activity
20172024
most citedLightweight Self-Attentive Sequential Recommendation

111 citations · 801 across the 59 of their papers we have counts for

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Showing 2023Show all

20 papers · 1 filter

cs.IR2023

On-Device Recommender Systems: A Tutorial on The New-Generation Recommendation Paradigm

Hongzhi Yin, Tong Chen, Liang Qu +1

Given the sheer volume of contemporary e-commerce applications, recommender systems (RSs) have gained significant attention in both academia and industry. However, traditional clou…

cs.IR2023★ 1 cited

Adversarial Item Promotion on Visually-Aware Recommender Systems by Guided Diffusion

Lijian Chen, Wei Yuan, Tong Chen +3

Visually-aware recommender systems have found widespread application in domains where visual elements significantly contribute to the inference of users' potential preferences. Whi…

cs.LG2023

Unraveling the "Anomaly" in Time Series Anomaly Detection: A Self-supervised Tri-domain Solution

Yuting Sun, Guansong Pang, Guanhua Ye +3

The ongoing challenges in time series anomaly detection (TSAD), notably the scarcity of anomaly labels and the variability in anomaly lengths and shapes, have led to the need for a…

cs.IR2023

Budgeted Embedding Table For Recommender Systems

Yunke Qu, Tong Chen, Quoc Viet Hung Nguyen +1

At the heart of contemporary recommender systems (RSs) are latent factor models that provide quality recommendation experience to users. These models use embedding vectors, which a…

cs.LG2023

To Predict or to Reject: Causal Effect Estimation with Uncertainty on Networked Data

Hechuan Wen, Tong Chen, Li Kheng Chai +3

Due to the imbalanced nature of networked observational data, the causal effect predictions for some individuals can severely violate the positivity/overlap assumption, rendering u…

cs.IR2023★ 1 cited

Learning Compact Compositional Embeddings via Regularized Pruning for Recommendation

Xurong Liang, Tong Chen, Quoc Viet Hung Nguyen +2

Latent factor models are the dominant backbones of contemporary recommender systems (RSs) given their performance advantages, where a unique vector embedding with a fixed dimension…