45 citations · 208 across the 17 of their papers we have counts for
17 papers
Multi-domain Recommendation with Embedding Disentangling and Domain Alignment
Wentao Ning, Xiao Yan, Weiwen Liu +3
Multi-domain recommendation (MDR) aims to provide recommendations for different domains (e.g., types of products) with overlapping users/items and is common for platforms such as A…
DGI: Easy and Efficient Inference for GNNs
Peiqi Yin, Xiao Yan, Jinjing Zhou +5
While many systems have been developed to train Graph Neural Networks (GNNs), efficient model inference and evaluation remain to be addressed. For instance, using the widely adopte…
Manu: A Cloud Native Vector Database Management System
Rentong Guo, Xiaofan Luan, Long Xiang +12
With the development of learning-based embedding models, embedding vectors are widely used for analyzing and searching unstructured data. As vector collections exceed billion-scale…
Effective and Efficient PageRank-based Positioning for Graph Visualization
Shiqi Zhang, Renchi Yang, Xiaokui Xiao +2
Graph visualization is a vital component in many real-world applications (e.g., social network analysis, web mining, and bioinformatics) that enables users to unearth crucial insig…
Automatic Meta-Path Discovery for Effective Graph-Based Recommendation
Wentao Ning, Reynold Cheng, Jiajun Shen +7
Heterogeneous Information Networks (HINs) are labeled graphs that depict relationships among different types of entities (e.g., users, movies and directors). For HINs, meta-path-ba…
Combating Ambiguity for Hash-code Learning in Medical Instance Retrieval
Jiansheng Fang, Huazhu Fu, Dan Zeng +3
When encountering a dubious diagnostic case, medical instance retrieval can help radiologists make evidence-based diagnoses by finding images containing instances similar to a quer…
The item selection problem for user cold-start recommendation
Yitong Meng, Jie Liu, Xiao Yan +1
When a new user just signs up on a website, we usually have no information about him/her, i.e. no interaction with items, no user profile and no social links with other users. Unde…
Hierarchical Graph Matching Network for Graph Similarity Computation
Haibo Xiu, Xiao Yan, Xiaoqiang Wang +2
Graph edit distance / similarity is widely used in many tasks, such as graph similarity search, binary function analysis, and graph clustering. However, computing the exact graph e…
TensorOpt: Exploring the Tradeoffs in Distributed DNN Training with Auto-Parallelism
Zhenkun Cai, Kaihao Ma, Xiao Yan +5
A good parallelization strategy can significantly improve the efficiency or reduce the cost for the distributed training of deep neural networks (DNNs). Recently, several methods h…
Self-Enhanced GNN: Improving Graph Neural Networks Using Model Outputs
Han Yang, Xiao Yan, Xinyan Dai +2
Graph neural networks (GNNs) have received much attention recently because of their excellent performance on graph-based tasks. However, existing research on GNNs focuses on design…
Convolutional Embedding for Edit Distance
Xinyan Dai, Xiao Yan, Kaiwen Zhou +3
Edit-distance-based string similarity search has many applications such as spell correction, data de-duplication, and sequence alignment. However, computing edit distance is known…
Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning
Xinyan Dai, Xiao Yan, Kaiwen Zhou +4
The high cost of communicating gradients is a major bottleneck for federated learning, as the bandwidth of the participating user devices is limited. Existing gradient compression…
Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search
Xinyan Dai, Xiao Yan, Kelvin K. W. Ng +2
Vector quantization (VQ) techniques are widely used in similarity search for data compression, fast metric computation and etc. Originally designed for Euclidean distance, existing…
Understanding and Improving Proximity Graph based Maximum Inner Product Search
Jie Liu, Xiao Yan, Xinyan Dai +3
The inner-product navigable small world graph (ip-NSW) represents the state-of-the-art method for approximate maximum inner product search (MIPS) and it can achieve an order of mag…
Pyramid: A General Framework for Distributed Similarity Search
Shiyuan Deng, Xiao Yan, Kelvin K. W. Ng +2
Similarity search is a core component in various applications such as image matching, product recommendation and low-shot classification. However, single machine solutions are usua…
Norm-Range Partition: A Universal Catalyst for LSH based Maximum Inner Product Search (MIPS)
Xiao Yan, Xinyan Dai, Jie Liu +2
Recently, locality sensitive hashing (LSH) was shown to be effective for MIPS and several algorithms including -ALSH, Sign-ALSH and Simple-LSH have been proposed. In this pape…
Norm-Ranging LSH for Maximum Inner Product Search
Xiao Yan, Jinfeng Li, Xinyan Dai +2
Neyshabur and Srebro proposed Simple-LSH, which is the state-of-the-art hashing method for maximum inner product search (MIPS) with performance guarantee. We found that the perform…