Zhao Chen

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IEEE ∙ Columbia University ∙ Magic Leap, Inc.

Just Pick a Sign: Optimizing Deep Multitask Models with Gradient Sign Dropout

The vast majority of deep models use multiple gradient signals, typicall...
10/14/2020 ∙ by Zhao Chen, et al. ∙ 0 ∙ share

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Sparse representation for damage identification of structural systems

Identifying damage of structural systems is typically characterized as a...
06/06/2020 ∙ by Zhao Chen, et al. ∙ 0 ∙ share

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Taskology: Utilizing Task Relations at Scale

It has been recognized that the joint training of computer vision tasks ...
05/14/2020 ∙ by Yao Lu, et al. ∙ 1 ∙ share

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Deep learning of physical laws from scarce data

Harnessing data to discover the underlying governing laws or equations t...
05/05/2020 ∙ by Zhao Chen, et al. ∙ 9 ∙ share

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DeepPerimeter: Indoor Boundary Estimation from Posed Monocular Sequences

We present DeepPerimeter, a deep learning based pipeline for inferring a...
04/25/2019 ∙ by Ameya Phalak, et al. ∙ 10 ∙ share

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Decentralized Computation Offloading for Multi-User Mobile Edge Computing: A Deep Reinforcement Learning Approach

Mobile edge computing (MEC) emerges recently as a promising solution to ...
12/16/2018 ∙ by Zhao Chen, et al. ∙ 0 ∙ share

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Gradient Adversarial Training of Neural Networks

We propose gradient adversarial training, an auxiliary deep learning fra...
06/21/2018 ∙ by Ayan Sinha, et al. ∙ 8 ∙ share

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A Stochastic Geometry Analysis of Energy Harvesting in Large Scale Wireless Networks

In this paper, the theoretical sustainable capacity of wireless networks...
06/02/2018 ∙ by Ziru Chen, et al. ∙ 0 ∙ share

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Beamforming Design for Max-Min Fair SWIPT in Green Cloud-RAN with Wireless Fronthaul

In this paper, a joint beamforming design for max-min fair simultaneous ...
05/06/2018 ∙ by Zhao Chen, et al. ∙ 0 ∙ share

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Estimating Depth from RGB and Sparse Sensing

We present a deep model that can accurately produce dense depth maps giv...
04/08/2018 ∙ by Zhao Chen, et al. ∙ 0 ∙ share

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A Hybrid Approach for Efficient Wireless Information and Power Transfer in Green C-RAN

In this paper, we consider a green cloud radio access network (C-RAN) wi...
03/28/2018 ∙ by Xu Li, et al. ∙ 0 ∙ share

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GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks

Deep multitask networks, in which one neural network produces multiple p...
11/07/2017 ∙ by Zhao Chen, et al. ∙ 0 ∙ share

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3-D Convolutional Neural Networks for Glioblastoma Segmentation

Convolutional Neural Networks (CNN) have emerged as powerful tools for l...
11/14/2016 ∙ by Darvin Yi, et al. ∙ 0 ∙ share

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Zhao Chen

Featured Co-authors

Yang Liu

Yu Cheng

Xiaodong Wang

Hao Sun

Anelia Angelova

Yao Lu

Xu Li

Dragomir Anguelov

Andrew Rabinovich

Vijay Badrinarayanan

Jiquan Ngiam

Just Pick a Sign: Optimizing Deep Multitask Models with Gradient Sign Dropout

Sparse representation for damage identification of structural systems

Taskology: Utilizing Task Relations at Scale

Deep learning of physical laws from scarce data

DeepPerimeter: Indoor Boundary Estimation from Posed Monocular Sequences

Decentralized Computation Offloading for Multi-User Mobile Edge Computing: A Deep Reinforcement Learning Approach

Gradient Adversarial Training of Neural Networks

A Stochastic Geometry Analysis of Energy Harvesting in Large Scale Wireless Networks

Beamforming Design for Max-Min Fair SWIPT in Green Cloud-RAN with Wireless Fronthaul

Estimating Depth from RGB and Sparse Sensing

A Hybrid Approach for Efficient Wireless Information and Power Transfer in Green C-RAN

GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks

3-D Convolutional Neural Networks for Glioblastoma Segmentation