Search Results for author: Xiao Dong

Found 11 papers, 0 papers with code

M5Product: A Multi-modal Pretraining Benchmark for E-commercial Product Downstream Tasks

no code implementations9 Sep 2021 Xiao Dong, Xunlin Zhan, Yangxin Wu, Yunchao Wei, XiaoYong Wei, Minlong Lu, Xiaodan Liang

In this paper, we aim to advance the research of multi-modal pre-training on E-commerce and subsequently contribute a large-scale dataset, named M5Product, which consists of over 6 million multimodal pairs, covering more than 6, 000 categories and 5, 000 attributes.

Product1M: Towards Weakly Supervised Instance-Level Product Retrieval via Cross-modal Pretraining

no code implementations ICCV 2021 Xunlin Zhan, Yangxin Wu, Xiao Dong, Yunchao Wei, Minlong Lu, Yichi Zhang, Hang Xu, Xiaodan Liang

In this paper, we investigate a more realistic setting that aims to perform weakly-supervised multi-modal instance-level product retrieval among fine-grained product categories.

Pinpointing the Memory Behaviors of DNN Training

no code implementations1 Apr 2021 Jiansong Li, Xiao Dong, Guangli Li, Peng Zhao, Xueying Wang, Xiaobing Chen, Xianzhi Yu, Yongxin Yang, Zihan Jiang, Wei Cao, Lei Liu, Xiaobing Feng

The training of deep neural networks (DNNs) is usually memory-hungry due to the limited device memory capacity of DNN accelerators.

A Unified Joint Maximum Mean Discrepancy for Domain Adaptation

no code implementations25 Jan 2021 Wei Wang, Baopu Li, Shuhui Yang, Jing Sun, Zhengming Ding, Junyang Chen, Xiao Dong, Zhihui Wang, Haojie Li

From the revealed unified JMMD, we illustrate that JMMD degrades the feature-label dependence (discriminability) that benefits to classification, and it is sensitive to the label distribution shift when the label kernel is the weighted class conditional one.

Domain Adaptation

Adaptive Collaborative Similarity Learning for Unsupervised Multi-view Feature Selection

no code implementations25 Apr 2019 Xiao Dong, Lei Zhu, Xuemeng Song, Jingjing Li, Zhiyong Cheng

We propose to dynamically learn the collaborative similarity structure, and further integrate it with the ultimate feature selection into a unified framework.

Feature Selection

Understanding over-parameterized deep networks by geometrization

no code implementations11 Feb 2019 Xiao Dong, Ling Zhou

This can be regarded as a strong support of our proposal that geometrization is not only the bible for physics, it is also the key idea to understand deep learning systems.

Geometrization of deep networks for the interpretability of deep learning systems

no code implementations6 Jan 2019 Xiao Dong, Ling Zhou

By comparing the geometry of image matching and deep networks, we show that geometrization of deep networks can be used to understand existing deep learning systems and it may also help to solve the interpretability problem of deep learning systems.

Auto-tuning Neural Network Quantization Framework for Collaborative Inference Between the Cloud and Edge

no code implementations16 Dec 2018 Guangli Li, Lei Liu, Xueying Wang, Xiao Dong, Peng Zhao, Xiaobing Feng

By analyzing the characteristics of layers in DNNs, an auto-tuning neural network quantization framework for collaborative inference is proposed.

Quantization

Demystifying AlphaGo Zero as AlphaGo GAN

no code implementations24 Nov 2017 Xiao Dong, Jiasong Wu, Ling Zhou

The astonishing success of AlphaGo Zero\cite{Silver_AlphaGo} invokes a worldwide discussion of the future of our human society with a mixed mood of hope, anxiousness, excitement and fear.

How deep learning works --The geometry of deep learning

no code implementations30 Oct 2017 Xiao Dong, Jiasong Wu, Ling Zhou

Why and how that deep learning works well on different tasks remains a mystery from a theoretical perspective.

Template Matching

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