2 citations · 5 across the 13 of their papers we have counts for
4 papers · 1 filter
SiGeo: Sub-One-Shot NAS via Information Theory and Geometry of Loss Landscape
Hua Zheng, Kuang-Hung Liu, Igor Fedorov +3
Neural Architecture Search (NAS) has become a widely used tool for automating neural network design. While one-shot NAS methods have successfully reduced computational requirements…
AutoML for Large Capacity Modeling of Meta's Ranking Systems
Hang Yin, Kuang-Hung Liu, Mengying Sun +16
Web-scale ranking systems at Meta serving billions of users is complex. Improving ranking models is essential but engineering heavy. Automated Machine Learning (AutoML) can release…
Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale
Wei Wen, Kuang-Hung Liu, Igor Fedorov +19
Neural Architecture Search (NAS) has demonstrated its efficacy in computer vision and potential for ranking systems. However, prior work focused on academic problems, which are eva…
DistDNAS: Search Efficient Feature Interactions within 2 Hours
Tunhou Zhang, Wei Wen, Igor Fedorov +8
Search efficiency and serving efficiency are two major axes in building feature interactions and expediting the model development process in recommender systems. On large-scale ben…