18 citations · 76 across the 20 of their papers we have counts for
5 papers · 1 filter
Prompt-Tuning Decision Transformer with Preference Ranking
Shengchao Hu, Li Shen, Ya Zhang +1
Prompt-tuning has emerged as a promising method for adapting pre-trained models to downstream tasks or aligning with human preferences. Prompt learning is widely used in NLP but ha…
Long-Tailed Partial Label Learning via Dynamic Rebalancing
Feng Hong, Jiangchao Yao, Zhihan Zhou +2
Real-world data usually couples the label ambiguity and heavy imbalance, challenging the algorithmic robustness of partial label learning (PLL) and long-tailed learning (LT). The s…
Variational Collaborative Learning for User Probabilistic Representation
Kenan Cui, Xu Chen, Jiangchao Yao +1
Collaborative filtering (CF) has been successfully employed by many modern recommender systems. Conventional CF-based methods use the user-item interaction data as the sole informa…
Masking: A New Perspective of Noisy Supervision
Bo Han, Jiangchao Yao, Gang Niu +4
It is important to learn various types of classifiers given training data with noisy labels. Noisy labels, in the most popular noise model hitherto, are corrupted from ground-truth…
Variational Composite Autoencoders
Jiangchao Yao, Ivor Tsang, Ya Zhang
Learning in the latent variable model is challenging in the presence of the complex data structure or the intractable latent variable. Previous variational autoencoders can be low…