Search Results for author: Dapeng Liu

Found 8 papers, 2 papers with code

Decoupled Training: Return of Frustratingly Easy Multi-Domain Learning

no code implementations19 Sep 2023 Ximei Wang, Junwei Pan, Xingzhuo Guo, Dapeng Liu, Jie Jiang

Multi-domain learning (MDL) aims to train a model with minimal average risk across multiple overlapping but non-identical domains.

Recommendation Systems

Generic and Robust Root Cause Localization for Multi-Dimensional Data in Online Service Systems

1 code implementation5 May 2023 Zeyan Li, Junjie Chen, Yihao Chen, Chengyang Luo, Yiwei Zhao, Yongqian Sun, Kaixin Sui, Xiping Wang, Dapeng Liu, Xing Jin, Qi Wang, Dan Pei

Such attribute combinations are substantial clues to the underlying root causes and thus are called root causes of multidimensional data.

AutoAttention: Automatic Field Pair Selection for Attention in User Behavior Modeling

no code implementations27 Oct 2022 Zuowu Zheng, Xiaofeng Gao, Junwei Pan, Qi Luo, Guihai Chen, Dapeng Liu, Jie Jiang

In this paper, we propose a novel model named AutoAttention, which includes all item/user/context side fields as the query, and assigns a learnable weight for each field pair between behavior fields and query fields.

Click-Through Rate Prediction

Cross-Task Knowledge Distillation in Multi-Task Recommendation

no code implementations20 Feb 2022 Chenxiao Yang, Junwei Pan, Xiaofeng Gao, Tingyu Jiang, Dapeng Liu, Guihai Chen

Multi-task learning (MTL) has been widely used in recommender systems, wherein predicting each type of user feedback on items (e. g, click, purchase) are treated as individual tasks and jointly trained with a unified model.

Knowledge Distillation Multi-Task Learning +1

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

1 code implementation13 Aug 2021 Haoming Li, Feiyang Pan, Xiang Ao, Zhao Yang, Min Lu, Junwei Pan, Dapeng Liu, Lei Xiao, Qing He

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 minutes to several days.

Convolutional Normalizing Flows for Deep Gaussian Processes

no code implementations17 Apr 2021 Haibin Yu, Dapeng Liu, Yizhou Chen, Bryan Kian Hsiang Low, Patrick Jaillet

Deep Gaussian processes (DGPs), a hierarchical composition of GP models, have successfully boosted the expressive power of their single-layer counterpart.

Gaussian Processes Variational Inference

Decision Making for Autonomous Driving via Augmented Adversarial Inverse Reinforcement Learning

no code implementations19 Nov 2019 Pin Wang, Dapeng Liu, Jiayu Chen, Hanhan Li, Ching-Yao Chan

Simulation results show that the augmented AIRL outperforms all the baseline methods, and its performance is comparable with that of the experts on all of the four metrics.

Autonomous Driving Imitation Learning +2

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

no code implementations26 May 2019 Feiyang Pan, Xiang Ao, Pingzhong Tang, Min Lu, Dapeng Liu, Lei Xiao, Qing He

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 known as the issue of miscalibration.

BIG-bench Machine Learning Click-Through Rate Prediction

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