Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Arnold P. Boedihardjo"'
Publikováno v:
ACM Transactions on Knowledge Discovery from Data. 13:1-22
The presence of data noise and corruptions has recently invoked increasing attention on robust least-squares regression ( RLSR ), which addresses this fundamental problem that learns reliable regression coefficients when response variables can be arb
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::afe725487e973dd4da1c28aa533a2769
https://doi.org/10.1145/3314105
https://doi.org/10.1145/3314105
Publikováno v:
Knowledge and Information Systems. 61:363-396
A wide variety of publicly available heterogeneous data has provided us with an opportunity to meander through contextual snippets relevant to a particular event or persons of interest. One example of a heterogeneous source is online news articles wh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c5cf38c8f04d97e6b54539c0b423a5b7
https://doi.org/10.1007/s10115-018-1304-9
https://doi.org/10.1007/s10115-018-1304-9
Publikováno v:
GeoInformatica. 22:503-506
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c5b62445363cfbd5c2252f9fa4c4a562
https://doi.org/10.1007/s10707-018-0324-7
https://doi.org/10.1007/s10707-018-0324-7
Autor:
Tim Oates, Crystal Chen, Pavel Senin, Sunil Gandhi, Arnold P. Boedihardjo, Jessica Lin, Xing Wang, Susan Frankenstein
Publikováno v:
ACM Transactions on Knowledge Discovery from Data. 12:1-28
The problems of recurrent and anomalous pattern discovery in time series, e.g., motifs and discords, respectively, have received a lot of attention from researchers in the past decade. However, since the pattern search space is usually intractable, m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b821bfa1527dcc6b66c68f15d3292ec5
https://doi.org/10.1145/3051126
https://doi.org/10.1145/3051126
Publikováno v:
ACM Transactions on Intelligent Systems and Technology. 9:1-30
The scarcity of potable water is a critical challenge in many regions around the world. Previous studies have shown that knowledge of device-level water usage can lead to significant conservation. Although there is considerable interest in determinin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6558373dc59736d1fc9140dbb0b9bf63
https://doi.org/10.1145/3141770
https://doi.org/10.1145/3141770
Publikováno v:
International Journal of Data Science and Analytics. 8:241-256
There is an overwhelming number of news articles published every day around the globe. Following the evolution of a news-story is a difficult task given that there is no such mechanism available to track back in time to study the diffusion of the rel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7e2c8b20799f93fd88f5e285240d266a
https://doi.org/10.1007/s41060-017-0091-9
https://doi.org/10.1007/s41060-017-0091-9
Publikováno v:
ICDM
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 features are not accessible entirely at one time. Until now, several importan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::025db691d7cdd8025e4ae3312d9cc4f1
Autor:
Naren Ramakrishnan, Chang-Tien Lu, Feng Chen, Arnold P. Boedihardjo, Sumit Shah, Raimundo F. Dos Santos
Publikováno v:
GeoInformatica. 20:879-921
This paper proposes three methods of association analysis that address two challenges of Big Data: capturing relatedness among real-world events in high data volumes, and modeling similar events that are described disparately under high data variabil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::476e0e7316a0e4cb96d2376814be0a16
https://doi.org/10.1007/s10707-016-0247-0
https://doi.org/10.1007/s10707-016-0247-0
Publikováno v:
IEEE BigData
In the era of information overload, people are struggling to make sense of complex story events in massive social media data. Most existing approaches are designed to address event extraction in news reports, documents and abstracts, but such approac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ace603b069d0e507fae6207b4e14f18b
https://doi.org/10.1109/bigdata.2017.8258107
https://doi.org/10.1109/bigdata.2017.8258107
Publikováno v:
IEEE BigData
In today's era of information overload, people are struggling to detect the evolution of hot topics from massive news media and microblogs such as Twitter. Reports from mainstream news agencies and discussions from microblogs could complement each ot
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a13e8b4454d1b8742875e0df0c178214
https://doi.org/10.1109/bigdata.2017.8258093
https://doi.org/10.1109/bigdata.2017.8258093