Chao Ma

A Mean-field Analysis of Deep ResNet and Beyond: Towards Provable Optimization Via Overparameterization From Depth

Training deep neural networks with stochastic gradient descent (SGD) can...
03/11/2020 ∙ by Yiping Lu, et al. ∙ 42 ∙ share

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Machine Learning from a Continuous Viewpoint

We present a continuous formulation of machine learning, as a problem in...
12/30/2019 ∙ by Weinan E, et al. ∙ 32 ∙ share

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A Comparative Analysis of the Optimization and Generalization Property of Two-layer Neural Network and Random Feature Models Under Gradient Descent Dynamics

A fairly comprehensive analysis is presented for the gradient descent dy...
04/08/2019 ∙ by Weinan E, et al. ∙ 24 ∙ share

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Unsupervised Deep Tracking

We propose an unsupervised visual tracking method in this paper. Differe...
04/03/2019 ∙ by Ning Wang, et al. ∙ 16 ∙ share

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See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks

We introduce a novel network, called CO-attention Siamese Network (COSNe...
01/19/2020 ∙ by Xiankai Lu, et al. ∙ 16 ∙ share

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Analysis of the Gradient Descent Algorithm for a Deep Neural Network Model with Skip-connections

The behavior of the gradient descent (GD) algorithm is analyzed for a de...
04/10/2019 ∙ by Weinan E, et al. ∙ 14 ∙ share

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Depth-Aware Video Frame Interpolation

Video frame interpolation aims to synthesize nonexistent frames in-betwe...
04/01/2019 ∙ by Wenbo Bao, et al. ∙ 10 ∙ share

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On the Generalization Properties of Minimum-norm Solutions for Over-parameterized Neural Network Models

We study the generalization properties of minimum-norm solutions for thr...
12/15/2019 ∙ by Weinan E, et al. ∙ 10 ∙ share

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Deep Image Deraining Via Intrinsic Rainy Image Priors and Multi-scale Auxiliary Decoding

Different rain models and novel network structures have been proposed to...
11/25/2019 ∙ by Yinglong Wang, et al. ∙ 9 ∙ share

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EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE

Making decisions requires information relevant to the task at hand. Many...
09/28/2018 ∙ by Chao Ma, et al. ∙ 6 ∙ share

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A Priori Estimates of the Population Risk for Residual Networks

Optimal a priori estimates are derived for the population risk of a regu...
03/06/2019 ∙ by Weinan E, et al. ∙ 6 ∙ share

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Deep Attentive Tracking via Reciprocative Learning

Visual attention, derived from cognitive neuroscience, facilitates human...
10/09/2018 ∙ by Shi Pu, et al. ∙ 4 ∙ share

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Deep Single Image Deraining Via Estimating Transmission and Atmospheric Light in rainy Scenes

Rain removal in images/videos is still an important task in computer vis...
06/22/2019 ∙ by Yinglong Wang, et al. ∙ 4 ∙ share

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Real-Time Correlation Tracking via Joint Model Compression and Transfer

Correlation filters (CF) have received considerable attention in visual ...
07/23/2019 ∙ by Ning Wang, et al. ∙ 3 ∙ share

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Barron Spaces and the Compositional Function Spaces for Neural Network Models

One of the key issues in the analysis of machine learning models is to i...
06/18/2019 ∙ by Weinan E, et al. ∙ 1 ∙ share

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Deep Extreme Feature Extraction: New MVA Method for Searching Particles in High Energy Physics

In this paper, we present Deep Extreme Feature Extraction (DEFE), a new ...
03/24/2016 ∙ by Chao Ma, et al. ∙ 0 ∙ share

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Robust Visual Tracking via Hierarchical Convolutional Features

Visual tracking is challenging as target objects often undergo significa...
07/12/2017 ∙ by Chao Ma, et al. ∙ 0 ∙ share

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Adaptive Correlation Filters with Long-Term and Short-Term Memory for Object Tracking

Object tracking is challenging as target objects often undergo drastic a...
07/07/2017 ∙ by Chao Ma, et al. ∙ 0 ∙ share

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Person Re-Identification via Recurrent Feature Aggregation

We address the person re-identification problem by effectively exploitin...
01/23/2017 ∙ by Yichao Yan, et al. ∙ 0 ∙ share

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Learning a No-Reference Quality Metric for Single-Image Super-Resolution

Numerous single-image super-resolution algorithms have been proposed in ...
12/18/2016 ∙ by Chao Ma, et al. ∙ 0 ∙ share

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Visual Question Answering with Memory-Augmented Networks

This paper exploits a memory-augmented neural network to predict accurat...
07/17/2017 ∙ by Chao Ma, et al. ∙ 0 ∙ share

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VITAL: VIsual Tracking via Adversarial Learning

The tracking-by-detection framework consists of two stages, i.e., drawin...
04/12/2018 ∙ by Yibing Song, et al. ∙ 0 ∙ share

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Variational Implicit Processes

This paper introduces the variational implicit processes (VIPs), a Bayes...
06/06/2018 ∙ by Chao Ma, et al. ∙ 0 ∙ share

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CREST: Convolutional Residual Learning for Visual Tracking

Discriminative correlation filters (DCFs) have been shown to perform sup...
08/01/2017 ∙ by Yibing Song, et al. ∙ 0 ∙ share

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Joint Neural Entity Disambiguation with Output Space Search

In this paper, we present a novel model for entity disambiguation that c...
06/19/2018 ∙ by Hamed Shahbazi, et al. ∙ 0 ∙ share

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Model Reduction with Memory and the Machine Learning of Dynamical Systems

The well-known Mori-Zwanzig theory tells us that model reduction leads t...
08/10/2018 ∙ by Chao Ma, et al. ∙ 0 ∙ share

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A Priori Estimates of the Generalization Error for Two-layer Neural Networks

New estimates for the generalization error are established for the two-l...
10/15/2018 ∙ by Weinan E, et al. ∙ 0 ∙ share

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Person-Job Fit: Adapting the Right Talent for the Right Job with Joint Representation Learning

Person-Job Fit is the process of matching the right talent for the right...
10/08/2018 ∙ by Chen Zhu, et al. ∙ 0 ∙ share

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Target-Aware Deep Tracking

Existing deep trackers mainly use convolutional neural networks pre-trai...
04/03/2019 ∙ by Xin Li, et al. ∙ 0 ∙ share

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Global Convergence of Gradient Descent for Deep Linear Residual Networks

We analyze the global convergence of gradient descent for deep linear re...
11/02/2019 ∙ by Lei Wu, et al. ∙ 0 ∙ share

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Chao Ma

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