papers
Publications (12)
cs.CL2017
Abstract Syntax Networks for Code Generation and Semantic Parsing
Maxim Rabinovich, Mitchell Stern, Dan Klein
stat.ML2018
Kernel Feature Selection via Conditional Covariance Minimization
Jianbo Chen, Mitchell Stern, Martin J. Wainwright +1
stat.ML2018
The Marginal Value of Adaptive Gradient Methods in Machine Learning
Ashia C. Wilson, Rebecca Roelofs, Mitchell Stern +2
cs.CL2017
Improving Neural Parsing by Disentangling Model Combination and Reranking Effects
Daniel Fried, Mitchell Stern, Dan Klein
cs.CL2019
KERMIT: Generative Insertion-Based Modeling for Sequences
William Chan, Nikita Kitaev, Kelvin Guu +2
cs.CL2017
A Minimal Span-Based Neural Constituency Parser
Mitchell Stern, Jacob Andreas, Dan Klein
cs.CL2018
What's Going On in Neural Constituency Parsers? An Analysis
David Gaddy, Mitchell Stern, Dan Klein
cs.CL2017
Effective Inference for Generative Neural Parsing
Mitchell Stern, Daniel Fried, Dan Klein
cs.LG2018
Adafactor: Adaptive Learning Rates with Sublinear Memory Cost
Noam Shazeer, Mitchell Stern
cs.CL2019
Insertion Transformer: Flexible Sequence Generation via Insertion Operations
Mitchell Stern, William Chan, Jamie Kiros +1
cs.LG2018
Blockwise Parallel Decoding for Deep Autoregressive Models
Mitchell Stern, Noam Shazeer, Jakob Uszkoreit
cs.LG2017
Stochastic Cubic Regularization for Fast Nonconvex Optimization
Nilesh Tripuraneni, Mitchell Stern, Chi Jin +2