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ORCIDMitchell Stern
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2020 – today
- 2021
[c16]Matheus V. X. Ferreira, Daniel J. Moroz, David C. Parkes, Mitchell Stern:
Dynamic posted-price mechanisms for the blockchain transaction-fee market. AFT 2021: 86-99- [c15]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: 6:1-6:1 - [i18]Matheus V. X. Ferreira, Daniel J. Moroz, David C. Parkes, Mitchell Stern:
Dynamic Posted-Price Mechanisms for the Blockchain Transaction-Fee Market. CoRR abs/2103.14144 (2021) - 2020
- [b1]Mitchell Stern:
Structured Neural Models and Structured Decoding for Natural Language Processing. University of California, Berkeley, USA, 2020 - [c14]Ruiqi Zhong, Mitchell Stern, Dan Klein:
Semantic Scaffolds for Pseudocode-to-Code Generation. ACL 2020: 2283-2295 - [c13]Eric Wallace, Mitchell Stern, Dawn Song:
Imitation Attacks and Defenses for Black-box Machine Translation Systems. EMNLP (1) 2020: 5531-5546 - [c12]William Chan, Mitchell Stern, Jamie Kiros, Jakob Uszkoreit:
An Empirical Study of Generation Order for Machine Translation. EMNLP (1) 2020: 5764-5773 - [i17]Laura Ruis, Mitchell Stern, Julia Proskurnia, William Chan:
Insertion-Deletion Transformer. CoRR abs/2001.05540 (2020) - [i16]Eric Wallace, Mitchell Stern, Dawn Song:
Imitation Attacks and Defenses for Black-box Machine Translation Systems. CoRR abs/2004.15015 (2020) - [i15]Ruiqi Zhong, Mitchell Stern, Dan Klein:
Semantic Scaffolds for Pseudocode-to-Code Generation. CoRR abs/2005.05927 (2020) - [i14]Elman Mansimov, Mitchell Stern, Mia Xu Chen, Orhan Firat, Jakob Uszkoreit, Puneet Jain:
Towards End-to-End In-Image Neural Machine Translation. CoRR abs/2010.10648 (2020)
2010 – 2019
- 2019
- [c11]Mitchell Stern, William Chan, Jamie Kiros, Jakob Uszkoreit:
Insertion Transformer: Flexible Sequence Generation via Insertion Operations. ICML 2019: 5976-5985 - [i13]Mitchell Stern, William Chan, Jamie Kiros, Jakob Uszkoreit:
Insertion Transformer: Flexible Sequence Generation via Insertion Operations. CoRR abs/1902.03249 (2019) - [i12]William Chan, Nikita Kitaev, Kelvin Guu, Mitchell Stern, Jakob Uszkoreit:
KERMIT: Generative Insertion-Based Modeling for Sequences. CoRR abs/1906.01604 (2019) - [i11]William Chan, Mitchell Stern, Jamie Kiros, Jakob Uszkoreit:
An Empirical Study of Generation Order for Machine Translation. CoRR abs/1910.13437 (2019) - 2018
- [c10]Noam Shazeer, Mitchell Stern:
Adafactor: Adaptive Learning Rates with Sublinear Memory Cost. ICML 2018: 4603-4611 - [c9]David Gaddy, Mitchell Stern, Dan Klein:
What's Going On in Neural Constituency Parsers? An Analysis. NAACL-HLT 2018: 999-1010 - [c8]Nilesh Tripuraneni, Mitchell Stern, Chi Jin, Jeffrey Regier, Michael I. Jordan:
Stochastic Cubic Regularization for Fast Nonconvex Optimization. NeurIPS 2018: 2904-2913 - [c7]Mitchell Stern, Noam Shazeer, Jakob Uszkoreit:
Blockwise Parallel Decoding for Deep Autoregressive Models. NeurIPS 2018: 10107-10116 - [i10]Noam Shazeer, Mitchell Stern:
Adafactor: Adaptive Learning Rates with Sublinear Memory Cost. CoRR abs/1804.04235 (2018) - [i9]David Gaddy, Mitchell Stern, Dan Klein:
What's Going On in Neural Constituency Parsers? An Analysis. CoRR abs/1804.07853 (2018) - [i8]Mitchell Stern, Noam Shazeer, Jakob Uszkoreit:
Blockwise Parallel Decoding for Deep Autoregressive Models. CoRR abs/1811.03115 (2018) - 2017
- [c6]Daniel Fried, Mitchell Stern, Dan Klein:
Improving Neural Parsing by Disentangling Model Combination and Reranking Effects. ACL (2) 2017: 161-166 - [c5]Mitchell Stern, Jacob Andreas, Dan Klein:
A Minimal Span-Based Neural Constituency Parser. ACL (1) 2017: 818-827 - [c4]Maxim Rabinovich, Mitchell Stern, Dan Klein:
Abstract Syntax Networks for Code Generation and Semantic Parsing. ACL (1) 2017: 1139-1149 - [c3]Mitchell Stern, Daniel Fried, Dan Klein:
Effective Inference for Generative Neural Parsing. EMNLP 2017: 1695-1700 - [c2]Ashia C. Wilson, Rebecca Roelofs, Mitchell Stern, Nati Srebro, Benjamin Recht:
The Marginal Value of Adaptive Gradient Methods in Machine Learning. NIPS 2017: 4148-4158 - [c1]Jianbo Chen, Mitchell Stern, Martin J. Wainwright, Michael I. Jordan:
Kernel Feature Selection via Conditional Covariance Minimization. NIPS 2017: 6946-6955 - [i7]Maxim Rabinovich, Mitchell Stern, Dan Klein:
Abstract Syntax Networks for Code Generation and Semantic Parsing. CoRR abs/1704.07535 (2017) - [i6]Mitchell Stern, Jacob Andreas, Dan Klein:
A Minimal Span-Based Neural Constituency Parser. CoRR abs/1705.03919 (2017) - [i5]Ashia C. Wilson, Rebecca Roelofs, Mitchell Stern, Nathan Srebro, Benjamin Recht:
The Marginal Value of Adaptive Gradient Methods in Machine Learning. CoRR abs/1705.08292 (2017) - [i4]Jianbo Chen, Mitchell Stern, Martin J. Wainwright, Michael I. Jordan:
Kernel Feature Selection via Conditional Covariance Minimization. CoRR abs/1707.01164 (2017) - [i3]Daniel Fried, Mitchell Stern, Dan Klein:
Improving Neural Parsing by Disentangling Model Combination and Reranking Effects. CoRR abs/1707.03058 (2017) - [i2]Mitchell Stern, Daniel Fried, Dan Klein:
Effective Inference for Generative Neural Parsing. CoRR abs/1707.08976 (2017) - [i1]Nilesh Tripuraneni, Mitchell Stern, Chi Jin, Jeffrey Regier, Michael I. Jordan:
Stochastic Cubic Regularization for Fast Nonconvex Optimization. CoRR abs/1711.02838 (2017)
Coauthor Index
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