activity
20172021
most citedThe Marginal Value of Adaptive Gradient Methods in Machine Learning

546 citations · 1.2k across the 17 of their papers we have counts for

collaborators

18 papers

cs.GT2021★ 8 cited

Dynamic Posted-Price Mechanisms for the Blockchain Transaction Fee Market

Matheus V. X. Ferreira, Daniel J. Moroz, David C. Parkes +1

In recent years, prominent blockchain systems such as Bitcoin and Ethereum have experienced explosive growth in transaction volume, leading to frequent surges in demand for limited…

cs.CL2020

Towards End-to-End In-Image Neural Machine Translation

Elman Mansimov, Mitchell Stern, Mia Chen +3

In this paper, we offer a preliminary investigation into the task of in-image machine translation: transforming an image containing text in one language into an image containing th…

cs.CL2020★ 3 cited

Semantic Scaffolds for Pseudocode-to-Code Generation

Ruiqi Zhong, Mitchell Stern, Dan Klein

We propose a method for program generation based on semantic scaffolds, lightweight structures representing the high-level semantic and syntactic composition of a program. By first…

cs.CL2020★ 19 cited

Imitation Attacks and Defenses for Black-box Machine Translation Systems

Eric Wallace, Mitchell Stern, Dawn Song

Adversaries may look to steal or attack black-box NLP systems, either for financial gain or to exploit model errors. One setting of particular interest is machine translation (MT),…

cs.LG2020★ 7 cited

Insertion-Deletion Transformer

Laura Ruis, Mitchell Stern, Julia Proskurnia +1

We propose the Insertion-Deletion Transformer, a novel transformer-based neural architecture and training method for sequence generation. The model consists of two phases that are…

cs.CL2019★ 1 cited

An Empirical Study of Generation Order for Machine Translation

William Chan, Mitchell Stern, Jamie Kiros +1

In this work, we present an empirical study of generation order for machine translation. Building on recent advances in insertion-based modeling, we first introduce a soft order-re…