733 citations · 3.1k across the 122 of their papers we have counts for
10 papers · 1 filter
Locally Smoothed Neural Networks
Liang Pang, Yanyan Lan, Jun Xu +2
Convolutional Neural Networks (CNN) and the locally connected layer are limited in capturing the importance and relations of different local receptive fields, which are often cruci…
EagleMine: Vision-Guided Mining in Large Graphs
Wenjie Feng, Shenghua Liu, Christos Faloutsos +3
Given a graph with millions of nodes, what patterns exist in the distributions of node characteristics, and how can we detect them and separate anomalous nodes in a way similar to…
Learning Visual Features from Snapshots for Web Search
Yixing Fan, Jiafeng Guo, Yanyan Lan +3
When applying learning to rank algorithms to Web search, a large number of features are usually designed to capture the relevance signals. Most of these features are computed based…
Path-Based Attention Neural Model for Fine-Grained Entity Typing
Denghui Zhang, Pengshan Cai, Yantao Jia +3
Fine-grained entity typing aims to assign entity mentions in the free text with types arranged in a hierarchical structure. Traditional distant supervision based methods employ a s…
DeepRank: A New Deep Architecture for Relevance Ranking in Information Retrieval
Liang Pang, Yanyan Lan, Jiafeng Guo +3
This paper concerns a deep learning approach to relevance ranking in information retrieval (IR). Existing deep IR models such as DSSM and CDSSM directly apply neural networks to ge…
A Deep Investigation of Deep IR Models
Liang Pang, Yanyan Lan, Jiafeng Guo +2
The effective of information retrieval (IR) systems have become more important than ever. Deep IR models have gained increasing attention for its ability to automatically learning…