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07/19/2023
DisCover: Disentangled Music Representation Learning for Cover Song Identification
In the field of music information retrieval (MIR), cover song identifica...
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06/15/2023
ReLoop2: Building Self-Adaptive Recommendation Models via Responsive Error Compensation Loop
Industrial recommender systems face the challenge of operating in non-st...
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04/03/2023
FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction
Click-through rate (CTR) prediction is one of the fundamental tasks for ...
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04/02/2023
FANS: Fast Non-Autoregressive Sequence Generation for Item List Continuation
User-curated item lists, such as video-based playlists on Youtube and bo...
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10/18/2022
IntTower: the Next Generation of Two-Tower Model for Pre-Ranking System
Scoring a large number of candidates precisely in several milliseconds i...
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09/05/2022
A Brief History of Recommender Systems
Soon after the invention of the Internet, the recommender system emerged...
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08/15/2022
Debiased Recommendation with Neural Stratification
Debiased recommender models have recently attracted increasing attention...
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07/09/2022
Explainable Legal Case Matching via Inverse Optimal Transport-based Rationale Extraction
As an essential operation of legal retrieval, legal case matching plays ...
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04/01/2022
Sequential Recommendation with Causal Behavior Discovery
The key of sequential recommendation lies in the accurate item correlati...
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09/26/2021
SimpleX: A Simple and Strong Baseline for Collaborative Filtering
Collaborative filtering (CF) is a widely studied research topic in recom...
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03/05/2021
Non-invasive Self-attention for Side Information Fusion in Sequential Recommendation
Sequential recommender systems aim to model users' evolving interests fr...
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04/14/2020
Personalized Re-ranking for Improving Diversity in Live Recommender Systems
Users of industrial recommender systems are normally suggesteda list of ...
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01/22/2020
MetaSelector: Meta-Learning for Recommendation with User-Level Adaptive Model Selection
Recommender systems often face heterogeneous datasets containing highly ...
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12/03/2019
Less Is Better: Unweighted Data Subsampling via Influence Function
In the time of Big Data, training complex models on large-scale data set...
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07/05/2019
Uncovering Download Fraud Activities in Mobile App Markets
Download fraud is a prevalent threat in mobile App markets, where frauds...
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04/12/2018
DeepFM: An End-to-End Wide & Deep Learning Framework for CTR Prediction
Learning sophisticated feature interactions behind user behaviors is cri...
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02/22/2018