15 citations · 19 across the 4 of their papers we have counts for
8 papers
Unintended Bias in Language Model-driven Conversational Recommendation
Tianshu Shen, Jiaru Li, Mohamed Reda Bouadjenek +2
Conversational Recommendation Systems (CRSs) have recently started to leverage pretrained language models (LM) such as BERT for their ability to semantically interpret a wide range…
Supervised Contrastive Replay: Revisiting the Nearest Class Mean Classifier in Online Class-Incremental Continual Learning
Zheda Mai, Ruiwen Li, Hyunwoo Kim +1
Online class-incremental continual learning (CL) studies the problem of learning new classes continually from an online non-stationary data stream, intending to adapt to new data w…
Online Continual Learning in Image Classification: An Empirical Survey
Zheda Mai, Ruiwen Li, Jihwan Jeong +3
Online continual learning for image classification studies the problem of learning to classify images from an online stream of data and tasks, where tasks may include new classes (…
Attentive Autoencoders for Multifaceted Preference Learning in One-class Collaborative Filtering
Zheda Mai, Ga Wu, Kai Luo +1
Most existing One-Class Collaborative Filtering (OC-CF) algorithms estimate a user's preference as a latent vector by encoding their historical interactions. However, users often s…
CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions
Vincenzo Lomonaco, Lorenzo Pellegrini, Pau Rodriguez +12
In the last few years, we have witnessed a renewed and fast-growing interest in continual learning with deep neural networks with the shared objective of making current AI systems…
Online Class-Incremental Continual Learning with Adversarial Shapley Value
Dongsub Shim, Zheda Mai, Jihwan Jeong +3
As image-based deep learning becomes pervasive on every device, from cell phones to smart watches, there is a growing need to develop methods that continually learn from data while…