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Dive into the research topics where Christopher H. Lin is active.

Publication


Featured researches published by Christopher H. Lin.


north american chapter of the association for computational linguistics | 2016

Effective Crowd Annotation for Relation Extraction

Angli Liu; Stephen Soderland; Jonathan Bragg; Christopher H. Lin; Xiao Ling; Daniel S. Weld

Can crowdsourced annotation of training data boost performance for relation extraction over methods based solely on distant supervision? While crowdsourcing has been shown effective for many NLP tasks, previous researchers found only minimal improvement when applying the method to relation extraction. This paper demonstrates that a much larger boost is possible, e.g., raising F1 from 0.40 to 0.60. Furthermore, the gains are due to a simple, generalizable technique, Gated Instruction, which combines an interactive tutorial, feedback to correct errors during training, and improved screening.


Artificial Intelligence | 2013

POMDP-based control of workflows for crowdsourcing

Peng Dai; Christopher H. Lin; Daniel S. Weld


national conference on artificial intelligence | 2012

Dynamically switching between synergistic workflows for crowdsourcing

Christopher H. Lin; Mausam Mausam; Daniel S. Weld


uncertainty in artificial intelligence | 2012

Crowdsourcing control: moving beyond multiple choice

Christopher H. Lin; Daniel S. Weld


national conference on artificial intelligence | 2012

PersonaLized online education - A crowdsourcing challenge

Daniel S. Weld; Eytan Adar; Lydia B. Chilton; Raphael Hoffmann; Eric Horvitz; Mitchell Koch; James A. Landay; Christopher H. Lin


national conference on artificial intelligence | 2014

To Re(label), or Not To Re(label)

Christopher H. Lin; Daniel S. Weld


national conference on artificial intelligence | 2014

Signals in the silence: models of implicit feedback in a recommendation system for crowdsourcing

Christopher H. Lin; Ece Kamar; Eric Horvitz


national conference on artificial intelligence | 2016

Re-active learning: active learning with relabeling

Christopher H. Lin; Daniel S. Weld


international conference on artificial intelligence | 2015

Metareasoning for planning under uncertainty

Christopher H. Lin; Andrey Kolobov; Ece Kamar; Eric Horvitz


national conference on artificial intelligence | 2012

Crowdsourcing Control: Moving Beyond Multiple Choice.

Christopher H. Lin; Daniel S. Weld

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Daniel S. Weld

University of Washington

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Jonathan Bragg

University of Washington

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Andrey Kolobov

University of Washington

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Eytan Adar

University of Michigan

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Mitchell Koch

University of Washington

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Peng Dai

University of Washington

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