Mitchell Stern

Publication Activity (10 Years)

Years Active: 2017-2021
Publications (10 Years): 34

Top Topics

Machine Translation

Insertions And Deletions

Top Venues

Publications

Matheus V. X. Ferreira, Daniel J. Moroz, David C. Parkes, Mitchell Stern
Dynamic Posted-Price Mechanisms for the Blockchain Transaction Fee Market (Invited Talk). Tokenomics (2021)
Matheus V. X. Ferreira, Daniel J. Moroz, David C. Parkes, Mitchell Stern
Dynamic Posted-Price Mechanisms for the Blockchain Transaction-Fee Market. CoRR (2021)
Matheus V. X. Ferreira, Daniel J. Moroz, David C. Parkes, Mitchell Stern
Dynamic posted-price mechanisms for the blockchain transaction-fee market. AFT (2021)
Elman Mansimov, Mitchell Stern, Mia Xu Chen, Orhan Firat, Jakob Uszkoreit, Puneet Jain
Towards End-to-End In-Image Neural Machine Translation. CoRR (2020)
Eric Wallace, Mitchell Stern, Dawn Song
Imitation Attacks and Defenses for Black-box Machine Translation Systems. CoRR (2020)
Eric Wallace, Mitchell Stern, Dawn Song
Imitation Attacks and Defenses for Black-box Machine Translation Systems. EMNLP (1) (2020)
William Chan, Mitchell Stern, Jamie Kiros, Jakob Uszkoreit
An Empirical Study of Generation Order for Machine Translation. EMNLP (1) (2020)
Laura Ruis, Mitchell Stern, Julia Proskurnia, William Chan
Insertion-Deletion Transformer. CoRR (2020)
Ruiqi Zhong, Mitchell Stern, Dan Klein
Semantic Scaffolds for Pseudocode-to-Code Generation. ACL (2020)
Ruiqi Zhong, Mitchell Stern, Dan Klein
Semantic Scaffolds for Pseudocode-to-Code Generation. CoRR (2020)
William Chan, Mitchell Stern, Jamie Kiros, Jakob Uszkoreit
An Empirical Study of Generation Order for Machine Translation. CoRR (2019)
William Chan, Nikita Kitaev, Kelvin Guu, Mitchell Stern, Jakob Uszkoreit
KERMIT: Generative Insertion-Based Modeling for Sequences. CoRR (2019)
Mitchell Stern, William Chan, Jamie Kiros, Jakob Uszkoreit
Insertion Transformer: Flexible Sequence Generation via Insertion Operations. ICML (2019)
Mitchell Stern, William Chan, Jamie Kiros, Jakob Uszkoreit
Insertion Transformer: Flexible Sequence Generation via Insertion Operations. CoRR (2019)
David Gaddy, Mitchell Stern, Dan Klein
What's Going On in Neural Constituency Parsers? An Analysis. NAACL-HLT (2018)
Nilesh Tripuraneni, Mitchell Stern, Chi Jin, Jeffrey Regier, Michael I. Jordan
Stochastic Cubic Regularization for Fast Nonconvex Optimization. NeurIPS (2018)
Mitchell Stern, Noam Shazeer, Jakob Uszkoreit
Blockwise Parallel Decoding for Deep Autoregressive Models. CoRR (2018)
Mitchell Stern, Noam Shazeer, Jakob Uszkoreit
Blockwise Parallel Decoding for Deep Autoregressive Models. NeurIPS (2018)
David Gaddy, Mitchell Stern, Dan Klein
What's Going On in Neural Constituency Parsers? An Analysis. CoRR (2018)
Noam Shazeer, Mitchell Stern
Adafactor: Adaptive Learning Rates with Sublinear Memory Cost. CoRR (2018)
Noam Shazeer, Mitchell Stern
Adafactor: Adaptive Learning Rates with Sublinear Memory Cost. ICML (2018)
Daniel Fried, Mitchell Stern, Dan Klein
Improving Neural Parsing by Disentangling Model Combination and Reranking Effects. ACL (2) (2017)
Mitchell Stern, Jacob Andreas, Dan Klein
A Minimal Span-Based Neural Constituency Parser. CoRR (2017)
Mitchell Stern, Jacob Andreas, Dan Klein
A Minimal Span-Based Neural Constituency Parser. ACL (1) (2017)
Nilesh Tripuraneni, Mitchell Stern, Chi Jin, Jeffrey Regier, Michael I. Jordan
Stochastic Cubic Regularization for Fast Nonconvex Optimization. CoRR (2017)
Jianbo Chen, Mitchell Stern, Martin J. Wainwright, Michael I. Jordan
Kernel Feature Selection via Conditional Covariance Minimization. CoRR (2017)
Ashia C. Wilson, Rebecca Roelofs, Mitchell Stern, Nathan Srebro, Benjamin Recht
The Marginal Value of Adaptive Gradient Methods in Machine Learning. CoRR (2017)
Mitchell Stern, Daniel Fried, Dan Klein
Effective Inference for Generative Neural Parsing. CoRR (2017)
Daniel Fried, Mitchell Stern, Dan Klein
Improving Neural Parsing by Disentangling Model Combination and Reranking Effects. CoRR (2017)
Maxim Rabinovich, Mitchell Stern, Dan Klein
Abstract Syntax Networks for Code Generation and Semantic Parsing. ACL (1) (2017)
Jianbo Chen, Mitchell Stern, Martin J. Wainwright, Michael I. Jordan
Kernel Feature Selection via Conditional Covariance Minimization. NIPS (2017)
Mitchell Stern, Daniel Fried, Dan Klein
Effective Inference for Generative Neural Parsing. EMNLP (2017)
Ashia C. Wilson, Rebecca Roelofs, Mitchell Stern, Nati Srebro, Benjamin Recht
The Marginal Value of Adaptive Gradient Methods in Machine Learning. NIPS (2017)
Maxim Rabinovich, Mitchell Stern, Dan Klein
Abstract Syntax Networks for Code Generation and Semantic Parsing. CoRR (2017)