activity
20112021
most citedMobile augmented reality survey: a bottom-up approach

68 citations · 234 across the 19 of their papers we have counts for

collaborators

19 papers

cs.IR2021★ 24 cited

Genetic Meta-Structure Search for Recommendation on Heterogeneous Information Network

Zhenyu Han, Fengli Xu, Jinghan Shi +4

In the past decade, the heterogeneous information network (HIN) has become an important methodology for modern recommender systems. To fully leverage its power, manually designed n…

cs.DC2021★ 2 cited

Towards Mobile Distributed Ledgers

Dimitris Chatzopoulos, Anurag Jain, Sujit Gujar +2

Advances in mobile computing have paved the way for new types of distributed applications that can be executed solely by mobile devices on device-to-device (D2D) ecosystems (e.g.,…

cs.CY2020★ 8 cited

Trustworthy AI in the Age of Pervasive Computing and Big Data

Abhishek Kumar, Tristan Braud, Sasu Tarkoma +1

The era of pervasive computing has resulted in countless devices that continuously monitor users and their environment, generating an abundance of user behavioural data. Such data…

cs.HC2019★ 3 cited

Emerging Natural User Interfaces in Mobile Computing: A Bottoms-Up Survey

Kirill A. Shatilov, Dimitris Chatzopoulos, Lik-Hang Lee +1

Mobile and wearable interfaces and interaction paradigms are highly constrained by the available screen real estate, and the computational and power resources. Although there exist…

cs.NI2019★ 21 cited

Energy-Efficient Power Control of Train-ground mmWave Communication for High Speed Trains

Lei Wang, Bo Ai, Yong Niu +2

High speed train system has proven to be a very flexible and attractive system that can be developed under various circumstances and in different contexts and cultures. As a result…

cs.GT2019★ 1 cited

FaRM: Fair Reward Mechanism for Information Aggregation in Spontaneous Localized Settings (Extended Version)

Moin Hussain Moti, Dimitris Chatzopoulos, Pan Hui +1

Although peer prediction markets are widely used in crowdsourcing to aggregate information from agents, they often fail to reward the participating agents equitably. Honest agents…