The objective of topic inference in research proposals aims to obtain th...
Feature transformation aims to reconstruct an effective representation s...
The task of root cause analysis (RCA) is to identify the root causes of
...
Temporal knowledge graph (TKG) reasoning aims to predict the future miss...
The two fields of urban planning and artificial intelligence (AI) arose ...
Our work focuses on anomaly detection in cyber-physical systems. Prior
l...
Spatiotemporal data mining plays an important role in air quality monito...
In this paper, we propose REASON, a novel framework that enables the
aut...
Feature transformation for AI is an essential task to boost the effectiv...
Urban traffic speed prediction aims to estimate the future traffic speed...
Recently, many deep learning based beamformers have been proposed for
mu...
Graph generative models have broad applications in biology, chemistry an...
The essential task of urban planning is to generate the optimal land-use...
Funding agencies are largely relied on a topic matching between domain
e...
Traditional urban planning demands urban experts to spend considerable t...
The peer merit review of research proposals has been the major mechanism...
Feature transformation aims to extract a good representation (feature) s...
Recent neural network based Direction of Arrival (DoA) estimation algori...
Traffic demand forecasting by deep neural networks has attracted widespr...
Recent studies have shown great promise in applying graph neural network...
Sound source localization aims to seek the direction of arrival (DOA) of...
Representation (feature) space is an environment where data points are
v...
In many scenarios, 1) data streams are generated in real time; 2) labele...
Feature selection and instance selection are two important techniques of...
Mobile user profiling refers to the efforts of extracting users'
charact...
In this paper, we focus on the problem of modeling dynamic geo-human
int...
Urban planning refers to the efforts of designing land-use configuration...
Urban planning designs land-use configurations and can benefit building
...
With the growth of the academic engines, the mining and analysis acquisi...
In this paper, we propose a single-agent Monte Carlo based reinforced fe...
Automated characterization of spatial data is a kind of critical geograp...
To advance the development of science and technology, research proposals...
In this paper, we study the problem of mobile user profiling, which is a...
Graph Convolutional Network (GCN) has been widely applied in transportat...
We study the problem of balancing effectiveness and efficiency in automa...
Feature selection aims to select a subset of features to optimize the
pe...
Class-Incremental Learning (CIL) aims to train a reliable model with the...
In this paper, we study the problem of balancing effectiveness and effic...
While Water Treatment Networks (WTNs) are critical infrastructures for l...
While Graph Neural Network (GNN) has shown superiority in learning node
...
Urban planning refers to the efforts of designing land-use configuration...
Public transportation plays a critical role in people's daily life. It h...
In many recommender systems, users and items are associated with attribu...
Precise user and item embedding learning is the key to building a succes...
Collaborative Filtering (CF) is one of the most successful approaches fo...
In recent years, due to the booming development of online social network...
In recent years, many research works propose to embed the network struct...
In recent years, many research works propose to embed the networked data...
Network embedding aims at projecting the network data into a low-dimensi...
Outlier detection is the identification of points in a dataset that do n...