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03/25/2021
Dynamic Posted-Price Mechanisms for the Blockchain Transaction-Fee Market
In recent years, prominent blockchain systems such as Bitcoin and Ethere...
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10/20/2020
Towards End-to-End In-Image Neural Machine Translation
In this paper, we offer a preliminary investigation into the task of in-...
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05/12/2020
Semantic Scaffolds for Pseudocode-to-Code Generation
We propose a method for program generation based on semantic scaffolds, ...
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04/30/2020
Imitation Attacks and Defenses for Black-box Machine Translation Systems
We consider an adversary looking to steal or attack a black-box machine ...
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01/15/2020
Insertion-Deletion Transformer
We propose the Insertion-Deletion Transformer, a novel transformer-based...
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10/29/2019
An Empirical Study of Generation Order for Machine Translation
In this work, we present an empirical study of generation order for mach...
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06/04/2019
KERMIT: Generative Insertion-Based Modeling for Sequences
We present KERMIT, a simple insertion-based approach to generative model...
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02/08/2019
Insertion Transformer: Flexible Sequence Generation via Insertion Operations
We present the Insertion Transformer, an iterative, partially autoregres...
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11/07/2018
Blockwise Parallel Decoding for Deep Autoregressive Models
Deep autoregressive sequence-to-sequence models have demonstrated impres...
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04/20/2018
What's Going On in Neural Constituency Parsers? An Analysis
A number of differences have emerged between modern and classic approach...
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04/11/2018
Adafactor: Adaptive Learning Rates with Sublinear Memory Cost
In several recently proposed stochastic optimization methods (e.g. RMSPr...
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11/08/2017
Stochastic Cubic Regularization for Fast Nonconvex Optimization
This paper proposes a stochastic variant of a classic algorithm---the cu...
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07/27/2017
Effective Inference for Generative Neural Parsing
Generative neural models have recently achieved state-of-the-art results...
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07/10/2017
Improving Neural Parsing by Disentangling Model Combination and Reranking Effects
Recent work has proposed several generative neural models for constituen...
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07/04/2017
Kernel Feature Selection via Conditional Covariance Minimization
We propose a framework for feature selection that employs kernel-based m...
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05/23/2017
The Marginal Value of Adaptive Gradient Methods in Machine Learning
Adaptive optimization methods, which perform local optimization with a m...
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05/10/2017
A Minimal Span-Based Neural Constituency Parser
In this work, we present a minimal neural model for constituency parsing...
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04/25/2017