Transfer learning for low-resource natural language analysis

Transfer learning for low-resource natural language analysis

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.

Bibliographic Details
Main Author:	Zhang, Yuan, Ph. D. Massachusetts Institute of Technology
Other Authors:	Regina Barzilay.
Format:	Thesis
Language:	eng
Published:	Massachusetts Institute of Technology 2017
Subjects:	Electrical Engineering and Computer Science.
Online Access:	http://hdl.handle.net/1721.1/108847

Similar Items

Transfer learning and robustness for natural language processing
by: Jin, Di,Ph.D.Massachusetts Institute of Technology.
Published: (2021)

Interpretable neural models for natural language processing
by: Lei, Tao, Ph. D. Massachusetts Institute of Technology
Published: (2017)

Parsing with sparse annotated resources
by: Zhang, Yuan, Ph. D. Massachusetts Institute of Technology
Published: (2013)

Language technologies in speech-enabled second language learning games : from reading to dialogue
by: Xu, Yushi, Ph. D. Massachusetts Institute of Technology
Published: (2012)

Computing with unreliable resources : design, analysis and algorithms
by: Wang, Da, Ph. D. Massachusetts Institute of Technology
Published: (2014)

Evaluating style transfer in natural language
by: Matthews, Nicholas (Nicholas J.)
Published: (2018)

Empowering natural language processing in low-resource regimes
by: Feng, Zijian
Published: (2025)

A natural language interface for querying graph databases
by: Sun, Christina, M. Eng. Massachusetts Institute of Technology
Published: (2018)

Multimedia for language learning
by: Kovács, Géza, M. Eng. Massachusetts Institute of Technology
Published: (2014)

Comparison of natural language processing algorithms for medical texts
by: Chen, Michelle W., M. Eng. Massachusetts Institute of Technology
Published: (2015)

Knowledge and learning in natural language
by: Yang, Charles D
Published: (2014)

Towards robust natural language and image processing In low-resource scenarios
by: Liu, Linlin
Published: (2023)

Electronic transport in low-angle twisted bilayer graphene
by: Cao, Yuan, Ph. D. Massachusetts Institute of Technology
Published: (2016)

Reinforcement learning with natural language signals
by: Sidor, Szymon
Published: (2016)

Semi-supervised learning for natural language
by: Liang, Percy
Published: (2006)

Type system for resource bounds with type-preserving compilation
by: Wang, Peng,Ph. D.Massachusetts Institute of Technology.
Published: (2019)

Pre-training model based on the transfer learning in natural language processing
by: Tang, Jiayi
Published: (2019)

On the power of (even a little) flexibility in dynamic resource allocation
by: Xu, Kuang, Ph. D. Massachusetts Institute of Technology
Published: (2014)

Domain knowledge acquisition via language grounding
by: Lei, Tao, Ph. D. Massachusetts Institute of Technology
Published: (2013)

Toward an intelligent multimodal interface for natural interaction
by: Yin, Ying Ph. D. Massachusetts Institute of Technology
Published: (2011)

Language-independent methods for computer-assisted pronunciation training
by: Lee, Ann, Ph. D. Massachusetts Institute of Technology
Published: (2017)

Learning semantic maps from natural language
by: Hemachandra, Sachithra Madhawa
Published: (2015)

Design of a low-voltage low-power dc-dc HF converter
by: Hu, Jingying, Ph. D. Massachusetts Institute of Technology.
Published: (2008)

Active power ancillary service provision of commercial building energy storage resources
by: Kim, Youngjin, Ph. D. Massachusetts Institute of Technology
Published: (2016)

Deep learning and structured data
by: Zhang, Chiyuan, Ph. D. Massachusetts Institute of Technology
Published: (2018)

Dynamic resource allocation in WDM networks with optical bypass and waveband switching
by: Chen, Li-Wei, Ph. D. Massachusetts Institute of Technology
Published: (2006)

Design and implementation of low-latency, low-power reconfigurable on-chip networks
by: Chen, Chia-Hsin, Ph. D. Massachusetts Institute of Technology
Published: (2017)

Real-time continuous gesture recognition for natural multimodal interaction
by: Yin, Ying, Ph. D. Massachusetts Institute of Technology
Published: (2014)

Semantic representation learning for natural language understanding
by: Zhang, Yong
Published: (2018)

DRACL (Decentralized resource access control list)
by: Allen, Steven D., M. Eng. Massachusetts Institute of Technology
Published: (2017)

Unsupervised spoken keyword spotting and learning of acoustically meaningful units
by: Zhang, Yaodong, Ph. D. Massachusetts Institute of Technology
Published: (2010)

Low-swing signaling for energy efficient on-chip networks
by: Park, Sunghyun, Ph. D. Massachusetts Institute of Technology
Published: (2011)

An architecture for low-power voice-command recognition systems
by: He, Qing, Ph. D. Massachusetts Institute of Technology
Published: (2016)

Intelligible models for learning categorical data via generalized fourier spectrum
by: Zhang, Xuhong,Ph. D.Massachusetts Institute of Technology.
Published: (2019)

Towards low-power yet high-performance networks-on-chip
by: Park, Sunghyun, Ph. D. Massachusetts Institute of Technology
Published: (2015)

Language style transfer
by: Shen, Tianxiao
Published: (2018)

Online, low-latency decision making for Fetal Magnetic Resonance Imaging with machine learning
by: Xu, Junshen(Computer scientist)Massachusetts Institute of Technology.
Published: (2020)

Design of low-voltage, high-bandwidth radio frequency power converters
by: Hu, Jingying, Ph. D. Massachusetts Institute of Technology
Published: (2012)

Unsupervised multilingual learning
by: Snyder, Benjamin, Ph. D. Massachusetts Institute of Technology
Published: (2011)

Bilayer graphene growth by low pressure chemical vapor deposition on copper foil
by: Fang, Wenjing, Ph. D. Massachusetts Institute of Technology
Published: (2012)