Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Can Wang"'
Publikováno v:
International Journal of Machine Learning and Cybernetics. 12:1015-1030
The development of mobile Internet and sharing economy brings the prosperity of spatial crowdsourcing (SC). Pricing is a crucial step for SC platforms to solve the Profit-driven Task Assignment (PTA) problem to maximize their total profit. However, d
Publikováno v:
Frontiers of Information Technology & Electronic Engineering. 20:538-553
Feature selection has attracted a great deal of interest over the past decades. By selecting meaningful feature subsets, the performance of learning algorithms can be effectively improved. Because label information is expensive to obtain, unsupervise
Publikováno v:
Knowledge-Based Systems. 166:30-41
Existing works on influence maximization (IM) aim at finding influential online users as seed nodes. Originated from these seed nodes, large online influence spread can be triggered. However, such user-driven perspective limits the IM problem within
Publikováno v:
Complexity, Vol 2019 (2019)
Recommender systems have become indispensable for online services since they alleviate the information overload problem for users. Some work has been proposed to support the personalized recommendation by utilizing collaborative filtering to learn th
Publikováno v:
CIKM
The e-commerce era is witnessing a rapid development of various annual online promotions, such as Black Friday, Cyber Monday, and Alibaba's 11.11, etc. S ales P redictions for O nline P romotions (SPOP) are a set of sales related forecasts for the pr
Publikováno v:
World Wide Web. 22:517-531
Current multi-output regression method usually ignores the relationship among response variables, and thus it is challenging to obtain an effective coefficient matrix for predicting the response variables with the features. We address these problems
Publikováno v:
Knowledge-Based Systems. 213:106692
Influence maximization (IM) in social media aims at finding influential seed users to trigger large online cascading influence spread. Existing studies mainly focus on maximizing the number of the activated nodes, but the diversity of the activated n
Publikováno v:
Applied Intelligence. 46:521-533
Recommender systems have attracted lots of attention since they alleviate the information overload problem for users. Matrix factorization is one of the most widely employed collaborative filtering techniques in the research of recommender systems du
Publikováno v:
CAAI Transactions on Intelligence Technology. 1:210-224
Indoor multi-tracking is more challenging compared with outdoor tasks due to frequent occlusion, view-truncation, severe scale change and pose variation, which may bring considerable unreliability and ambiguity to target representation and data assoc
Publikováno v:
Neurocomputing. 171:1118-1130
Feature selection plays an important role in many machine learning applications. By extracting meaningful features and eliminating both redundancies and noises, it effectively improves the accuracy and efficiency of the learning algorithm. In this pa