Heri Ramampiaro
Bakgrunn og aktiviteter
Ramampiaro er professor ved Institutt for datateknologi og informatikk, Norges teknisk-naturvitenskapelige universitet (NTNU). Han er gruppeleder for forskningsgruppen for Data og kunstig intelligens, og nestleder for Instituttet for datateknologi og informatikk (IDI). Ramampiaro har vært sentral i etableringen av Telenor – NTNU AI-Lab (nå Norwegian Open AI-Lab), som han også var leder for. Hans hovedforskningsinteresser er innen tekstanalyse, informasjonsgjenfinning, og maskinlæring.
For mer informasjon om mine avktiviteter vennligst gå her.
Vitenskapelig, faglig og kunstnerisk arbeid
Et utvalg av nyere tidsskriftspublikasjoner, kunstneriske produksjoner, bok, inklusiv bokdeler og rapport-del. Se alle publikasjoner i databasen
Tidsskriftspublikasjoner
- (2020) Space-time series clustering: Algorithms, taxonomy, and case study on urban smart cities. Engineering Applications of Artificial Intelligence. vol. 95.
- (2020) EfficientPose: Scalable single-person pose estimation. Applied intelligence (Boston).
- (2020) Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles. Proceedings of Machine Learning Research (PMLR). vol. 124.
- (2019) Towards efficiently mining closed high utility itemsets from incremental databases. Knowledge-Based Systems. vol. 165.
- (2019) Deep Learning‐based infant motion tracking facilitating early detection of cerebral palsy. Developmental Medicine & Child Neurology. vol. 61 (S2).
- (2019) Locality-adapted kernel densities of term co-occurrences for location prediction of tweets. Information Processing & Management. vol. 56 (4).
- (2019) Forecasting Intra-Hour Imbalances in Electric Power Systems. PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE. vol. 33 (1).
- (2018) A deep network model for paraphrase detection in short text messages. Information Processing & Management. vol. 54.
- (2018) Applying temporal dependence to detect changes in streaming data. Applied intelligence (Boston). vol. 48 (12).
- (2018) High utility drift detection in quantitative data streams. Knowledge-Based Systems. vol. 157.
- (2018) Spatial Statistics of Term Co-occurrences for Location Prediction of Tweets. Lecture Notes in Computer Science (LNCS). vol. 10772.
- (2018) Effective hate-speech detection in Twitter data using recurrent neural networks. Applied intelligence (Boston). vol. 48 (12).
- (2018) Extracting news events from microblogs. Journal of Statistics & Management Systems. vol. 21 (4).
- (2017) Content-Based Social Recommendation with Poisson Matrix Factorization. Lecture Notes in Computer Science (LNCS). vol. 10534 LNAI.
- (2017) Efficient High Utility Itemset Mining using Buffered Utility-Lists. Applied intelligence (Boston). vol. 48 (7).
- (2015) Geo-Temporal Distribution of Tag Terms for Event-Related Image Retrieval. Information Processing & Management. vol. 51 (1).
- (2014) Learning to Rank for Personalized Fashion Recommender Systems via Implicit Feedback. Lecture Notes in Computer Science (LNCS). vol. 8891.
- (2014) A scalable algorithm for extraction and clustering of event-related pictures. Multimedia tools and applications. vol. 70 (1).
- (2013) Event-Related Image Retrieval: Exploring Geographical and Temporal Distribution of User Tags. International Journal of Multimedia Information Retrieval.
- (2013) Exploring Temporal Proximity and Spatial Distribution of Terms in Web-based Search of Event-Related Images. ACM Hypertext Proceedings.