92 citations · 156 across the 15 of their papers we have counts for
8 papers · 1 filter
A Meta-Level Learning Algorithm for Sequential Hyper-Parameter Space Reduction in AutoML
Giorgos Borboudakis, Paulos Charonyktakis, Konstantinos Paraschakis +1
AutoML platforms have numerous options for the algorithms to try for each step of the analysis, i.e., different possible algorithms for imputation, transformations, feature selecti…
A Meta-level Analysis of Online Anomaly Detectors
Antonios Ntroumpogiannis, Michail Giannoulis, Nikolaos Myrtakis +3
Real-time detection of anomalies in streaming data is receiving increasing attention as it allows us to raise alerts, predict faults, and detect intrusions or threats across indust…
On Predictive Explanation of Data Anomalies
Nikolaos Myrtakis, Ioannis Tsamardinos, Vassilis Christophides
Numerous algorithms have been proposed for detecting anomalies (outliers, novelties) in an unsupervised manner. Unfortunately, it is not trivial, in general, to understand why a gi…
Inference of Stochastic Dynamical Systems from Cross-Sectional Population Data
Anastasios Tsourtis, Yannis Pantazis, Ioannis Tsamardinos
Inferring the driving equations of a dynamical system from population or time-course data is important in several scientific fields such as biochemistry, epidemiology, financial ma…
Bootstrapping the Out-of-sample Predictions for Efficient and Accurate Cross-Validation
Ioannis Tsamardinos, Elissavet Greasidou, Michalis Tsagris +1
Cross-Validation (CV), and out-of-sample performance-estimation protocols in general, are often employed both for (a) selecting the optimal combination of algorithms and values of…
Massively-Parallel Feature Selection for Big Data
Ioannis Tsamardinos, Giorgos Borboudakis, Pavlos Katsogridakis +2
We present the Parallel, Forward-Backward with Pruning (PFBP) algorithm for feature selection (FS) in Big Data settings (high dimensionality and/or sample size). To tackle the chal…
Forward-Backward Selection with Early Dropping
Giorgos Borboudakis, Ioannis Tsamardinos
Forward-backward selection is one of the most basic and commonly-used feature selection algorithms available. It is also general and conceptually applicable to many different types…
Discovering and Exploiting Entailment Relationships in Multi-Label Learning
Christina Papagiannopoulou, Grigorios Tsoumakas, Ioannis Tsamardinos
This work presents a sound probabilistic method for enforcing adherence of the marginal probabilities of a multi-label model to automatically discovered deterministic relationships…