activity
20172021
most citedPBODL : Parallel Bayesian Online Deep Learning for Click-Through Rate Prediction in Tencent Advertising System

14 citations · 33 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG202112 cited

Follow the Prophet: Accurate Online Conversion Rate Prediction in the Face of Delayed Feedback

Haoming Li, Feiyang Pan, Xiang Ao +6

The delayed feedback problem is one of the imperative challenges in online advertising, which is caused by the highly diversified feedback delay of a conversion varying from a few…

cs.CV2020

RUArt: A Novel Text-Centered Solution for Text-Based Visual Question Answering

Zan-Xia Jin, Heran Wu, Chun Yang +4

Text-based visual question answering (VQA) requires to read and understand text in an image to correctly answer a given question. However, most current methods simply add optical c…

cs.LG2019

Field-aware Calibration: A Simple and Empirically Strong Method for Reliable Probabilistic Predictions

Feiyang Pan, Xiang Ao, Pingzhong Tang +4

It is often observed that the probabilistic predictions given by a machine learning model can disagree with averaged actual outcomes on specific subsets of data, which is also know…

cs.CV20177 cited

AdaDNNs: Adaptive Ensemble of Deep Neural Networks for Scene Text Recognition

Chun Yang, Xu-Cheng Yin, Zejun Li +4

Recognizing text in the wild is a really challenging task because of complex backgrounds, various illuminations and diverse distortions, even with deep neural networks (convolution…

cs.LG201714 cited

PBODL : Parallel Bayesian Online Deep Learning for Click-Through Rate Prediction in Tencent Advertising System

Xun Liu, Wei Xue, Lei Xiao +1

We describe a parallel bayesian online deep learning framework (PBODL) for click-through rate (CTR) prediction within today's Tencent advertising system, which provides quick and a…