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05/17/2023
DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining
The mixture proportions of pretraining data domains (e.g., Wikipedia, bo...
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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...
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02/13/2023
Symbolic Discovery of Optimization Algorithms
We present a method to formulate algorithm discovery as program search, ...
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12/27/2022
MixupE: Understanding and Improving Mixup from Directional Derivative Perspective
Mixup is a popular data augmentation technique for training deep neural ...
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11/19/2021
Combined Scaling for Zero-shot Transfer Learning
We present a combined scaling method called BASIC that achieves 85.7 zer...
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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...
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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...
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02/15/2021
Meta Back-translation
Back-translation is an effective strategy to improve the performance of ...
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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...
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01/05/2021
AutoDropout: Learning Dropout Patterns to Regularize Deep Networks
Neural networks are often over-parameterized and hence benefit from aggr...
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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 ...
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11/09/2020
Towards Domain-Agnostic Contrastive Learning
Despite recent success, most contrastive self-supervised learning method...
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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...
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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...
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09/24/2020
Image-Based Sorghum Head Counting When You Only Look Once
Modern trends in digital agriculture have seen a shift towards artificia...
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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 ...
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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...
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03/23/2020
Meta Pseudo Labels
Many training algorithms of a deep neural network can be interpreted as ...
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11/22/2019
Optimizing Data Usage via Differentiable Rewards
To acquire a new skill, humans learn better and faster if a tutor, based...
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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...
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02/09/2019
Multilingual Neural Machine Translation With Soft Decoupled Encoding
Multilingual training of neural machine translation (NMT) systems has le...
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08/28/2018
A Tree-based Decoder for Neural Machine Translation
Recent advances in Neural Machine Translation (NMT) show that adding syn...
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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...
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02/09/2018
Efficient Neural Architecture Search via Parameter Sharing
We propose Efficient Neural Architecture Search (ENAS), a fast and inexp...
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02/09/2018
Efficient Neural Architecture Search via Parameters Sharing
We propose Efficient Neural Architecture Search (ENAS), a fast and inexp...
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06/13/2017
Device Placement Optimization with Reinforcement Learning
The past few years have witnessed a growth in size and computational req...
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11/29/2016
Neural Combinatorial Optimization with Reinforcement Learning
This paper presents a framework to tackle combinatorial optimization pro...
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08/17/2015
