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20122026
most citedA General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems

289 citations · 702 across the 8 of their papers we have counts for

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6 papers · 1 filter

cs.LG2026

OCP: Orthogonal Constrained Projection for Sparse Scaling in Industrial Commodity Recommendation

Chen Sun, Beilin Xu, Boheng Tan +6

In industrial commodity recommendation systems, the representation quality of Item-Id vocabularies directly impacts the scalability and generalization ability of recommendation mod…

cs.LG2022★ 5 cited

Constrained Reinforcement Learning for Short Video Recommendation

Qingpeng Cai, Ruohan Zhan, Chi Zhang +5

The wide popularity of short videos on social media poses new opportunities and challenges to optimize recommender systems on the video-sharing platforms. Users provide complex and…

cs.LG2020

Meta Graph Attention on Heterogeneous Graph with Node-Edge Co-evolution

Yucheng Lin, Huiting Hong, Xiaoqing Yang +3

Graph neural networks have become an important tool for modeling structured data. In many real-world systems, intricate hidden information may exist, e.g., heterogeneity in nodes/e…

cs.LG2020

A Survey on Machine Learning from Few Samples

Jiang Lu, Pinghua Gong, Jieping Ye +2

Few sample learning (FSL) is significant and challenging in the field of machine learning. The capability of learning and generalizing from very few samples successfully is a notic…

cs.LG2018★ 256 cited

Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction

Huaxiu Yao, Fei Wu, Jintao Ke +6

Taxi demand prediction is an important building block to enabling intelligent transportation systems in a smart city. An accurate prediction model can help the city pre-allocate re…

cs.LG2013★ 289 cited

A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems

Pinghua Gong, Changshui Zhang, Zhaosong Lu +2

Non-convex sparsity-inducing penalties have recently received considerable attentions in sparse learning. Recent theoretical investigations have demonstrated their superiority over…