• The Concept of Workload Delay as a Quality-of-Service Metric for Consolidated Cloud Environments with Deadline Requirements 

      Tasoulas, Evangelos; Hammer, Hugo Lewi; Haugerud, Hårek; Yazidi, Anis; Bratterud, Alfred; Feng, Boning (Chapter; Peer reviewed, 2017)
      Virtual Machine (VM) consolidation in the cloud has received significant research interest. A large body of approaches for VM consolidation in data centers resort to variants of the bin packing problem which tries to ...
    • Crawling JavaScript websites using WebKit - with application to analysis of hate speech in online discussions 

      Hammer, Hugo Lewi; Bratterud, Alfred; Fagernes, Siri (NIK: Norsk Informatikkonferanse;2013, Journal article; Peer reviewed, 2013-11)
      JavaScript Client-side hidden web pages (CSHW) contain dynamic material created as a result of specific user activities. The number of CSHW websites is increasing. Crawling the so-called Hidden Web is challenging, particularly ...
    • A dataset for predicting cloud cover over Europe 

      Svennevik, Hanna; Hicks, Steven; Riegler, Michael; Storelvmo, Trude; Hammer, Hugo Lewi (Peer reviewed; Journal article, 2024)
      Clouds are important factors when projecting future climate. Unfortunately, future cloud fractional cover (the portion of the sky covered by clouds) is associated with significant uncertainty, making climate projections ...
    • A Deep Diagnostic Framework Using Explainable Artificial Intelligence and Clustering 

      Thunold, Håvard Horgen; Riegler, Michael; Yazidi, Anis; Hammer, Hugo Lewi (Peer reviewed; Journal article, 2023)
      An important part of diagnostics is to gain insight into properties that characterize a disease. Machine learning has been used for this purpose, for instance, to identify biomarkers in genomics. However, when patient ...
    • Deep Tower Networks for Efficient Temperature Forecasting from Multiple Data Sources 

      Eide, Siri Sofie; Riegler, Michael; Hammer, Hugo Lewi; Bremnes, John Bjørnar (Sensors;Volume 22 / Issue 7, Peer reviewed; Journal article, 2022-04-06)
      Many data related problems involve handling multiple data streams of different types at the same time. These problems are both complex and challenging, and researchers often end up using only one modality or combining them ...
    • Detecting Threats of Violence in Online Discussions Using Bigrams of Important Words 

      Hammer, Hugo Lewi (IEEE Joint;, Chapter; Peer reviewed, 2014)
      Making violent threats towards minorities like immigrants or homosexuals is increasingly common on the Internet. We present a method to automatically detect threats of violence using machine learning. A material of ...
    • Déjà vu - Predicting the number of players in online games through normalization of historical data 

      Tyvand, Jon-Erik; Begnum, Kyrre; Hammer, Hugo Lewi (Chapter; Peer reviewed, 2011)
      A key factor to delivering a good online gaming experience is to have sufficient server resources relative to the number of players online. In this work, we present a simple profiling technique which allows effective ...
    • Diagnosing Schizophrenia from Activity Records using Hidden Markov Model Parameters 

      Boeker, Matthias; Riegler, Michael; Hammer, Hugo Lewi; Halvorsen, Pål; Fasmer, Ole Bernt; Jakobsen, Petter (Annual IEEE Symposium on Computer-Based Medical Systems;2021 IEEE 34th International Symposium on Computer-Based Medical Systems, Conference object, 2021-07-12)
      The diagnosis of Schizophrenia is mainly based on qualitative characteristics. With the usage of portable devices which measure activity of humans, the diagnosis of Schizophrenia can be enriched through quantitative features. ...
    • Does Clicker Use Improve Exam Scores? A Controlled Randomized Experiment in a Bachelor-Level Course in Software Engineering 

      Kvadsheim, Reidar; Haugerud, Hårek; Hammer, Hugo Lewi; Bratterud, Alfred; Habib, Laurence (Journal article, 2015)
      This paper reports a study of clicker use within an undergraduate course in Operating Systems. It is based on a controlled, randomized experiment with a crossover design that measures learning outcomes by means of test ...
    • Dyadic Aggregated Autoregressive Model (DASAR) for Automatic Modulation Classification 

      Pinto-Orellana, Marco Antonio; Hammer, Hugo Lewi (IEEE Access;Volume 8, Journal article; Peer reviewed, 2020-08-27)
      In this article, we presented a novel spectral estimation method, the dyadic aggregated autoregressive model (DASAR), that characterizes the spectrum dynamics of a modulated signal. DASAR enhances automatic modulation ...
    • Efficient Estimation of Generative Models Using Tukey Depth 

      Vo, Minh-Quan; Nguyen, Thu; Riegler, Michael; Hammer, Hugo Lewi (Peer reviewed; Journal article, 2024)
      Generative models have recently received a lot of attention. However, a challenge with such models is that it is usually not possible to compute the likelihood function, which makes parameter estimation or training of ...
    • Efficient quantile tracking using an oracle 

      Hammer, Hugo Lewi; Yazidi, Anis; Riegler, Michael; Rue, Håvard (Applied intelligence (Boston);, Peer reviewed; Journal article, 2022-04-14)
      Concept drift is a well-known issue that arises when working with data streams. In this paper, we present a procedure that allows a quantile tracking procedure to cope with concept drift. We suggest using expected quantile ...
    • Efficient Tracking of Statistical Properties of Data Streams with Rapid Changes 

      Hammer, Hugo Lewi; Yazidi, Anis (The 26th Mediterranean Conference on Control and Automation;, Chapter; Chapter; Peer reviewed, 2018-08-23)
      Many real-life dynamical systems change rapidly followed by almost stationary periods. In this paper, we consider streams of data with such rapidly changing behavior and investigate the problem of tracking their statistical ...
    • Enhanced Equivalence Projective Simulation: A Framework for Modeling Formation of Stimulus Equivalence Classes 

      Abolpour Mofrad, Asieh; Yazidi, Anis; Abolpour Mofrad, Samaneh; Hammer, Hugo Lewi; Arntzen, Erik (Neural Computation;Vol. 33, No. 2, Journal article; Peer reviewed, 2021-02-01)
      Formation of stimulus equivalence classes has been recently modeled through equivalence projective simulation (EPS), a modified version of a projective simulation (PS) learning agent. PS is endowed with an episodic memory ...
    • Equivalence Projective Simulation as a Framework for Modeling Formation of Stimulus Equivalence Classes 

      Abolpour Mofrad, Asieh; Yazidi, Anis; Hammer, Hugo Lewi; Arntzen, Erik (Neural Computation;Volume 32, No. 5, Journal article; Peer reviewed, 2020-04-14)
      Stimulus equivalence (SE) and projective simulation (PS) study complex behavior, the former in human subjects and the latter in artificial agents. We apply the PS learning framework for modeling the formation of equivalence ...
    • Estimating tukey depth using incremental quantile estimators 

      Hammer, Hugo Lewi; Yazidi, Anis; Rue, Håvard (Pattern Recognition;Volume 122, February 2022, 108339, Peer reviewed; Journal article, 2022)
      Measures of distance or how data points are positioned relative to each other are fundamental in pattern recognition. The concept of depth measures how deep an arbitrary point is positioned in a dataset, and is an interesting ...
    • EvoDynamic: A Framework for the Evolution of Generally Represented Dynamical Systems and Its Application to Criticality 

      Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (Lecture Notes in Computer Science;Volume 12104, Conference object, 2020-04-09)
      Dynamical systems possess a computational capacity that may be exploited in a reservoir computing paradigm. This paper presents a general representation of dynamical systems which is based on matrix multiplication. That ...
    • Game-Theoretic Learning for Sensor Reliability Evaluation Without Knowledge of the Ground Truth 

      Yazidi, Anis; Hammer, Hugo Lewi; Samouylov, Konstantin; Herrera-Viedma, Enrique (IEEE Transactions on Cybernetics;Date of Publication 06 January 2020, Journal article; Peer reviewed, 2020)
      Sensor fusion has attracted a lot of research attention during the few last years. Recently, a new research direction has emerged dealing with sensor fusion without knowledge of the ground truth. In this article, we present ...
    • GANEx: A complete pipeline of training, inference and benchmarking GAN experiments 

      Thambawita, Vajira; Hammer, Hugo Lewi; Riegler, Michael Alexander; Halvorsen, Pål (International Workshop on Content-Based Multimedia Indexing, CBMI;, Conference object, 2019-10-21)
      Deep learning (DL) is one of the standard methods in the field of multimedia research to perform data classification, detection, segmentation and generation. Within DL, generative adversarial networks (GANs) represents a ...
    • Hvorfor trenger vi statistikk? 

      Brurberg, Kjetil Gundro; Hammer, Hugo Lewi (Sykepleien Forskning;8 (1), Journal article, 2013)