Sanjay Krishnan

Orcid: 0000-0001-6968-4090

According to our database1, Sanjay Krishnan authored at least 89 papers between 2014 and 2024.

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Bibliography

2024
Intent-Based Access Control: Using LLMs to Intelligently Manage Access Control.
CoRR, 2024

ServeFlow: A Fast-Slow Model Architecture for Network Traffic Analysis.
CoRR, 2024

Range Entropy Queries and Partitioning.
Proceedings of the 27th International Conference on Database Theory, 2024

Towards Resource-adaptive Query Execution in Cloud Native Databases.
Proceedings of the 14th Conference on Innovative Data Systems Research, 2024

2023
AMIR: Active Multimodal Interaction Recognition from Video and Network Traffic in Connected Environments.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., March, 2023

How Large Language Models Will Disrupt Data Management.
Proc. VLDB Endow., 2023

Hierarchical Residual Encoding for Multiresolution Time Series Compression.
Proc. ACM Manag. Data, 2023

Quantifying Uncertainty in Aggregate Queries over Integrated Datasets.
CoRR, 2023

DeepScribe: Localization and Classification of Elamite Cuneiform Signs Via Deep Learning.
CoRR, 2023

EdgeServe: An Execution Layer for Decentralized Prediction.
CoRR, 2023

JanusAQP: Efficient Partition Tree Maintenance for Dynamic Approximate Query Processing.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Rotary: A Resource Arbitration Framework for Progressive Iterative Analytics.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Toward a Life Cycle Assessment for the Carbon Footprint of Data.
Proceedings of the 2nd Workshop on Sustainable Computer Systems, 2023

Data Makes Better Data Scientists.
Proceedings of the Workshop on Human-In-the-Loop Data Analytics, 2023

2022
Data Station: Delegated, Trustworthy, and Auditable Computation to Enable Data-Sharing Consortia with a Data Escrow.
Proc. VLDB Endow., 2022

Towards causal physical error discovery in video analytics systems.
Proceedings of the HILDA@SIGMOD 2022: Proceedings of the Workshop on Human-In-the-Loop Data Analytics, 2022

Sensor fusion on the edge: initial experiments in the EdgeServe system.
Proceedings of the BiDEDE '22: Proceedings of The International Workshop on Big Data in Emergent Distributed Environments, 2022

2021
Declarative Data Serving: The Future of Machine Learning Inference on the Edge.
Proc. VLDB Endow., 2021

VizExtract: Automatic Relation Extraction from Data Visualizations.
CoRR, 2021

Resource-efficient Shared Query Execution via Exploiting Time Slackness.
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing.
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

Understanding and optimizing packed neural network training for hyper-parameter tuning.
Proceedings of the Fifth Workshop on Data Management for End-To-End Machine Learning, 2021

CIAO: An Optimization Framework for Client-Assisted Data Loading.
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

Version Reconciliation for Collaborative Databases.
Proceedings of the SoCC '21: ACM Symposium on Cloud Computing, 2021

VergeDB: A Database for IoT Analytics on Edge Devices.
Proceedings of the 11th Conference on Innovative Data Systems Research, 2021

2020
CrocodileDB in Action: Resource-Efficient Query Execution by Exploiting Time Slackness.
Proc. VLDB Endow., 2020

The Data Station: Combining Data, Compute, and Market Forces.
CoRR, 2020

Machine Learning enabled Spectrum Sharing in Dense LTE-U/Wi-Fi Coexistence Scenarios.
CoRR, 2020

An Empirical Evaluation of Perturbation-based Defenses.
CoRR, 2020

Thrifty Query Execution via Incrementability.
Proceedings of the 2020 International Conference on Management of Data, 2020

Fast and Reliable Missing Data Contingency Analysis with Predicate-Constraints.
Proceedings of the 2020 International Conference on Management of Data, 2020

Machine Learning based detection of multiple Wi-Fi BSSs for LTE-U CSAT.
Proceedings of the International Conference on Computing, Networking and Communications, 2020

CrocodileDB: Efficient Database Execution through Intelligent Deferment.
Proceedings of the 10th Conference on Innovative Data Systems Research, 2020

2019
Artificial Intelligence in Resource-Constrained and Shared Environments.
ACM SIGOPS Oper. Syst. Rev., 2019

Deep Unsupervised Cardinality Estimation.
Proc. VLDB Endow., 2019

Intermittent Query Processing.
Proc. VLDB Endow., 2019

SWIRL: A sequential windowed inverse reinforcement learning algorithm for robot tasks with delayed rewards.
Int. J. Robotics Res., 2019

Selectivity Estimation with Deep Likelihood Models.
CoRR, 2019

AlphaClean: Automatic Generation of Data Cleaning Pipelines.
CoRR, 2019

Opportunistic View Materialization with Deep Reinforcement Learning.
CoRR, 2019

Optimizing Robot-Assisted Surgery Suture Plans to Avoid Joint Limits and Singularities.
Proceedings of the International Symposium on Medical Robotics, 2019

Band-limited Training and Inference for Convolutional Neural Networks.
Proceedings of the 36th International Conference on Machine Learning, 2019

DeepLens: Towards a Visual Data Management System.
Proceedings of the 9th Biennial Conference on Innovative Data Systems Research, 2019

Automating Planar Object Singulation by Linear Pushing with Single-point and Multi-point Contacts.
Proceedings of the 15th IEEE International Conference on Automation Science and Engineering, 2019

2018
Hierarchical Deep Reinforcement Learning For Robotics and Data Science.
PhD thesis, 2018

Learning to Optimize Join Queries With Deep Reinforcement Learning.
CoRR, 2018

Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models.
Proceedings of the Algorithmic Foundations of Robotics XIII, 2018

SPRK: A low-cost stewart platform for motion study in surgical robotics.
Proceedings of the International Symposium on Medical Robotics, 2018

Using intermittent synchronization to compensate for rhythmic body motion during autonomous surgical cutting and debridement.
Proceedings of the International Symposium on Medical Robotics, 2018

Fast and Reliable Autonomous Surgical Debridement with Cable-Driven Robots Using a Two-Phase Calibration Procedure.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Parametrized Hierarchical Procedures for Neural Programming.
Proceedings of the 6th International Conference on Learning Representations, 2018

Learning 2D Surgical Camera Motion From Demonstrations.
Proceedings of the 14th IEEE International Conference on Automation Science and Engineering, 2018

2017
A Data Quality Metric (DQM): How to Estimate the Number of Undetected Errors in Data Sets.
Proc. VLDB Endow., 2017

Transition state clustering: Unsupervised surgical trajectory segmentation for robot learning.
Int. J. Robotics Res., 2017

Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning.
CoRR, 2017

BoostClean: Automated Error Detection and Repair for Machine Learning.
CoRR, 2017

DDCO: Discovery of Deep Continuous Options forRobot Learning from Demonstrations.
CoRR, 2017

Multi-Level Discovery of Deep Options.
CoRR, 2017

PALM: Machine Learning Explanations For Iterative Debugging.
Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics, 2017

M-CAFE 2.0: A Scalable Platform with Comparative Plots and Topic Tagging for Ongoing Course Feedback.
Proceedings of the 18th Annual Conference on Information Technology Education and the 6th Annual Conference on Research in Information Technology, 2017

Multilateral surgical pattern cutting in 2D orthotropic gauze with deep reinforcement learning policies for tensioning.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Malasakit 1.0: A participatory online platform for crowdsourcing disaster risk reduction strategies in the philippines.
Proceedings of the IEEE Global Humanitarian Technology Conference, 2017

DDCO: Discovery of Deep Continuous Options for Robot Learning from Demonstrations.
Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

RLEX: Saftey and Data Quality in Reinforcement Learning-based and Adaptive Systems.
Proceedings of the 8th Biennial Conference on Innovative Data Systems Research, 2017

Statistical data cleaning for deep learning of automation tasks from demonstrations.
Proceedings of the 13th IEEE Conference on Automation Science and Engineering, 2017

An algorithm and user study for teaching bilateral manipulation via iterated best response demonstrations.
Proceedings of the 13th IEEE Conference on Automation Science and Engineering, 2017

2016
ActiveClean: Interactive Data Cleaning For Statistical Modeling.
Proc. VLDB Endow., 2016

ActiveClean: Interactive Data Cleaning While Learning Convex Loss Models.
CoRR, 2016

HIRL: Hierarchical Inverse Reinforcement Learning for Long-Horizon Tasks with Delayed Rewards.
CoRR, 2016

SWIRL: A SequentialWindowed Inverse Reinforcement Learning Algorithm for Robot Tasks With Delayed Rewards.
Proceedings of the Algorithmic Foundations of Robotics XII, 2016

PrivateClean: Data Cleaning and Differential Privacy.
Proceedings of the 2016 International Conference on Management of Data, 2016

Towards reliable interactive data cleaning: a user survey and recommendations.
Proceedings of the Workshop on Human-In-the-Loop Data Analytics, 2016

ActiveClean: An Interactive Data Cleaning Framework For Modern Machine Learning.
Proceedings of the 2016 International Conference on Management of Data, 2016

Data Cleaning: Overview and Emerging Challenges.
Proceedings of the 2016 International Conference on Management of Data, 2016

TSC-DL: Unsupervised trajectory segmentation of multi-modal surgical demonstrations with Deep Learning.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

2015
Stale View Cleaning: Getting Fresh Answers from Stale Materialized Views.
Proc. VLDB Endow., 2015

Wisteria: Nurturing Scalable Data Cleaning Infrastructure.
Proc. VLDB Endow., 2015

SampleClean: Fast and Reliable Analytics on Dirty Data.
IEEE Data Eng. Bull., 2015

M-CAFE 1.0: Motivating and Prioritizing Ongoing Student Feedback During MOOCs and Large on-Campus Courses using Collaborative Filtering.
Proceedings of the 16th Annual Conference on Information Technology Education, 2015

A Case Study in Mobile-Optimized vs. Responsive Web Application Design.
Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct, 2015

M-CAFE: Managing MOOC Student Feedback with Collaborative Filtering.
Proceedings of the Second ACM Conference on Learning @ Scale, 2015

DevCAFE 1.0: A participatory platform for assessing development initiatives in the field.
Proceedings of the 2015 IEEE Global Humanitarian Technology Conference, 2015

2014
A Partitioning Framework for Aggressive Data Skipping.
Proc. VLDB Endow., 2014

A sample-and-clean framework for fast and accurate query processing on dirty data.
Proceedings of the International Conference on Management of Data, 2014

Fine-grained partitioning for aggressive data skipping.
Proceedings of the International Conference on Management of Data, 2014

A methodology for learning, analyzing, and mitigating social influence bias in recommender systems.
Proceedings of the Eighth ACM Conference on Recommender Systems, 2014

Communication-Efficient Distributed Dual Coordinate Ascent.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Learning accurate kinematic control of cable-driven surgical robots using data cleaning and Gaussian Process Regression.
Proceedings of the 2014 IEEE International Conference on Automation Science and Engineering, 2014


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