Reloop: A self-correction continual learning loop for recommender systems
Deep learning-based recommendation has become a widely adopted technique in various
online applications. Typically, a deployed model undergoes frequent re-training to capture …
online applications. Typically, a deployed model undergoes frequent re-training to capture …
Auc maximization in imbalanced lifelong learning
Imbalanced data is ubiquitous in machine learning, such as medical or fine-grained image
datasets. The existing continual learning methods employ various techniques such as …
datasets. The existing continual learning methods employ various techniques such as …
Multi-Epoch learning with Data Augmentation for Deep Click-Through Rate Prediction
This paper investigates the one-epoch overfitting phenomenon in Click-Through Rate (CTR)
models, where performance notably declines at the start of the second epoch. Despite …
models, where performance notably declines at the start of the second epoch. Despite …
RelayRec: Empowering Privacy-Preserving CTR Prediction via Cloud-Device Relay Learning
Click-through rate (CTR) prediction holds paramount importance across numerous
applications, profoundly impacting user experience and business profitability. The freshness …
applications, profoundly impacting user experience and business profitability. The freshness …
Investigating the effects of incremental training on neural ranking models
B Schifferer, W Shi, GDSP Moreira, E Oldridge… - Proceedings of the 17th …, 2023 - dl.acm.org
Recommender systems are an essential component of online platforms providing users with
personalized experiences. Some recommendation scenarios such as social networks and …
personalized experiences. Some recommendation scenarios such as social networks and …
Capturing Dynamic User Behavior in Recommender Systems by Finetuning
F Durmuş, B Türkmen, MS Aldemir… - 2023 8th International …, 2023 - ieeexplore.ieee.org
The amount of digital content is increasing significantly. Thus, it is important for companies to
show the most relevant digital advertisements to the users to maximize their profits and i …
show the most relevant digital advertisements to the users to maximize their profits and i …
Imbalanced Lifelong Learning with AUC Maximization
Imbalanced data is ubiquitous in machine learning, such as medical or fine-grained image
datasets. The existing continual learning methods employ various techniques such as …
datasets. The existing continual learning methods employ various techniques such as …