338 citations · 1.4k across the 188 of their papers we have counts for
12 papers · 1 filter
Meta-learning with an Adaptive Task Scheduler
Huaxiu Yao, Yu Wang, Ying Wei +4
To benefit the learning of a new task, meta-learning has been proposed to transfer a well-generalized meta-model learned from various meta-training tasks. Existing meta-learning al…
Fast Variational AutoEncoder with Inverted Multi-Index for Collaborative Filtering
Jin Chen, Defu Lian, Binbin Jin +3
Variational AutoEncoder (VAE) has been extended as a representative nonlinear method for collaborative filtering. However, the bottleneck of VAE lies in the softmax computation ove…
Linear-Time Self Attention with Codeword Histogram for Efficient Recommendation
Yongji Wu, Defu Lian, Neil Zhenqiang Gong +4
Self-attention has become increasingly popular in a variety of sequence modeling tasks from natural language processing to recommendation, due to its effectiveness. However, self-a…
Rethinking Lifelong Sequential Recommendation with Incremental Multi-Interest Attention
Yongji Wu, Lu Yin, Defu Lian +4
Sequential recommendation plays an increasingly important role in many e-commerce services such as display advertisement and online shopping. With the rapid development of these se…
Assessing Dialogue Systems with Distribution Distances
Jiannan Xiang, Yahui Liu, Deng Cai +3
An important aspect of developing dialogue systems is how to evaluate and compare the performance of different systems. Existing automatic evaluation metrics are based on turn-leve…
GraphFormers: GNN-nested Transformers for Representation Learning on Textual Graph
Junhan Yang, Zheng Liu, Shitao Xiao +6
The representation learning on textual graph is to generate low-dimensional embeddings for the nodes based on the individual textual features and the neighbourhood information. Rec…
A Unified Transferable Model for ML-Enhanced DBMS
Ziniu Wu, Pei Yu, Peilun Yang +6
Recently, the database management system (DBMS) community has witnessed the power of machine learning (ML) solutions for DBMS tasks. Despite their promising performance, these exis…
Hybrid Encoder: Towards Efficient and Precise Native AdsRecommendation via Hybrid Transformer Encoding Networks
Junhan Yang, Zheng Liu, Bowen Jin +7
Transformer encoding networks have been proved to be a powerful tool of understanding natural languages. They are playing a critical role in native ads service, which facilitates t…
Matching-oriented Product Quantization For Ad-hoc Retrieval
Shitao Xiao, Zheng Liu, Yingxia Shao +2
Product quantization (PQ) is a widely used technique for ad-hoc retrieval. Recent studies propose supervised PQ, where the embedding and quantization models can be jointly trained…
Efficient Optimal Selection for Composited Advertising Creatives with Tree Structure
Jin Chen, Tiezheng Ge, Gangwei Jiang +3
Ad creatives are one of the prominent mediums for online e-commerce advertisements. Ad creatives with enjoyable visual appearance may increase the click-through rate (CTR) of produ…
Automated Creative Optimization for E-Commerce Advertising
Jin Chen, Ju Xu, Gangwei Jiang +4
Advertising creatives are ubiquitous in E-commerce advertisements and aesthetic creatives may improve the click-through rate (CTR) of the products. Nowadays smart advertisement pla…
A Hybrid Bandit Model with Visual Priors for Creative Ranking in Display Advertising
Shiyao Wang, Qi Liu, Tiezheng Ge +2
Creative plays a great important role in e-commerce for exhibiting products. Sellers usually create multiple creatives for comprehensive demonstrations, thus it is crucial to displ…