Shampoo is an online and stochastic optimization algorithm belonging to the AdaGrad
family of methods for training neural networks. It constructs a block-diagonal preconditioner …

We study a mismatch between the deep learning recommendation models' flat architecture,
common distributedtraining paradigm and hierarchical data center topology. To address the …

Training recommendation systems (RecSys) faces several challenges as it requires the
“data preprocessing” stage to preprocess an ample amount of raw data and feed them to the …

Over recent years, news recommender systems have gained significant attention in both
academia and industry, emphasizing the need for a standardized benchmark to evaluate …

Recommendation models are an important category of deep learning models whose size is
growing enormous. They consist of a sparse part with TBs of memory footprint and a dense …

We present a new Python toolkit called RecWizard for Conversational Recommender
Systems (CRS). RecWizard offers support for development of models and interactive user …

Deep neural networks (DNNs) have achieved significant advancements in click-through rate
(CTR) prediction by demonstrating strong generalization on training data. However, in real …

Training large-scale deep learning recommendation models (DLRMs) with embedding
tables stretching across multiple GPUs in a cluster presents a unique challenge, demanding …

Embedding-based deep recommendation models (EDRMs), which contain small dense
models and large embedding tables, are widely used in industry. Embedding …

Recommendation systems are essential for filtering data and retrieving relevant information
across various applications. Recent advancements have seen these systems incorporate …