249 citations · 1.5k across the 70 of their papers we have counts for
9 papers · 1 filter
Using Deep Learning for price prediction by exploiting stationary limit order book features
Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas +3
The recent surge in Deep Learning (DL) research of the past decade has successfully provided solutions to many difficult problems. The field of quantitative analysis has been slowl…
Compressively Sensed Image Recognition
Aysen Degerli, Sinem Aslan, Mehmet Yamac +2
Compressive Sensing (CS) theory asserts that sparse signal reconstruction is possible from a small number of linear measurements. Although CS enables low-cost linear sampling, it r…
Finding Better Topologies for Deep Convolutional Neural Networks by Evolution
Honglei Zhang, Serkan Kiranyaz, Moncef Gabbouj
Due to the nonlinearity of artificial neural networks, designing topologies for deep convolutional neural networks (CNN) is a challenging task and often only heuristic approach, su…
Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data
Paraskevi Nousi, Avraam Tsantekidis, Nikolaos Passalis +5
Forecasting the movements of stock prices is one the most challenging problems in financial markets analysis. In this paper, we use Machine Learning (ML) algorithms for the predict…
Progressive Operational Perceptron with Memory
Dat Thanh Tran, Serkan Kiranyaz, Moncef Gabbouj +1
Generalized Operational Perceptron (GOP) was proposed to generalize the linear neuron model in the traditional Multilayer Perceptron (MLP) and this model can mimic the synaptic con…
Heterogeneous Multilayer Generalized Operational Perceptron
Dat Thanh Tran, Serkan Kiranyaz, Moncef Gabbouj +1
The traditional Multilayer Perceptron (MLP) using McCulloch-Pitts neuron model is inherently limited to a set of neuronal activities, i.e., linear weighted sum followed by nonlinea…
Weighted Linear Discriminant Analysis based on Class Saliency Information
Lei Xu, Alexandros Iosifidis, Moncef Gabbouj
In this paper, we propose a new variant of Linear Discriminant Analysis to overcome underlying drawbacks of traditional LDA and other LDA variants targeting problems involving imba…
Subspace Support Vector Data Description
Fahad Sohrab, Jenni Raitoharju, Moncef Gabbouj +1
This paper proposes a novel method for solving one-class classification problems. The proposed approach, namely Subspace Support Vector Data Description, maps the data to a subspac…
Deep Multi-view Learning to Rank
Guanqun Cao, Alexandros Iosifidis, Moncef Gabbouj +2
We study the problem of learning to rank from multiple information sources. Though multi-view learning and learning to rank have been studied extensively leading to a wide range of…