Search Results for author: Qingtao Tang

Found 5 papers, 2 papers with code

Hybrid CNN Based Attention with Category Prior for User Image Behavior Modeling

no code implementations5 May 2022 Xin Chen, Qingtao Tang, Ke Hu, Yue Xu, Shihang Qiu, Jia Cheng, Jun Lei

In Meituan, one of the largest e-commerce platform in China, an item is typically displayed with its image and whether a user clicks the item or not is usually influenced by its image, which implies that user's image behaviors are helpful for understanding user's visual preference and improving the accuracy of CTR prediction.

Click-Through Rate Prediction

Deep Position-wise Interaction Network for CTR Prediction

1 code implementation10 Jun 2021 Jianqiang Huang, Ke Hu, Qingtao Tang, Mingjian Chen, Yi Qi, Jia Cheng, Jun Lei

Click-through rate (CTR) prediction plays an important role in online advertising and recommender systems.

Click-Through Rate Prediction Position +1

JSRT: James-Stein Regression Tree

no code implementations18 Oct 2020 Xingchun Xiang, Qingtao Tang, Huaixuan Zhang, Tao Dai, Jiawei Li, Shu-Tao Xia

To address this issue, we propose a novel regression tree, named James-Stein Regression Tree (JSRT) by considering global information from different nodes.

regression

$t$-$k$-means: A Robust and Stable $k$-means Variant

1 code implementation17 Jul 2019 Yiming Li, Yang Zhang, Qingtao Tang, Weipeng Huang, Yong Jiang, Shu-Tao Xia

$k$-means algorithm is one of the most classical clustering methods, which has been widely and successfully used in signal processing.

Clustering

Learning from Noisy Web Data with Category-level Supervision

no code implementations CVPR 2018 Li Niu, Qingtao Tang, Ashok Veeraraghavan, Ashu Sabharwal

As tons of photos are being uploaded to public websites (e. g., Flickr, Bing, and Google) every day, learning from web data has become an increasingly popular research direction because of freely available web resources, which is also referred to as webly supervised learning.

General Classification

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