276 citations · 664 across the 33 of their papers we have counts for
8 papers · 1 filter
Learning Transferrable Parameters for Long-tailed Sequential User Behavior Modeling
Jianwen Yin, Chenghao Liu, Weiqing Wang +2
Sequential user behavior modeling plays a crucial role in online user-oriented services, such as product purchasing, news feed consumption, and online advertising. The performance…
Bilevel Continual Learning
Quang Pham, Doyen Sahoo, Chenghao Liu +1
Continual learning aims to learn continuously from a stream of tasks and data in an online-learning fashion, being capable of exploiting what was learned previously to improve curr…
Adaptive Task Sampling for Meta-Learning
Chenghao Liu, Zhihao Wang, Doyen Sahoo +3
Meta-learning methods have been extensively studied and applied in computer vision, especially for few-shot classification tasks. The key idea of meta-learning for few-shot classif…
Graph Prototypical Networks for Few-shot Learning on Attributed Networks
Kaize Ding, Jianling Wang, Jundong Li +3
Attributed networks nowadays are ubiquitous in a myriad of high-impact applications, such as social network analysis, financial fraud detection, and drug discovery. As a central an…
MCEN: Bridging Cross-Modal Gap between Cooking Recipes and Dish Images with Latent Variable Model
Han Fu, Rui Wu, Chenghao Liu +1
Nowadays, driven by the increasing concern on diet and health, food computing has attracted enormous attention from both industry and research community. One of the most popular re…
UniConv: A Unified Conversational Neural Architecture for Multi-domain Task-oriented Dialogues
Hung Le, Doyen Sahoo, Chenghao Liu +2
Building an end-to-end conversational agent for multi-domain task-oriented dialogues has been an open challenge for two main reasons. First, tracking dialogue states of multiple do…
A^2-GCN: An Attribute-aware Attentive GCN Model for Recommendation
Fan Liu, Zhiyong Cheng, Lei Zhu +2
As important side information, attributes have been widely exploited in the existing recommender system for better performance. In the real-world scenarios, it is common that some…
Cross-Modal Food Retrieval: Learning a Joint Embedding of Food Images and Recipes with Semantic Consistency and Attention Mechanism
Hao Wang, Doyen Sahoo, Chenghao Liu +4
Food retrieval is an important task to perform analysis of food-related information, where we are interested in retrieving relevant information about the queried food item such as…