27 citations · 115 across the 9 of their papers we have counts for
9 papers
Wisdom of the Contexts: Active Ensemble Learning for Contextual Anomaly Detection
Ece Calikus, Slawomir Nowaczyk, Mohamed-Rafik Bouguelia +1
In contextual anomaly detection, an object is only considered anomalous within a specific context. Most existing methods for CAD use a single context based on a set of user-specifi…
No Free Lunch But A Cheaper Supper: A General Framework for Streaming Anomaly Detection
Ece Calikus, Slawomir Nowaczyk, Anita Sant'Anna +1
In recent years, there has been increased research interest in detecting anomalies in temporal streaming data. A variety of algorithms have been developed in the data mining commun…
Differentially Private Markov Chain Monte Carlo
Mikko A. Heikkilä, Joonas Jälkö, Onur Dikmen +1
Recent developments in differentially private (DP) machine learning and DP Bayesian learning have enabled learning under strong privacy guarantees for the training data subjects. I…
Differentially Private Variational Inference for Non-conjugate Models
Joonas Jälkö, Onur Dikmen, Antti Honkela
Many machine learning applications are based on data collected from people, such as their tastes and behaviour as well as biological traits and genetic data. Regardless of how impo…
Efficient differentially private learning improves drug sensitivity prediction
Antti Honkela, Mrinal Das, Arttu Nieminen +2
Users of a personalised recommendation system face a dilemma: recommendations can be improved by learning from data, but only if the other users are willing to share their private…
Learning Mixtures of Ising Models using Pseudolikelihood
Onur Dikmen
Maximum pseudolikelihood method has been among the most important methods for learning parameters of statistical physics models, such as Ising models. In this paper, we study how p…
Optimizing the Information Retrieval Trade-off in Data Visualization Using -Divergence
Ehsan Amid, Onur Dikmen, Erkki Oja
Data visualization is one of the major applications of nonlinear dimensionality reduction. From the information retrieval perspective, the quality of a visualization can be evaluat…
Learning the Information Divergence
Onur Dikmen, Zhirong Yang, Erkki Oja
Information divergence that measures the difference between two nonnegative matrices or tensors has found its use in a variety of machine learning problems. Examples are Nonnegativ…
Consistent inference of a general model using the pseudo-likelihood method
Alexander Mozeika, Onur Dikmen, Joonas Piili
Recently maximum pseudo-likelihood (MPL) inference method has been successfully applied to statistical physics models with intractable likelihoods. We use information theory to der…