron J. Elmore, Sanjay Krishnan, Michael J. Franklin:
Intermittent Query Processing. Proc. VLDB Endow. 12(11): 1427-1441 (2019)
[j9]
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Zongheng Yang, Eric Liang, Amog Kamsetty, Chenggang Wu, Yan Duan, Xi Chen, Pieter Abbeel, Joseph M. Hellerstein, Sanjay Krishnan, Ion Stoica:
Deep Unsupervised Cardinality Estimation. Proc. VLDB Endow. 13(3): 279-292 (2019)
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Sanjay Krishnan, Aaron J. Elmore, Michael J. Franklin, John Paparrizos, Zechao Shang, Adam Dziedzic, Rui Liu:
Artificial Intelligence in Resource-Constrained and Shared Environments. ACM SIGOPS Oper. Syst. Rev. 53(1): 1-6 (2019)
2017
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Sanjay Krishnan, Animesh Garg, Sachin Patil, Colin Lea, Gregory D. Hager, Pieter Abbeel, Ken Goldberg:
Transition state clustering: Unsupervised surgical trajectory segmentation for robot learning. Int. J. Robotics Res. 36(13-14): 1595-1618 (2017)
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Yeounoh Chung, Sanjay Krishnan, Tim Kraska:
A Data Quality Metric (DQM): How to Estimate the Number of Undetected Errors in Data Sets. Proc. VLDB Endow. 10(10): 1094-1105 (2017)
2016
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Sanjay Krishnan, Jiannan Wang, Eugene Wu, Michael J. Franklin, Ken Goldberg:
ActiveClean: Interactive Data Cleaning For Statistical Modeling. Proc. VLDB Endow. 9(12): 948-959 (2016)
2015
[j4]
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Sanjay Krishnan, Jiannan Wang, Michael J. Franklin, Ken Goldberg, Tim Kraska, Tova Milo, Eugene Wu:
SampleClean: Fast and Reliable Analytics on Dirty Data. IEEE Data Eng. Bull. 38(3): 59-75 (2015)
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Sanjay Krishnan, Jiannan Wang, Michael J. Franklin, Ken Goldberg, Tim Kraska:
Stale View Cleaning: Getting Fresh Answers from Stale Materialized Views. Proc. VLDB Endow. 8(12): 1370-1381 (2015)
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Daniel Haas, Sanjay Krishnan, Jiannan Wang, Michael J. Franklin, Eugene Wu:
Wisteria: Nurturing Scalable Data Cleaning Infrastructure. Proc. VLDB Endow. 8(12): 2004-2007 (2015)
2014
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Liwen Sun, Sanjay Krishnan, Reynold S. Xin, Michael J. Franklin:
A Partitioning Framework for Aggressive Data Skipping. Proc. VLDB Endow. 7(13): 1617-1620 (2014)

Conference and Workshop Papers

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2024
[c55]
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Rui Liu, Jun Hyuk Chang, Riki Otaki, Zhe Heng Eng, Aaron J. Elmore, Michael J. Franklin, Sanjay Krishnan:
Towards Resource-adaptive Query Execution in Cloud Native Databases. CIDR 2024
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Jinjin Zhao, Sanjay Krishnan:
Compression and In-Situ Query Processing for Fine-Grained Array Lineage. ICDE 2024: 3654-3667
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Rui Liu, Aaron J. Elmore, Michael J. Franklin, Sanjay Krishnan:
Riveter: Adaptive Query Suspension and Resumption Framework for Cloud Native Databases. ICDE 2024: 3975-3988
[c52]
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Sanjay Krishnan, Stavros Sintos:
Range Entropy Queries and Partitioning. ICDT 2024: 6:1-6:21
2023
[c51]
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Jinjin Zhao, Avigdor Gal, Sanjay Krishnan:
Data Makes Better Data Scientists. HILDA@SIGMOD 2023: 12:1-12:3
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Gabriel Mersy, Sanjay Krishnan:
Toward a Life Cycle Assessment for the Carbon Footprint of Data. HotCarbon 2023: 14:1-14:9
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Xi Liang, Stavros Sintos, Sanjay Krishnan:
JanusAQP: Efficient Partition Tree Maintenance for Dynamic Approximate Query Processing. ICDE 2023: 572-584
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Rui Liu, Aaron J. Elmore, Michael J. Franklin, Sanjay Krishnan:
Rotary: A Resource Arbitration Framework for Progressive Iterative Analytics. ICDE 2023: 2140-2153
2022
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Ted Shaowang, Xi Liang, Sanjay Krishnan:
Sensor fusion on the edge: initial experiments in the EdgeServe system. BiDEDE@SIGMOD 2022: 8:1-8:7
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Ted Shaowang, Jinjin Zhao, Stavros Sintos, Sanjay Krishnan:
Towards causal physical error discovery in video analytics systems. HILDA@SIGMOD 2022: 10:1-10:6
2021
[c45]
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John Paparrizos, Chunwei Liu, Bruno Barbarioli, Johnny Hwang, Ikraduya Edian, Aaron J. Elmore, Michael J. Franklin, Sanjay Krishnan:
VergeDB: A Database for IoT Analytics on Edge Devices. CIDR 2021
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Nalin Ranjan, Zechao Shang, Sanjay Krishnan, Aaron J. Elmore:
Version Reconciliation for Collaborative Databases. SoCC 2021: 473-488
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Cong Ding, Dixin Tang, Xi Liang, Aaron J. Elmore, Sanjay Krishnan:
CIAO: An Optimization Framework for Client-Assisted Data Loading. ICDE 2021: 1979-1984
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Rui Liu, Sanjay Krishnan, Aaron J. Elmore, Michael J. Franklin:
Understanding and optimizing packed neural network training for hyper-parameter tuning. DEEM@SIGMOD 2021: 3:1-3:11
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Xi Liang, Stavros Sintos, Zechao Shang, Sanjay Krishnan:
Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing. SIGMOD Conference 2021: 1129-1141
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Dixin Tang, Zechao Shang, William W. Ma, Aaron J. Elmore, Sanjay Krishnan:
Resource-efficient Shared Query Execution via Exploiting Time Slackness. SIGMOD Conference 2021: 1797-1810
2020
[c39]
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Zechao Shang, Xi Liang, Dixin Tang, Cong Ding, Aaron J. Elmore, Sanjay Krishnan, Michael J. Franklin:
CrocodileDB: Efficient Database Execution through Intelligent Deferment. CIDR 2020
[c38]
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Vanlin Sathya, Adam Dziedzic, Monisha Ghosh, Sanjay Krishnan:
Machine Learning based detection of multiple Wi-Fi BSSs for LTE-U CSAT. ICNC 2020: 596-601
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Xi Liang, Zechao Shang, Sanjay Krishnan, Aaron J. Elmore, Michael J. Franklin:
Fast and Reliable Missing Data Contingency Analysis with Predicate-Constraints. SIGMOD Conference 2020: 285-295
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Dixin Tang, Zechao Shang, Aaron J. Elmore, Sanjay Krishnan, Michael J. Franklin:
Thrifty Query Execution via Incrementability. SIGMOD Conference 2020: 1241-1256
2019
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Zisu Dong, Sanjay Krishnan, Sona Dolasia, Ashwin Balakrishna, Michael Danielczuk, Ken Goldberg:
Automating Planar Object Singulation by Linear Pushing with Single-point and Multi-point Contacts. CASE 2019: 1429-1436
[c34]
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Sanjay Krishnan, Adam Dziedzic, Aaron J. Elmore:
DeepLens: Towards a Visual Data Management System. CIDR 2019
[c33]
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Adam Dziedzic, John Paparrizos, Sanjay Krishnan, Aaron J. Elmore, Michael J. Franklin:
Band-limited Training and Inference for Convolutional Neural Networks. ICML 2019: 1745-1754
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Brijen Thananjeyan, Ajay Kumar Tanwani, Jessica J. Ji, Danyal Fer, Vatsal Patel, Sanjay Krishnan, Ken Goldberg:
Optimizing Robot-Assisted Surgery Suture Plans to Avoid Joint Limits and Singularities. ISMR 2019: 1-7
2018
[c31]
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Jessica J. Ji, Sanjay Krishnan, Vatsal Patel, Danyal Fer, Ken Goldberg:
Learning 2D Surgical Camera Motion From Demonstrations. CASE 2018: 35-42
[c30]
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Roy Fox, Richard Shin, Sanjay Krishnan, Ken Goldberg, Dawn Song, Ion Stoica:
Parametrized Hierarchical Procedures for Neural Programming. ICLR (Poster) 2018
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Daniel Seita, Sanjay Krishnan, Roy Fox, Stephen McKinley, John F. Canny, Ken Goldberg:
Fast and Reliable Autonomous Surgical Debridement with Cable-Driven Robots Using a Two-Phase Calibration Procedure. ICRA 2018: 6651-6658
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Vatsal Patel, Sanjay Krishnan, Aimee Goncalves, Carolyn Chen, Walter Doug Boyd, Ken Goldberg:
Using intermittent synchronization to compensate for rhythmic body motion during autonomous surgical cutting and debridement. ISMR 2018: 1-6
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Vatsal Patel, Sanjay Krishnan, Aimee Goncalves, Ken Goldberg:
SPRK: A low-cost stewart platform for motion study in surgical robotics. ISMR 2018: 1-6
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Ajay Kumar Tanwani, Jonathan Lee, Brijen Thananjeyan, Michael Laskey, Sanjay Krishnan, Roy Fox, Ken Goldberg, Sylvain Calinon:
Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models. WAFR 2018: 196-211
2017
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Carolyn Chen, Sanjay Krishnan, Michael Laskey, Roy Fox, Ken Goldberg:
An algorithm and user study for teaching bilateral manipulation via iterated best response demonstrations. CASE 2017: 151-158
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Caleb Chuck, Michael Laskey, Sanjay Krishnan, Ruta Joshi, Roy Fox, Ken Goldberg:
Statistical data cleaning for deep learning of automation tasks from demonstrations. CASE 2017: 1142-1149
[c23]
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Sanjay Krishnan:
RLEX: Saftey and Data Quality in Reinforcement Learning-based and Adaptive Systems. CIDR 2017
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Sanjay Krishnan, Roy Fox, Ion Stoica, Ken Goldberg:
DDCO: Discovery of Deep Continuous Options for Robot Learning from Demonstrations. CoRL 2017: 418-437
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Brandie Nonnecke, Shrestha Mohanty, Andrew Lee, Jonathan Lee, Sequoia Beckman, Justin Mi, Sanjay Krishnan, Rachel Edita Roxas, Nathaniel Oco, Camille Crittenden, Ken Goldberg:
Malasakit 1.0: A participatory online platform for crowdsourcing disaster risk reduction strategies in the philippines. GHTC 2017: 1-6
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Michael Laskey, Caleb Chuck, Jonathan Lee, Jeffrey Mahler, Sanjay Krishnan, Kevin G. Jamieson, Anca D. Dragan, Ken Goldberg:
Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations. ICRA 2017: 358-365
[c19]
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Brijen Thananjeyan, Animesh Garg, Sanjay Krishnan, Carolyn Chen, Lauren Miller, Ken Goldberg:
Multilateral surgical pattern cutting in 2D orthotropic gauze with deep reinforcement learning policies for tensioning. ICRA 2017: 2371-2378
[c18]
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Mo Zhou, Sanjay Krishnan, Jay Patel, Brandie Nonnecke, Camille Crittenden, Ken Goldberg:
M-CAFE 2.0: A Scalable Platform with Comparative Plots and Topic Tagging for Ongoing Course Feedback. SIGITE 2017: 159-164
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Sanjay Krishnan, Eugene Wu:
PALM: Machine Learning Explanations For Iterative Debugging. HILDA@SIGMOD 2017: 4:1-4:6
2016
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Adithyavairavan Murali, Animesh Garg, Sanjay Krishnan, Florian T. Pokorny, Pieter Abbeel, Trevor Darrell, Ken Goldberg:
TSC-DL: Unsupervised trajectory segmentation of multi-modal surgical demonstrations with Deep Learning. ICRA 2016: 4150-4157
[c15]
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Sanjay Krishnan, Daniel Haas, Michael J. Franklin, Eugene Wu:
Towards reliable interactive data cleaning: a user survey and recommendations. HILDA@SIGMOD 2016: 9
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Sanjay Krishnan, Jiannan Wang, Michael J. Franklin, Ken Goldberg, Tim Kraska:
PrivateClean: Data Cleaning and Differential Privacy. SIGMOD Conference 2016: 937-951
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Sanjay Krishnan, Michael J. Franklin, Ken Goldberg, Jiannan Wang, Eugene Wu:
ActiveClean: An Interactive Data Cleaning Framework For Modern Machine Learning. SIGMOD Conference 2016: 2117-2120
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Xu Chu, Ihab F. Ilyas, Sanjay Krishnan, Jiannan Wang:
Data Cleaning: Overview and Emerging Challenges. SIGMOD Conference 2016: 2201-2206
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Sanjay Krishnan, Animesh Garg, Richard Liaw, Brijen Thananjeyan, Lauren Miller, Florian T. Pokorny, Ken Goldberg:
SWIRL: A SequentialWindowed Inverse Reinforcement Learning Algorithm for Robot Tasks With Delayed Rewards. WAFR 2016: 672-687
2015
[c10]
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Brandie Nonnecke, Sanjay Krishnan, Jay Patel, Mo Zhou, Laura Byaruhanga, Dorothy Masinde, Maria Elena Meneses, Alejandro Martin del Campo, Camille Crittenden, Kenneth Y. Goldberg:
DevCAFE 1.0: A participatory platform for assessing development initiatives in the field. GHTC 2015: 437-444
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Sanjay Krishnan, Animesh Garg, Sachin Patil, Colin Lea, Gregory D. Hager, Pieter Abbeel, Ken Goldberg:
Transition State Clustering: Unsupervised Surgical Trajectory Segmentation for Robot Learning. ISRR (2) 2015: 91-110
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Mo Zhou, Alison Cliff, Allen Huang, Sanjay Krishnan, Brandie Nonnecke, Kanji Uchino, Samuel Joseph, Armando Fox, Ken Goldberg:
M-CAFE: Managing MOOC Student Feedback with Collaborative Filtering. L@S 2015: 309-312
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Jay Patel, Gil Gershoni, Sanjay Krishnan, Matti Nelimarkka, Brandie Nonnecke, Ken Goldberg:
A Case Study in Mobile-Optimized vs. Responsive Web Application Design. MobileHCI Adjunct 2015: 576-581
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Mo Zhou, Alison Cliff, Sanjay Krishnan, Brandie Nonnecke, Camille Crittenden, Kanji Uchino, Ken Goldberg:
M-CAFE 1.0: Motivating and Prioritizing Ongoing Student Feedback During MOOCs and Large on-Campus Courses using Collaborative Filtering. SIGITE 2015: 153-158
2014
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Jeffrey Mahler, Sanjay Krishnan, Michael Laskey, Siddarth Sen, Adithyavairavan Murali, Ben Kehoe, Sachin Patil, Jiannan Wang, Mike Franklin, Pieter Abbeel, Kenneth Y. Goldberg:
Learning accurate kinematic control of cable-driven surgical robots using data cleaning and Gaussian Process Regression. CASE 2014: 532-539
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Martin Jaggi, Virginia Smith, Martin Takác, Jonathan Terhorst, Sanjay Krishnan, Thomas Hofmann, Michael I. Jordan:
Communication-Efficient Distributed Dual Coordinate Ascent. NIPS 2014: 3068-3076
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Sanjay Krishnan, Jay Patel, Michael J. Franklin, Ken Goldberg:
A methodology for learning, analyzing, and mitigating social influence bias in recommender systems. RecSys 2014: 137-144
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Jiannan Wang, Sanjay Krishnan, Michael J. Franklin, Ken Goldberg, Tim Kraska, Tova Milo:
A sample-and-clean framework for fast and accurate query processing on dirty data. SIGMOD Conference 2014: 469-480
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Liwen Sun, Michael J. Franklin, Sanjay Krishnan, Reynold S. Xin:
Fine-grained partitioning for aggressive data skipping. SIGMOD Conference 2014: 1115-1126

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2023
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Rajesh Bordawekar, Cinzia Cappiello, Vasilis Efthymiou, Lisa Ehrlinger, Vijay Gadepally, Sainyam Galhotra, Sandra Geisler, Sven Groppe, Le Gruenwald, Alon Y. Halevy, Hazar Harmouch, Oktie Hassanzadeh, Ihab F. Ilyas, Ernesto Jiménez-Ruiz, Sanjay Krishnan, Tirthankar Lahiri, Guoliang Li, Jiaheng Lu, Wolfgang Mauerer, Umar Farooq Minhas, Felix Naumann, M. Tamer Özsu, El Kindi Rezig, Kavitha Srinivas, Michael Stonebraker, Satyanarayana R. Valluri, Maria-Esther Vidal, Haixun Wang, Jiannan Wang, Yingjun Wu, Xun Xue, Mohamed Zaït, Kai Zeng:
Joint Proceedings of Workshops at the 49th International Conference on Very Large Data Bases (VLDB 2023), Vancouver, Canada, August 28 - September 1, 2023. CEUR Workshop Proceedings 3462, CEUR-WS.org 2023 [contents]

Informal and Other Publications

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2024
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Shinan Liu, Ted Shaowang, Gerry Wan, Jeewon Chae, Jonatas Marques, Sanjay Krishnan, Nick Feamster:
ServeFlow: A Fast-Slow Model Architecture for Network Traffic Analysis. CoRR abs/2402.03694 (2024)
[i41]
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Pranav Subramaniam, Sanjay Krishnan:
Intent-Based Access Control: Using LLMs to Intelligently Manage Access Control. CoRR abs/2402.07332 (2024)
[i40]
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Jinjin Zhao, Ted Shaowang, Stavros Sintos, Sanjay Krishnan:
Towards Causal Physical Error Discovery in Video Analytics Systems. CoRR abs/2405.17686 (2024)
[i39]
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Jinjin Zhao, Avigdor Gal, Sanjay Krishnan:
Data Makes Better Data Scientists. CoRR abs/2405.17690 (2024)
[i38]
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Jinjin Zhao, Sanjay Krishnan:
Compression and In-Situ Query Processing for Fine-Grained Array Lineage. CoRR abs/2405.17701 (2024)
[i37]
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Jinjin Zhao, Avidgor Gal, Sanjay Krishnan:
A System for Quantifying Data Science Workflows with Fine-Grained Procedural Logging and a Pilot Study. CoRR abs/2405.17845 (2024)
2023
[i36]
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Ted Shaowang, Sanjay Krishnan:
EdgeServe: An Execution Layer for Decentralized Prediction. CoRR abs/2303.08028 (2023)
[i35]
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  - journals/corr/abs-2305-03842
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Siyuan Xia, Zhiru Zhu, Chris Zhu, Jinjin Zhao, Kyle Chard, Aaron J. Elmore, Ian T. Foster, Michael J. Franklin, Sanjay Krishnan, Raul Castro Fernandez:
Data Station: Delegated, Trustworthy, and Auditable Computation to Enable Data-Sharing Consortia with a Data Escrow. CoRR abs/2305.03842 (2023)
[i34]
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  - journals/corr/abs-2306-01268
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Edward C. Williams, Grace Su, Sandra R. Schloen, Miller C. Prosser, Susanne Paulus, Sanjay Krishnan:
DeepScribe: Localization and Classification of Elamite Cuneiform Signs Via Deep Learning. CoRR abs/2306.01268 (2023)
[i33]
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Deniz Turkcapar, Sanjay Krishnan:
Quantifying Uncertainty in Aggregate Queries over Integrated Datasets. CoRR abs/2309.05178 (2023)
[i32]
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Sanjay Krishnan, Stavros Sintos:
Range Entropy Queries and Partitioning. CoRR abs/2312.15959 (2023)
2022
[i31]
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Xi Liang, Stavros Sintos, Sanjay Krishnan:
JanusAQP: Efficient Partition Tree Maintenance for Dynamic Approximate Query Processing. CoRR abs/2204.09235 (2022)
2021
[i30]
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Cong Ding, Dixin Tang, Xi Liang, Aaron J. Elmore, Sanjay Krishnan:
CIAO: An Optimization Framework for Client-Assisted Data Loading. CoRR abs/2102.11793 (2021)
[i29]
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Xi Liang, Stavros Sintos, Zechao Shang, Sanjay Krishnan:
Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing. CoRR abs/2103.15994 (2021)
[i28]
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Nalin Ranjan, Zechao Shang, Aaron J. Elmore, Sanjay Krishnan:
Version Reconciliation for Collaborative Databases. CoRR abs/2110.01778 (2021)
[i27]
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Dale Decatur, Sanjay Krishnan:
VizExtract: Automatic Relation Extraction from Data Visualizations. CoRR abs/2112.03485 (2021)
2020
[i26]
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Rui Liu, Sanjay Krishnan, Aaron J. Elmore, Michael J. Franklin:
Understanding and Optimizing Packed Neural Network Training for Hyper-Parameter Tuning. CoRR abs/2002.02885 (2020)
[i25]
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Adam Dziedzic, Sanjay Krishnan:
An Empirical Evaluation of Perturbation-based Defenses. CoRR abs/2002.03080 (2020)
[i24]
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Adam Dziedzic, Vanlin Sathya, Muhammad Iqbal Rochman, Monisha Ghosh, Sanjay Krishnan:
Machine Learning enabled Spectrum Sharing in Dense LTE-U/Wi-Fi Coexistence Scenarios. CoRR abs/2003.13652 (2020)
[i23]
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Xi Liang, Zechao Shang, Aaron J. Elmore, Sanjay Krishnan, Michael J. Franklin:
Fast and Reliable Missing Data Contingency Analysis with Predicate-Constraints. CoRR abs/2004.04139 (2020)
[i22]
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  - journals/corr/abs-2009-00035
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Raul Castro Fernandez, Kyle Chard, Ben Blaiszik, Sanjay Krishnan, Aaron J. Elmore, Ziad Obermeyer, Josh Risley, Sendhil Mullainathan, Michael J. Franklin, Ian T. Foster:
The Data Station: Combining Data, Compute, and Market Forces. CoRR abs/2009.00035 (2020)
2019
[i21]
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Xi Liang, Aaron J. Elmore, Sanjay Krishnan:
Opportunistic View Materialization with Deep Reinforcement Learning. CoRR abs/1903.01363 (2019)
[i20]
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  - journals/corr/abs-1904-11827
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Sanjay Krishnan, Eugene Wu:
AlphaClean: Automatic Generation of Data Cleaning Pipelines. CoRR abs/1904.11827 (2019)
[i19]
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Zongheng Yang, Eric Liang, Amog Kamsetty, Chenggang Wu, Yan Duan, Xi Chen, Pieter Abbeel, Joseph M. Hellerstein, Sanjay Krishnan, Ion Stoica:
Selectivity Estimation with Deep Likelihood Models. CoRR abs/1905.04278 (2019)
[i18]
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  - journals/corr/abs-1911-09287
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Adam Dziedzic, John Paparrizos, Sanjay Krishnan, Aaron J. Elmore, Michael J. Franklin:
Band-limited Training and Inference for Convolutional Neural Networks. CoRR abs/1911.09287 (2019)
[i17]
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Vanlin Sathya, Adam Dziedzic, Monisha Ghosh, Sanjay Krishnan:
Machine Learning based detection of multiple Wi-Fi BSSs for LTE-U CSAT. CoRR abs/1911.09292 (2019)
2018
[i16]
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  - journals/corr/abs-1808-03196
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Sanjay Krishnan, Zongheng Yang, Ken Goldberg, Joseph M. Hellerstein, Ion Stoica:
Learning to Optimize Join Queries With Deep Reinforcement Learning. CoRR abs/1808.03196 (2018)
[i15]
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Ajay Kumar Tanwani, Jonathan Lee, Brijen Thananjeyan, Michael Laskey, Sanjay Krishnan, Roy Fox, Ken Goldberg, Sylvain Calinon:
Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models. CoRR abs/1811.07489 (2018)
[i14]
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Sanjay Krishnan, Adam Dziedzic, Aaron J. Elmore:
DeepLens: Towards a Visual Data Management System. CoRR abs/1812.07607 (2018)
2017
[i13]
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  - journals/corr/FoxKSG17
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Roy Fox, Sanjay Krishnan, Ion Stoica, Ken Goldberg:
Multi-Level Discovery of Deep Options. CoRR abs/1703.08294 (2017)
[i12]
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  - journals/corr/abs-1709-06668
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Daniel Seita, Sanjay Krishnan, Roy Fox, Stephen McKinley, John F. Canny, Ken Goldberg:
Fast and Reliable Autonomous Surgical Debridement with Cable-Driven Robots Using a Two-Phase Calibration Procedure. CoRR abs/1709.06668 (2017)
[i11]
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  - journals/corr/abs-1710-05421
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Sanjay Krishnan, Roy Fox, Ion Stoica, Ken Goldberg:
DDCO: Discovery of Deep Continuous Options forRobot Learning from Demonstrations. CoRR abs/1710.05421 (2017)
[i10]
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  - journals/corr/abs-1711-01299
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Sanjay Krishnan, Michael J. Franklin, Ken Goldberg, Eugene Wu:
BoostClean: Automated Error Detection and Repair for Machine Learning. CoRR abs/1711.01299 (2017)
[i9]
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  - journals/corr/abs-1711-01503
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Richard Liaw, Sanjay Krishnan, Animesh Garg, Daniel Crankshaw, Joseph E. Gonzalez, Ken Goldberg:
Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning. CoRR abs/1711.01503 (2017)
[i8]
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  - journals/corr/abs-1712-02917
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Vatsal Patel, Sanjay Krishnan, Aimee Goncalves, Carolyn Chen, Walter Doug Boyd, Ken Goldberg:
Using Intermittent Synchronization to Compensate for Rhythmic Body Motion During Autonomous Surgical Cutting and Debridement. CoRR abs/1712.02917 (2017)
[i7]
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  - journals/corr/abs-1712-02923
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Vatsal Patel, Sanjay Krishnan, Aimee Goncalves, Ken Goldberg:
SPRK: A Low-Cost Stewart Platform For Motion Study In Surgical Robotics. CoRR abs/1712.02923 (2017)
2016
[i6]
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Sanjay Krishnan, Jiannan Wang, Eugene Wu, Michael J. Franklin, Ken Goldberg:
ActiveClean: Interactive Data Cleaning While Learning Convex Loss Models. CoRR abs/1601.03797 (2016)
[i5]
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Sanjay Krishnan, Animesh Garg, Richard Liaw, Lauren Miller, Florian T. Pokorny, Ken Goldberg:
HIRL: Hierarchical Inverse Reinforcement Learning for Long-Horizon Tasks with Delayed Rewards. CoRR abs/1604.06508 (2016)
[i4]
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  - journals/corr/LaskeyCLMKJDG16
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Michael Laskey, Caleb Chuck, Jonathan Lee, Jeffrey Mahler, Sanjay Krishnan, Kevin G. Jamieson, Anca D. Dragan, Kenneth Y. Goldberg:
Comparing Human-Centric and Robot-Centric Sampling for Robot Deep Learning from Demonstrations. CoRR abs/1610.00850 (2016)
[i3]
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  - journals/corr/ChungKK16
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Yeounoh Chung, Sanjay Krishnan, Tim Kraska:
A Data Quality Metric (DQM): How to Estimate The Number of Undetected Errors in Data Sets. CoRR abs/1611.04878 (2016)
2015
[i2]
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  - journals/corr/KrishnanWFGK15
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Sanjay Krishnan, Jiannan Wang, Michael J. Franklin, Ken Goldberg, Tim Kraska:
Stale View Cleaning: Getting Fresh Answers from Stale Materialized Views. CoRR abs/1509.07454 (2015)
2014
[i1]
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  - journals/corr/JaggiSTTKHJ14
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Martin Jaggi, Virginia Smith, Martin Takác, Jonathan Terhorst, Sanjay Krishnan, Thomas Hofmann, Michael I. Jordan:
Communication-Efficient Distributed Dual Coordinate Ascent. CoRR abs/1409.1458 (2014)

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