Mitchell Stern - Concepedia

Author

Mitchell Stern

University of California, Berkeley

Also Known As

Mitchell Stern, Stern, Mitchell

Publications

2.4K

Citations

H-Index

Concepts

All Affiliations

University of California, Berkeley Google (United States)

About

Mitchell Stern is an author at University of California, Berkeley specializing in engineering, machine learning, and data science.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	15	16	1.8K
2	Data Science	10	10	1.5K
3	Computer Science	9	9	1.4K
4	Language Studies	8	8	648
5	Computer Engineering	2	2	226

Mitchell Stern

Publications

2.3K

Citations

H-Index

Page 1

	Year	Citations
The Marginal Value of Adaptive Gradient Methods in Machine Learning Ashia Wilson, Rebecca Roelofs, Mitchell Stern, arXiv (Cornell University) Artificial IntelligenceMarginal ValueEngineeringMachine LearningData Science	2017	552
Abstract Syntax Networks for Code Generation and Semantic Parsing Maxim Rabinovich, Mitchell Stern, Dan Klein	2017	317
The Marginal Value of Adaptive Gradient Methods in Machine Learning Ashia Wilson, Rebecca Roelofs, Mitchell Stern, Neural Information Processing Systems Artificial IntelligenceMarginal ValueEngineeringMachine LearningData Science	2017	246
A Minimal Span-Based Neural Constituency Parser Mitchell Stern, Jacob Andreas, Dan Klein Syntactic ParsingEngineeringDependency LinguisticsCorpus LinguisticsText Mining	2017	200
Adafactor: Adaptive Learning Rates with Sublinear Memory Cost Noam Shazeer, Mitchell Stern arXiv (Cornell University) EngineeringMachine LearningSequential LearningAdaptive Learning RatesDecay Rate	2018	163
Insertion Transformer: Flexible Sequence Generation via Insertion Operations Mitchell Stern, William Chan, Jamie Kiros, arXiv (Cornell University) EngineeringMachine LearningInsertion TransformerMultilingual PretrainingSequence Design	2019	162
What’s Going On in Neural Constituency Parsers? An Analysis David Gaddy, Mitchell Stern, Dan Klein Syntactic ParsingMitchell SternNeural Constituency ParsersEngineeringSyntactic Structure	2018	78
KERMIT: Generative Insertion-Based Modeling for Sequences William Chan, Nikita Kitaev, Kelvin Guu, arXiv (Cornell University) Structured PredictionEngineeringMachine LearningSequential LearningMultilingual Pretraining	2019	67
Stochastic Cubic Regularization for Fast Nonconvex Optimization Nilesh Tripuraneni, Mitchell Stern, Chi Jin, Neural Information Processing Systems Mathematical ProgrammingNumerical AnalysisEngineeringMachine LearningStochastic Gradients	2018	63
Imitation Attacks and Defenses for Black-box Machine Translation Systems Eric Wallace, Mitchell Stern, Dawn Song	2020	62

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