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Helge Langseth
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Publications
- 2024
- [j31]Bjørnar Vassøy, Helge Langseth:
Consumer-side fairness in recommender systems: a systematic survey of methods and evaluation. Artif. Intell. Rev. 57(4): 101 (2024) - [i18]Håkon Hanisch Kjærnli, Lluis Mas-Ribas, Aida Ashrafi, Gleb Sizov, Helge Langseth, Odd Erik Gundersen:
Probing the Robustness of Time-series Forecasting Models with CounterfacTS. CoRR abs/2403.03508 (2024) - 2023
- [j30]Sofia Aftab, Heri Ramampiaro, Helge Langseth, Massimiliano Ruocco:
Deep Contextual Grid Triplet Network for Context-Aware Recommendation. IEEE Access 11: 97522-97537 (2023) - [c38]Odd Erik Gundersen, Saeid Shamsaliei, Håkon Sletten Kjærnli, Helge Langseth:
On Reporting Robust and Trustworthy Conclusions from Model Comparison Studies Involving Neural Networks and Randomness. ACM-REP 2023: 37-61 - [c37]David Baumgartner, Helge Langseth, Heri Ramampiaro, Kenth Engø-Monsen:
mTADS: Multivariate Time Series Anomaly Detection Benchmark Suites. IEEE Big Data 2023: 588-597 - [c35]Bjørnar Vassøy, Helge Langseth, Benjamin Kille:
Providing Previously Unseen Users Fair Recommendations Using Variational Autoencoders. RecSys 2023: 871-876 - [i17]Bjørnar Vassøy, Helge Langseth:
Consumer-side Fairness in Recommender Systems: A Systematic Survey of Methods and Evaluation. CoRR abs/2305.09330 (2023) - [i16]Bjørnar Vassøy, Helge Langseth, Benjamin Kille:
Providing Previously Unseen Users Fair Recommendations Using Variational Autoencoders. CoRR abs/2308.15230 (2023) - 2022
- [c34]Shweta Tiwari, Gavin Bell, Helge Langseth, Heri Ramampiaro:
Detection of Potential Manipulations in Electricity Market using Machine Learning Approaches. ICAART (3) 2022: 975-983 - 2021
- [j28]Shweta Tiwari, Heri Ramampiaro, Helge Langseth:
Machine Learning in Financial Market Surveillance: A Survey. IEEE Access 9: 159734-159754 (2021) - 2020
- [j25]Bjørn Magnus Mathisen, Agnar Aamodt, Kerstin Bach, Helge Langseth:
Learning similarity measures from data. Prog. Artif. Intell. 9(2): 129-143 (2020) - [c32]Tárik S. Salem, Helge Langseth, Heri Ramampiaro:
Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles. UAI 2020: 1179-1187 - [i12]Bjørn Magnus Mathisen, Agnar Aamodt, Kerstin Bach, Helge Langseth:
Learning similarity measures from data. CoRR abs/2001.05312 (2020) - [i11]Tárik S. Salem, Helge Langseth, Heri Ramampiaro:
Prediction Intervals: Split Normal Mixture from Quality-Driven Deep Ensembles. CoRR abs/2007.09670 (2020) - 2019
- [c31]Tárik S. Salem, Karan Kathuria, Heri Ramampiaro, Helge Langseth:
Forecasting Intra-Hour Imbalances in Electric Power Systems. AAAI 2019: 9595-9600 - [p1]Heri Ramampiaro, Helge Langseth, Thomas Almenningen, Herman Schistad, Martin Havig, Hai Thanh Nguyen:
New Ideas in Ranking for Personalized Fashion Recommender Systems. Business and Consumer Analytics: New Ideas 2019: 933-961 - [i10]Georgios K. Pitsilis, Heri Ramampiaro, Helge Langseth:
Securing Tag-based recommender systems against profile injection attacks: A comparative study. (Extended Report). CoRR abs/1901.08422 (2019) - [i9]Tárik S. Salem, Karan Kathuria, Heri Ramampiaro, Helge Langseth:
Forecasting Intra-Hour Imbalances in Electric Power Systems. CoRR abs/1902.00563 (2019) - 2018
- [j23]Georgios K. Pitsilis, Heri Ramampiaro, Helge Langseth:
Effective hate-speech detection in Twitter data using recurrent neural networks. Appl. Intell. 48(12): 4730-4742 (2018) - [j21]Basant Agarwal, Heri Ramampiaro, Helge Langseth, Massimiliano Ruocco:
A deep network model for paraphrase detection in short text messages. Inf. Process. Manag. 54(6): 922-937 (2018) - [c30]Ming Zeng, Haoxiang Gao, Tong Yu, Ole J. Mengshoel, Helge Langseth, Ian R. Lane, Xiaobing Liu:
Understanding and improving recurrent networks for human activity recognition by continuous attention. UbiComp 2018: 56-63 - [i7]Georgios K. Pitsilis, Heri Ramampiaro, Helge Langseth:
Detecting Offensive Language in Tweets Using Deep Learning. CoRR abs/1801.04433 (2018) - [i6]Georgios Pitsilis, Heri Ramampiaro, Helge Langseth:
Securing Tag-based recommender systems against profile injection attacks: A comparative study. CoRR abs/1808.10550 (2018) - [i5]Ming Zeng, Haoxiang Gao, Tong Yu, Ole J. Mengshoel, Helge Langseth, Ian R. Lane, Xiaobing Liu:
Understanding and Improving Recurrent Networks for Human Activity Recognition by Continuous Attention. CoRR abs/1810.04038 (2018) - 2017
- [c29]Bjørn Magnus Mathisen, Agnar Aamodt, Helge Langseth:
Data Driven Case Base Construction for Prediction of Success of Marine Operations. ICCBR (Workshops) 2017: 104-113 - [c27]Eliezer de Souza da Silva, Helge Langseth, Heri Ramampiaro:
Content-Based Social Recommendation with Poisson Matrix Factorization. ECML/PKDD (1) 2017: 530-546 - [c26]Massimiliano Ruocco, Ole Steinar Lillestøl Skrede, Helge Langseth:
Inter-Session Modeling for Session-Based Recommendation. DLRS@RecSys 2017: 24-31 - [i3]Massimiliano Ruocco, Ole Steinar Lillestøl Skrede, Helge Langseth:
Inter-Session Modeling for Session-Based Recommendation. CoRR abs/1706.07506 (2017) - [i1]Basant Agarwal, Heri Ramampiaro, Helge Langseth, Massimiliano Ruocco:
A Deep Network Model for Paraphrase Detection in Short Text Messages. CoRR abs/1712.02820 (2017) - 2015
- [j15]Boye Annfelt Høverstad, Axel Tidemann, Helge Langseth, Pinar Öztürk:
Short-Term Load Forecasting With Seasonal Decomposition Using Evolution for Parameter Tuning. IEEE Trans. Smart Grid 6(4): 1904-1913 (2015) - [c16]Øyvind H. Myklatun, Thorstein K. Thorrud, Hai Thanh Nguyen, Helge Langseth, Anders Kofod-Petersen:
Probability-based Approach for Predicting E-commerce Consumer Behaviour Using Sparse Session Data. RecSys Challenge 2015: 5:1-5:4 - 2014
- [c14]Hai Thanh Nguyen, Thomas Almenningen, Martin Havig, Herman Schistad, Anders Kofod-Petersen, Helge Langseth, Heri Ramampiaro:
Learning to Rank for Personalised Fashion Recommender Systems via Implicit Feedback. MIKE 2014: 51-61 - 2013
- [c11]Boye Annfelt Høverstad, Axel Tidemann, Helge Langseth:
Effects of data cleansing on load prediction algorithms. CIASG 2013: 93-100 - 2011
- [c8]Tore Bruland, Agnar Aamodt, Helge Langseth:
A hybrid CBR and BN architecture refined through data analysis. ISDA 2011: 906-913 - [c7]Tor Gunnar Houeland, Tore Bruland, Agnar Aamodt, Helge Langseth:
Extended Abstract: Combining CBR and BN using metareasoning. SCAI 2011: 189-190 - [c6]Terje N. Lillegraven, Arnt C. Wolden, Anders Kofod-Petersen, Helge Langseth:
Extended Abstract: A design for a tourist CF system. SCAI 2011: 193-194 - [e1]Anders Kofod-Petersen, Fredrik Heintz, Helge Langseth:
Eleventh Scandinavian Conference on Artificial Intelligence, SCAI 2011, Trondheim, Norway, May 24th - 26th, 2011. Frontiers in Artificial Intelligence and Applications 227, IOS Press 2011, ISBN 978-1-60750-753-6 [contents] - 2010
- [c4]Tore Bruland, Agnar Aamodt, Helge Langseth:
Architectures Integrating Case-Based Reasoning and Bayesian Networks for Clinical Decision Support. Intelligent Information Processing 2010: 82-91
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last updated on 2024-09-13 01:39 CEST by the dblp team
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