122 citations · 191 across the 8 of their papers we have counts for
14 papers
A Self-Attention Network based Node Embedding Model
Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung
Despite several signs of progress have been made recently, limited research has been conducted for an inductive setting where embeddings are required for newly unseen nodes -- a se…
A Capsule Network-based Model for Learning Node Embeddings
Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen +1
In this paper, we focus on learning low-dimensional embeddings for nodes in graph-structured data. To achieve this, we propose Caps2NE -- a new unsupervised embedding model leverag…
A Relational Memory-based Embedding Model for Triple Classification and Search Personalization
Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung
Knowledge graph embedding methods often suffer from a limitation of memorizing valid triples to predict new ones for triple classification and search personalization problems. To t…
A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization
Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen +2
In this paper, we introduce an embedding model, named CapsE, exploring a capsule network to model relationship triples (subject, relation, object). Our CapsE represents each triple…
Detection of Unknown Anomalies in Streaming Videos with Generative Energy-based Boltzmann Models
Hung Vu, Tu Dinh Nguyen, Dinh Phung
Abnormal event detection is one of the important objectives in research and practical applications of video surveillance. However, there are still three challenging problems for mo…
A Capsule Network-based Embedding Model for Search Personalization
Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen +1
Search personalization aims to tailor search results to each specific user based on the user's personal interests and preferences (i.e., the user profile). Recent research approach…