AutoML for RecSys

Recommender Systems Neural Architecture Search Automated Machine Learning Deep Learning AutoML for RecSys

Towards Automated Model Design on Recommender Systems

A weight-sharing supernet paradigm for joint architecture search and Processing-In-Memory hardware co-design of deep recommender models.

Tunhou zhang
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Recommender Systems Neural Architecture Search Weight Sharing Path Sampling Deep Learning AutoML for RecSys

Farthest Greedy Path Sampling for Two-shot Recommender Search

We introduce Farthest Greedy Path Sampling (FGPS) for Two-shot Neural Architecture Search (TS-NAS) in recommender systems, achieving state-of-the-art performance on CTR prediction …

Yufan cao
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