Search Results for author: Denny Zhou

Found 14 papers, 4 papers with code

Network Pruning by Greedy Subnetwork Selection

no code implementations ICML 2020 Mao Ye, Chengyue Gong, Lizhen Nie, Denny Zhou, Adam Klivans, Qiang Liu

Theoretically, we show that the small networks pruned using our method achieve provably lower loss than small networks trained from scratch with the same size.

Network Pruning

SpreadsheetCoder: Formula Prediction from Semi-structured Context

1 code implementation26 Jun 2021 Xinyun Chen, Petros Maniatis, Rishabh Singh, Charles Sutton, Hanjun Dai, Max Lin, Denny Zhou

In this work, we present the first approach for synthesizing spreadsheet formulas from tabular context, which includes both headers and semi-structured tabular data.

Program Synthesis

Speeding up Deep Learning Training by Sharing Weights and Then Unsharing

no code implementations1 Jan 2021 Shuo Yang, Le Hou, Xiaodan Song, Qiang Liu, Denny Zhou

It has been widely observed that increasing deep learning model sizes often leads to significant performance improvements on a variety of natural language processing and computer vision tasks.

Linear-Time WordPiece Tokenization

no code implementations31 Dec 2020 Xinying Song, Alex Salcianu, Yang song, Dave Dopson, Denny Zhou

WordPiece tokenization is a subword-based tokenization schema adopted by BERT: it segments the input text via a longest-match-first tokenization strategy, known as Maximum Matching or MaxMatch.


Compositional Generalization via Neural-Symbolic Stack Machines

no code implementations NeurIPS 2020 Xinyun Chen, Chen Liang, Adams Wei Yu, Dawn Song, Denny Zhou

Despite achieving tremendous success, existing deep learning models have exposed limitations in compositional generalization, the capability to learn compositional rules and apply them to unseen cases in a systematic manner.

Few-Shot Learning Machine Translation

Go Wide, Then Narrow: Efficient Training of Deep Thin Networks

no code implementations ICML 2020 Denny Zhou, Mao Ye, Chen Chen, Tianjian Meng, Mingxing Tan, Xiaodan Song, Quoc Le, Qiang Liu, Dale Schuurmans

This is achieved by layerwise imitation, that is, forcing the thin network to mimic the intermediate outputs of the wide network from layer to layer.

Model Compression

Neural Symbolic Reader: Scalable Integration of Distributed and Symbolic Representations for Reading Comprehension

no code implementations ICLR 2020 Xinyun Chen, Chen Liang, Adams Wei Yu, Denny Zhou, Dawn Song, Quoc V. Le

Integrating distributed representations with symbolic operations is essential for reading comprehension requiring complex reasoning, such as counting, sorting and arithmetics, but most existing approaches are hard to scale to more domains or more complex reasoning.

Data Augmentation Question Answering +1

Black-box Off-policy Estimation for Infinite-Horizon Reinforcement Learning

no code implementations ICLR 2020 Ali Mousavi, Lihong Li, Qiang Liu, Denny Zhou

Off-policy estimation for long-horizon problems is important in many real-life applications such as healthcare and robotics, where high-fidelity simulators may not be available and on-policy evaluation is expensive or impossible.

Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection

1 code implementation3 Mar 2020 Mao Ye, Chengyue Gong, Lizhen Nie, Denny Zhou, Adam Klivans, Qiang Liu

This differs from the existing methods based on backward elimination, which remove redundant neurons from the large network.

Network Pruning

Deep Physiological State Space Model for Clinical Forecasting

no code implementations4 Dec 2019 Yuan Xue, Denny Zhou, Nan Du, Andrew Dai, Zhen Xu, Kun Zhang, Claire Cui

Clinical forecasting based on electronic medical records (EMR) can uncover the temporal correlations between patients' conditions and outcomes from sequences of longitudinal clinical measurements.

Extremely Small BERT Models from Mixed-Vocabulary Training

no code implementations EACL 2021 Sanqiang Zhao, Raghav Gupta, Yang song, Denny Zhou

Pretrained language models like BERT have achieved good results on NLP tasks, but are impractical on resource-limited devices due to memory footprint.

Knowledge Distillation Language Modelling +2

Neural Logic Machines

1 code implementation ICLR 2019 Honghua Dong, Jiayuan Mao, Tian Lin, Chong Wang, Lihong Li, Denny Zhou

We propose the Neural Logic Machine (NLM), a neural-symbolic architecture for both inductive learning and logic reasoning.

Decision Making Inductive logic programming +1

Doubly Sparse: Sparse Mixture of Sparse Experts for Efficient Softmax Inference

no code implementations ICLR 2019 Shun Liao, Ting Chen, Tian Lin, Denny Zhou, Chong Wang

In this paper, we present a novel softmax inference speedup method, Doubly Sparse Softmax (DS-Softmax), that leverages sparse mixture of sparse experts to efficiently retrieve top-k classes.

Image Classification Language Modelling +1

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