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09/11/2023
Quantifying Uncertainty in Aggregate Queries over Integrated Datasets
Data integration is a notoriously difficult and heuristic-driven process...
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06/02/2023
DeepScribe: Localization and Classification of Elamite Cuneiform Signs Via Deep Learning
Twenty-five hundred years ago, the paperwork of the Achaemenid Empire wa...
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05/05/2023
Data Station: Delegated, Trustworthy, and Auditable Computation to Enable Data-Sharing Consortia with a Data Escrow
Pooling and sharing data increases and distributes its value. But since ...
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03/02/2023
EdgeServe: An Execution Layer for Decentralized Prediction
The relevant features for a machine learning task may be aggregated from...
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04/20/2022
JanusAQP: Efficient Partition Tree Maintenance for Dynamic Approximate Query Processing
Approximate query processing over dynamic databases, i.e., under inserti...
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12/07/2021
VizExtract: Automatic Relation Extraction from Data Visualizations
Visual graphics, such as plots, charts, and figures, are widely used to ...
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10/05/2021
Version Reconciliation for Collaborative Databases
We propose MindPalace, a prototype of a versioned database for efficient...
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03/29/2021
Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing
Sample-based approximate query processing (AQP) suffers from many pitfal...
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02/23/2021
CIAO: An Optimization Framework for Client-Assisted Data Loading
Data loading has been one of the most common performance bottlenecks for...
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08/31/2020
The Data Station: Combining Data, Compute, and Market Forces
This paper introduces Data Stations, a new data architecture that we are...
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04/08/2020
Fast and Reliable Missing Data Contingency Analysis with Predicate-Constraints
Today, data analysts largely rely on intuition to determine whether miss...
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03/18/2020
Machine Learning enabled Spectrum Sharing in Dense LTE-U/Wi-Fi Coexistence Scenarios
The application of Machine Learning (ML) techniques to complex engineeri...
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02/08/2020
An Empirical Evaluation of Perturbation-based Defenses
Recent work has extensively shown that randomized perturbations of a neu...
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11/21/2019
Machine Learning based detection of multiple Wi-Fi BSSs for LTE-U CSAT
According to the LTE-U Forum specification, a LTE-U base-station (BS) re...
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11/21/2019
Band-limited Training and Inference for Convolutional Neural Networks
The convolutional layers are core building blocks of neural network arch...
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05/10/2019
Selectivity Estimation with Deep Likelihood Models
Selectivity estimation has long been grounded in statistical tools for d...
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04/26/2019
AlphaClean: Automatic Generation of Data Cleaning Pipelines
The analyst effort in data cleaning is gradually shifting away from the ...
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03/04/2019
Opportunistic View Materialization with Deep Reinforcement Learning
Carefully selected materialized views can greatly improve the performanc...
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12/18/2018
DeepLens: Towards a Visual Data Management System
Advances in deep learning have greatly widened the scope of automatic co...
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11/19/2018
Generalizing Robot Imitation Learning with Invariant Hidden Semi-Markov Models
Generalizing manipulation skills to new situations requires extracting i...
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08/09/2018
Learning to Optimize Join Queries With Deep Reinforcement Learning
Exhaustive enumeration of all possible join orders is often avoided, and...
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12/08/2017
SPRK: A Low-Cost Stewart Platform For Motion Study In Surgical Robotics
To simulate body organ motion due to breathing, heart beats, or peristal...
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12/08/2017
Using Intermittent Synchronization to Compensate for Rhythmic Body Motion During Autonomous Surgical Cutting and Debridement
Anatomical structures are rarely static during a surgical procedure due ...
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11/04/2017
Composing Meta-Policies for Autonomous Driving Using Hierarchical Deep Reinforcement Learning
Rather than learning new control policies for each new task, it is possi...
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11/03/2017
BoostClean: Automated Error Detection and Repair for Machine Learning
Predictive models based on machine learning can be highly sensitive to d...
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10/15/2017