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20152022
most citedA Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges

2.7k citations · 5.1k across the 51 of their papers we have counts for

collaborators
Showing 2016Show all

6 papers · 1 filter

cs.HC2016

Parsimonious Mixed-Effects HodgeRank for Crowdsourced Preference Aggregation

Qianqian Xu, Jiechao Xiong, Xiaochun Cao +1

In crowdsourced preference aggregation, it is often assumed that all the annotators are subject to a common preference or utility function which generates their comparison behavior…

cs.CV2016★ 4 cited

CUNet: A Compact Unsupervised Network for Image Classification

Le Dong, Ling He, Gaipeng Kong +3

In this paper, we propose a compact network called CUNet (compact unsupervised network) to counter the image classification challenge. Different from the traditional convolutional…

cs.CV2016★ 3 cited

A Hierarchical Distributed Processing Framework for Big Image Data

Le Dong, Zhiyu Lin, Yan Liang +5

This paper introduces an effective processing framework nominated ICP (Image Cloud Processing) to powerfully cope with the data explosion in image processing field. While most prev…

stat.ML2016★ 4 cited

False Discovery Rate Control and Statistical Quality Assessment of Annotators in Crowdsourced Ranking

Qianqian Xu, Jiechao Xiong, Xiaochun Cao +1

With the rapid growth of crowdsourcing platforms it has become easy and relatively inexpensive to collect a dataset labeled by multiple annotators in a short time. However due to t…

cs.CV2016★ 74 cited

Makeup like a superstar: Deep Localized Makeup Transfer Network

Si Liu, Xinyu Ou, Ruihe Qian +2

In this paper, we propose a novel Deep Localized Makeup Transfer Network to automatically recommend the most suitable makeup for a female and synthesis the makeup on her face. Give…

cs.CV2016

Quadratic Projection Based Feature Extraction with Its Application to Biometric Recognition

Yan Yan, Hanzi Wang, Si Chen +2

This paper presents a novel quadratic projection based feature extraction framework, where a set of quadratic matrices is learned to distinguish each class from all other classes.…