Laura Burdick

According to our database, Laura Burdick authored at least 10 papers between 2016 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

Using Paraphrases to Study Properties of Contextual Embeddings.

Laura Burdick, Jonathan K. Kummerfeld, Rada Mihalcea

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

2021

Analyzing Connections Between User Attributes, Images, and Text.

Laura Burdick, Rada Mihalcea, Ryan L. Boyd, James W. Pennebaker

Cogn. Comput., 2021

Analyzing the Surprising Variability in Word Embedding Stability Across Languages.

Laura Burdick, Jonathan K. Kummerfeld, Rada Mihalcea

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

Understanding Word Embedding Stability Across Languages and Applications.

Laura Burdick

PhD thesis, 2020

2019

Building a Flexible Knowledge Graph to Capture Real-World Events.

Laura Burdick, Oana Ignat, Yiming Zhang, Rada Mihalcea, Mingzhe Wang, Steve Wilson, Yumou Wei, Jia Deng

Proceedings of the 2019 Text Analysis Conference, 2019

Identifying Visible Actions in Lifestyle Vlogs.

Oana Ignat, Laura Burdick, Jia Deng, Rada Mihalcea

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

Entity and Event Extraction from Scratch Using Minimal Training Data.

Laura Wendlandt, Steven R. Wilson, Oana Ignat, Charles Welch, Li Zhang, Mingzhe Wang, Jia Deng, Rada Mihalcea

Proceedings of the 2018 Text Analysis Conference, 2018

Factors Influencing the Surprising Instability of Word Embeddings.

Laura Wendlandt, Jonathan K. Kummerfeld, Rada Mihalcea

Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

2017

Multimodal Analysis and Prediction of Latent User Dimensions.

Laura Wendlandt, Rada Mihalcea, Ryan L. Boyd, James W. Pennebaker

Proceedings of the Social Informatics, 2017

2016

Data Science in Service of Performing Arts: Applying Machine Learning to Predicting Audience Preferences.

Jacob D. Abernethy, Cyrus Anderson, Alex Chojnacki, Chengyu Dai, John Dryden, Eric M. Schwartz, Wenbo Shen, Jonathan C. Stroud, Laura Wendlandt, Sheng Yang, Daniel T. Zhang

CoRR, 2016