no code implementations • 16 Feb 2023 • Itai Ashlagi, Mark Braverman, Geng Zhao
In the model, each agent has a latent personal score for every agent on the other side of the market and her preferences follow a logit model based on these scores.
no code implementations • 27 Jan 2023 • Geng Zhao, Banghua Zhu, Jiantao Jiao, Michael I. Jordan
We analyze the sample complexity of regret minimization in this repeated Stackelberg game.
no code implementations • 21 Aug 2022 • Venkatesh Rammamoorthy, Geng Zhao, Bharathi Reddy, Ming-Yang Lin
The advent of deep learning has resulted in a number of applications which have transformed the landscape of the research area in which it has been applied.
2 code implementations • 11 Jul 2019 • Xin Jin, Le Wu, Geng Zhao, Xiao-Dong Li, Xiaokun Zhang, Shiming Ge, Dongqing Zou, Bin Zhou, Xinghui Zhou
This is a new formula of image aesthetic assessment, which predicts aesthetic attributes captions together with the aesthetic score of each attribute.
no code implementations • 25 Sep 2017 • Xin Jin, Shuyun Zhu, Le Wu, Geng Zhao, Xiao-Dong Li, Quan Zhou, Huimin Lu
In this work, a multi-level chaotic maps models for 3D textured encryption was presented by observing the different contributions for recognizing cipher 3D models between vertices (point cloud), polygons and textures.
2 code implementations • 23 Aug 2017 • Xin Jin, Le Wu, Xiao-Dong Li, Siyu Chen, Siwei Peng, Jingying Chi, Shiming Ge, Chenggen Song, Geng Zhao
Thus, a novel CNN based on the Cumulative distribution with Jensen-Shannon divergence (CJS-CNN) is presented to predict the aesthetic score distribution of human ratings, with a new reliability-sensitive learning method based on the kurtosis of the score distribution, which eliminates the requirement of the original full data of human ratings (without normalization).
no code implementations • 27 Feb 2017 • Xin Jin, Peng Yuan, Xiao-Dong Li, Chenggen Song, Shiming Ge, Geng Zhao, Yingya Chen
Only the base images are submitted randomly to the cloud server.
2 code implementations • 7 Oct 2016 • Xin Jin, Le Wu, Xiao-Dong Li, Xiaokun Zhang, Jingying Chi, Siwei Peng, Shiming Ge, Geng Zhao, Shuying Li
Thus, it is easy to use a pre-trained GoogLeNet for large-scale image classification problem and fine tune our connected layers on an large scale database of aesthetic related images: AVA, i. e. \emph{domain adaptation}.