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Eugene Wu
Researcher at Columbia University
Publications - 125
Citations - 5781
Eugene Wu is an academic researcher from Columbia University. The author has contributed to research in topics: Computer science & Visualization. The author has an hindex of 32, co-authored 105 publications receiving 5266 citations. Previous affiliations of Eugene Wu include Massachusetts Institute of Technology & Simon Fraser University.
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ActiveClean: Interactive Data Cleaning While Learning Convex Loss Models.
TL;DR: This work proposes ActiveClean, a progressive cleaning approach where the model is updated incrementally instead of re-training and can guarantee accuracy on partially cleaned data, and returns more accurate models than uniform sampling and Active Learning.
Proceedings ArticleDOI
Complaint-driven Training Data Debugging for Query 2.0
TL;DR: This work proposes Rain, a complaint-driven training data debugging system that allows users to specify complaints over the query's intermediate or final output, and aims to return a minimum set of training examples so that if they were removed, the complaints would be resolved.
Proceedings Article
The Case for RodentStore, an Adaptive, Declarative Storage System
TL;DR: This paper makes the case for Rodent store, an adaptive and declarative storage system providing a high-level interface for describing the physical representation of data, and describes the interface between RodentStore and other parts of a database system, such as the query optimizer and executor.
Proceedings ArticleDOI
DeepBase: Deep Inspection of Neural Networks
TL;DR: DeepBase as mentioned in this paper is a system to inspect neural network behaviors through a unified interface, allowing users to annotate the data with high-level labels (e.g., part-of-speech tags, image captions).
Proceedings ArticleDOI
Towards Democratizing Relational Data Visualization
Nan Tang,Eugene Wu,Guoliang Li +2 more
TL;DR: This tutorial will go logically through these prior art, paying particular attentions on problems that may attract the interest from the database community.