56 citations · 114 across the 6 of their papers we have counts for
6 papers
AdaTask: A Task-aware Adaptive Learning Rate Approach to Multi-task Learning
Enneng Yang, Junwei Pan, Ximei Wang +6
Multi-task learning (MTL) models have demonstrated impressive results in computer vision, natural language processing, and recommender systems. Even though many approaches have bee…
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…
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…
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…
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…
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…