122 citations · 436 across the 20 of their papers we have counts for
10 papers · 1 filter
Efficient Global String Kernel with Random Features: Beyond Counting Substructures
Lingfei Wu, Ian En-Hsu Yen, Siyu Huo +5
Analysis of large-scale sequential data has been one of the most crucial tasks in areas such as bioinformatics, text, and audio mining. Existing string kernels, however, either (i)…
Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding
Lingfei Wu, Ian En-Hsu Yen, Zhen Zhang +5
Graph kernels are widely used for measuring the similarity between graphs. Many existing graph kernels, which focus on local patterns within graphs rather than their global propert…
TITAN: A Spatiotemporal Feature Learning Framework for Traffic Incident Duration Prediction
Kaiqun Fu, Taoran Ji, Liang Zhao +1
Critical incident stages identification and reasonable prediction of traffic incident duration are essential in traffic incident management. In this paper, we propose a traffic inc…
Multi-stage Deep Classifier Cascades for Open World Recognition
Xiaojie Guo, Amir Alipour-Fanid, Lingfei Wu +4
At present, object recognition studies are mostly conducted in a closed lab setting with classes in test phase typically in training phase. However, real-world problem is far more…
DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums
Yuyang Gao, Lingfei Wu, Houman Homayoun +1
Online health communities such as the online breast cancer forum enable patients (i.e., users) to interact and help each other within various subforums, which are subsections of th…
CBOWRA: A Representation Learning Approach for Medication Anomaly Detection
Liang Zhao, Zhiyuan Ma, Yangming Zhou +3
Electronic health record is an important source for clinical researches and applications, and errors inevitably occur in the data, which could lead to severe damages to both patien…
ADMM for Efficient Deep Learning with Global Convergence
Junxiang Wang, Fuxun Yu, Xiang Chen +1
Alternating Direction Method of Multipliers (ADMM) has been used successfully in many conventional machine learning applications and is considered to be a useful alternative to Sto…
Machine Learning-Based Delay-Aware UAV Detection and Operation Mode Identification over Encrypted Wi-Fi Traffic
Amir Alipour-Fanid, Monireh Dabaghchian, Ning Wang +3
The consumer UAV (unmanned aerial vehicle) market has grown significantly over the past few years. Despite its huge potential in spurring economic growth by supporting various appl…
Robust Regression via Online Feature Selection under Adversarial Data Corruption
Xuchao Zhang, Shuo Lei, Liang Zhao +2
The presence of data corruption in user-generated streaming data, such as social media, motivates a new fundamental problem that learns reliable regression coefficient when feature…
Estimating the Circuit Deobfuscating Runtime based on Graph Deep Learning
Zhiqian Chen, Gaurav Kolhe, Setareh Rafatirad +4
Circuit obfuscation is a recently proposed defense mechanism to protect digital integrated circuits (ICs) from reverse engineering by using camouflaged gates i.e., logic gates whos…