The recent rise of social media has led to the spread of large amounts o...
Training good representations for items is critical in recommender model...
Large Language Models (LLMs) have demonstrated exceptional capabilities ...
Many approaches to Natural Language Processing (NLP) tasks often treat t...
Weight pruning is among the most popular approaches for compressing deep...
While pre-trained large-scale deep models have garnered attention as an
...
Automated plant diagnosis is a technology that promises large increases ...
As neural networks are increasingly being applied to real-world applicat...
Zero-shot learning (ZSL) has been shown to be a promising approach to
ge...
A key to causal inference with observational data is achieving balance i...
In domains where data are sensitive or private, there is great value in
...
Naively trained neural networks tend to experience catastrophic forgetti...
Conventional survival analysis approaches estimate risk scores or
indivi...
Stochastic blockmodels (SBM) and their variants, e.g., mixed-membership ...
Over the last few years, there has been growing interest in learning mod...