Hieu Pham | DeepAI

DeepAI AI Chat

Featured Co-authors

Yoshua Bengio
448 publications
Graham Neubig
243 publications
Percy Liang
165 publications
Cho-Jui Hsieh
147 publications
Zhen Li
122 publications
Quoc V. Le
113 publications
Tengyu Ma
97 publications
Christopher D. Manning
79 publications
Juho Kannala
79 publications
Yiming Yang
76 publications
Mohammad Norouzi
71 publications

∙ 05/17/2023

DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining

The mixture proportions of pretraining data domains (e.g., Wikipedia, bo...

0 Sang Michael Xie, et al. ∙

∙ 04/18/2023

Multimodal contrastive learning for diagnosing cardiovascular diseases from electrocardiography (ECG) signals and patient metadata

This work discusses the use of contrastive learning and deep learning fo...

0 Tue M. Cao, et al. ∙

∙ 02/13/2023

Symbolic Discovery of Optimization Algorithms

We present a method to formulate algorithm discovery as program search, ...

0 Xiangning Chen, et al. ∙

∙ 12/27/2022

MixupE: Understanding and Improving Mixup from Directional Derivative Perspective

Mixup is a popular data augmentation technique for training deep neural ...

0 Vikas Verma, et al. ∙

∙ 11/19/2021

Combined Scaling for Zero-shot Transfer Learning

We present a combined scaling method called BASIC that achieves 85.7 zer...

0 Hieu Pham, et al. ∙

∙ 08/02/2021

An Applied Deep Learning Approach for Estimating Soybean Relative Maturity from UAV Imagery to Aid Plant Breeding Decisions

For a global breeding organization, identifying the next generation of s...

0 Saba Moeinizade, et al. ∙

∙ 03/17/2021

WheatNet: A Lightweight Convolutional Neural Network for High-throughput Image-based Wheat Head Detection and Counting

For a globally recognized planting breeding organization, manually-recor...

5 Saeed Khaki, et al. ∙

∙ 02/15/2021

Meta Back-translation

Back-translation is an effective strategy to improve the performance of ...

0 Hieu Pham, et al. ∙

∙ 02/11/2021

Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

Pre-trained representations are becoming crucial for many NLP and percep...

0 Chao Jia, et al. ∙

∙ 01/05/2021

AutoDropout: Learning Dropout Patterns to Regularize Deep Networks

Neural networks are often over-parameterized and hence benefit from aggr...

7 Hieu Pham, et al. ∙

∙ 12/05/2020

YieldNet: A Convolutional Neural Network for Simultaneous Corn and Soybean Yield Prediction Based on Remote Sensing Data

Large scale crop yield estimation is, in part, made possible due to the ...

0 Saeed Khaki, et al. ∙

∙ 11/09/2020

Towards Domain-Agnostic Contrastive Learning

Despite recent success, most contrastive self-supervised learning method...

0 Vikas Verma, et al. ∙

∙ 10/30/2020

Training EfficientNets at Supercomputer Scale: 83 Accuracy in One Hour

EfficientNets are a family of state-of-the-art image classification mode...

10 Arissa Wongpanich, et al. ∙

∙ 10/23/2020

High-Throughput Image-Based Plant Stand Count Estimation Using Convolutional Neural Networks

The future landscape of modern farming and plant breeding is rapidly cha...

0 Saeed Khaki, et al. ∙

∙ 09/24/2020

Image-Based Sorghum Head Counting When You Only Look Once

Modern trends in digital agriculture have seen a shift towards artificia...

1 Lawrence Mosley, et al. ∙

∙ 07/20/2020

DeepCorn: A Semi-Supervised Deep Learning Method for High-Throughput Image-Based Corn Kernel Counting and Yield Estimation

The success of modern farming and plant breeding relies on accurate and ...

0 Saeed Khaki, et al. ∙

∙ 03/26/2020

Convolutional Neural Networks for Image-based Corn Kernel Detection and Counting

Precise in-season corn grain yield estimates enable farmers to make real...

32 Saeed Khaki, et al. ∙

∙ 03/23/2020

Meta Pseudo Labels

Many training algorithms of a deep neural network can be interpreted as ...

0 Hieu Pham, et al. ∙

∙ 11/22/2019

Optimizing Data Usage via Differentiable Rewards

To acquire a new skill, humans learn better and faster if a tutor, based...

11 Xinyi Wang, et al. ∙

∙ 08/14/2019

Optimizing Ensemble Weights and Hyperparameters of Machine Learning Models for Regression Problems

Aggregating multiple learners through an ensemble of models aims to make...

26 Mohsen Shahhosseini, et al. ∙

∙ 02/09/2019

Multilingual Neural Machine Translation With Soft Decoupled Encoding

Multilingual training of neural machine translation (NMT) systems has le...

0 Xinyi Wang, et al. ∙

∙ 08/28/2018

A Tree-based Decoder for Neural Machine Translation

Recent advances in Neural Machine Translation (NMT) show that adding syn...

0 Xinyi Wang, et al. ∙

∙ 08/22/2018

SwitchOut: an Efficient Data Augmentation Algorithm for Neural Machine Translation

In this work, we examine methods for data augmentation for text-based ta...

0 Xinyi Wang, et al. ∙

∙ 02/09/2018

Efficient Neural Architecture Search via Parameter Sharing

We propose Efficient Neural Architecture Search (ENAS), a fast and inexp...

0 Hieu Pham, et al. ∙

∙ 02/09/2018

Efficient Neural Architecture Search via Parameters Sharing

We propose Efficient Neural Architecture Search (ENAS), a fast and inexp...

0 Hieu Pham, et al. ∙

∙ 06/13/2017

Device Placement Optimization with Reinforcement Learning

The past few years have witnessed a growth in size and computational req...

0 Azalia Mirhoseini, et al. ∙

∙ 11/29/2016

Neural Combinatorial Optimization with Reinforcement Learning

This paper presents a framework to tackle combinatorial optimization pro...

0 Irwan Bello, et al. ∙

∙ 08/17/2015

Effective Approaches to Attention-based Neural Machine Translation

An attentional mechanism has lately been used to improve neural machine ...

0 Minh-Thang Luong, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world