Search Results for author: Feiyu Xu

Found 27 papers, 0 papers with code

Efficient Automatic Meta Optimization Search for Few-Shot Learning

no code implementations6 Sep 2019 Xinyue Zheng, Peng Wang, Qigang Wang, Zhongchao shi, Feiyu Xu

NAS automatically generates and evaluates meta-learner's architecture for few-shot learning problems, while the meta-learner uses meta-learning algorithm to optimize its parameters based on the distribution of learning tasks.

Few-Shot Learning Neural Architecture Search

Generating Pattern-Based Entailment Graphs for Relation Extraction

no code implementations SEMEVAL 2017 Kathrin Eichler, Feiyu Xu, Hans Uszkoreit, Sebastian Krause

A common approach is to exploit existing knowledge to learn linguistic patterns expressing the target relation and use these patterns for extracting new relation mentions.

Knowledge Base Population Natural Language Inference +1

A fine-grained corpus annotation schema of German nephrology records

no code implementations WS 2016 Rol Roller, , Hans Uszkoreit, Feiyu Xu, Laura Seiffe, Michael Mikhailov, Oliver Staeck, Klemens Budde, Fabian Halleck, Danilo Schmidt

In this work we present a fine-grained annotation schema to detect named entities in German clinical data of chronically ill patients with kidney diseases.

Named Entity Recognition

SynsetRank: Degree-adjusted Random Walk for Relation Identification

no code implementations2 Sep 2016 Shinichi Nakajima, Sebastian Krause, Dirk Weissenborn, Sven Schmeier, Nico Goernitz, Feiyu Xu

In relation extraction, a key process is to obtain good detectors that find relevant sentences describing the target relation.

Relation Extraction

Annotating Relation Mentions in Tabloid Press

no code implementations LREC 2014 Hong Li, Sebastian Krause, Feiyu Xu, Hans Uszkoreit, Robert Hummel, Veselina Mironova

The current corpus is already in active use in our research for evaluation of the relation extraction performance of our automatically learned extraction patterns.

Relation Extraction

Information Extraction from German Patient Records via Hybrid Parsing and Relation Extraction Strategies

no code implementations LREC 2014 Hans-Ulrich Krieger, Christian Spurk, Hans Uszkoreit, Feiyu Xu, Yi Zhang, Frank M{\"u}ller, Thomas Tolxdorff

In this paper, we report on first attempts and findings to analyzing German patient records, using a hybrid parsing architecture and a combination of two relation extraction strategies.

Chunking Medical Diagnosis +3

Language Resources and Annotation Tools for Cross-Sentence Relation Extraction

no code implementations LREC 2014 Sebastian Krause, Hong Li, Feiyu Xu, Hans Uszkoreit, Robert Hummel, Luise Spielhagen

In this paper, we present a novel combination of two types of language resources dedicated to the detection of relevant relations (RE) such as events or facts across sentence boundaries.

Coreference Resolution Dependency Parsing +1

Annotating Opinions in German Political News

no code implementations LREC 2012 Hong Li, Xiwen Cheng, Kristina Adson, Tal Kirshboim, Feiyu Xu

This paper presents an approach to construction of an annotated corpus for German political news for the opinion mining task.

Opinion Mining Question Answering +3

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