Nikolaos Passalis

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ARISTOTLE UNIVERSITY OF THESSALONIKI ∙ Tampere Universities

Graph Embedding with Data Uncertainty

spectral-based subspace learning is a common data preprocessing step in ...
09/01/2020 ∙ by Firas Laakom, et al. ∙ 0 ∙ share

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Attention-based Neural Bag-of-Features Learning for Sequence Data

In this paper, we propose 2D-Attention (2DA), a generic attention formul...
05/25/2020 ∙ by Dat Thanh Tran, et al. ∙ 0 ∙ share

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AutoSOS: Towards Multi-UAV Systems Supporting Maritime Search and Rescue with Lightweight AI and Edge Computing

Rescue vessels are the main actors in maritime safety and rescue operati...
05/07/2020 ∙ by Jorge Peña Queralta, et al. ∙ 0 ∙ share

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Heterogeneous Knowledge Distillation using Information Flow Modeling

Knowledge Distillation (KD) methods are capable of transferring the know...
05/02/2020 ∙ by Nikolaos Passalis, et al. ∙ 0 ∙ share

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deepsing: Generating Sentiment-aware Visual Stories using Cross-modal Music Translation

In this paper we propose a deep learning method for performing attribute...
12/11/2019 ∙ by Nikolaos Passalis, et al. ∙ 18 ∙ share

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Reversible Privacy Preservation using Multi-level Encryption and Compressive Sensing

Security monitoring via ubiquitous cameras and their more extended in in...
06/20/2019 ∙ by Mehmet Yamac, et al. ∙ 0 ∙ share

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Bag of Color Features For Color Constancy

In this paper, we propose a novel color constancy approach, called Bag o...
06/11/2019 ∙ by Firas Laakom, et al. ∙ 4 ∙ share

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Deep Adaptive Input Normalization for Price Forecasting using Limit Order Book Data

Deep Learning (DL) models can be used to tackle time series analysis tas...
02/21/2019 ∙ by Nikolaos Passalis, et al. ∙ 0 ∙ share

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Temporal Logistic Neural Bag-of-Features for Financial Time series Forecasting leveraging Limit Order Book Data

Time series forecasting is a crucial component of many important applica...
01/24/2019 ∙ by Nikolaos Passalis, et al. ∙ 0 ∙ share

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Deep Supervised Hashing leveraging Quadratic Spherical Mutual Information for Content-based Image Retrieval

Several deep supervised hashing techniques have been proposed to allow f...
01/16/2019 ∙ by Nikolaos Passalis, et al. ∙ 0 ∙ share

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Style Decomposition for Improved Neural Style Transfer

Universal Neural Style Transfer (NST) methods are capable of performing ...
11/30/2018 ∙ by Paraskevas Pegios, et al. ∙ 8 ∙ share

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Interactive dimensionality reduction using similarity projections

Recent advances in machine learning allow us to analyze and describe the...
11/13/2018 ∙ by Dimitris Spathis, et al. ∙ 20 ∙ share

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Decoding Generic Visual Representations From Human Brain Activity using Machine Learning

Among the most impressive recent applications of neural decoding is the ...
11/05/2018 ∙ by Angeliki Papadimitriou, et al. ∙ 0 ∙ share

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Using Deep Learning for price prediction by exploiting stationary limit order book features

The recent surge in Deep Learning (DL) research of the past decade has s...
10/23/2018 ∙ by Avraam Tsantekidis, et al. ∙ 0 ∙ share

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Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data

Forecasting the movements of stock prices is one the most challenging pr...
09/19/2018 ∙ by Paraskevi Nousi, et al. ∙ 0 ∙ share

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Probabilistic Knowledge Transfer for Deep Representation Learning

Knowledge Transfer (KT) techniques tackle the problem of transferring th...
03/28/2018 ∙ by Nikolaos Passalis, et al. ∙ 0 ∙ share

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Learning Bag-of-Features Pooling for Deep Convolutional Neural Networks

Convolutional Neural Networks (CNNs) are well established models capable...
07/25/2017 ∙ by Nikolaos Passalis, et al. ∙ 0 ∙ share

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Dimensionality Reduction using Similarity-induced Embeddings

The vast majority of Dimensionality Reduction (DR) techniques rely on se...
06/18/2017 ∙ by Nikolaos Passalis, et al. ∙ 0 ∙ share

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Nikolaos Passalis

Featured Co-authors

Moncef Gabbouj

Alexandros Iosifidis

Jenni Raitoharju

Jorge Peña Queralta

Tomi Westerlund

Anastasios Tefas

Dat Thanh Tran

Juho Kanniainen

Mehmet Yamac

Jarno Nikkanen

Dimitris Spathis

Graph Embedding with Data Uncertainty

Attention-based Neural Bag-of-Features Learning for Sequence Data

AutoSOS: Towards Multi-UAV Systems Supporting Maritime Search and Rescue with Lightweight AI and Edge Computing

Heterogeneous Knowledge Distillation using Information Flow Modeling

deepsing: Generating Sentiment-aware Visual Stories using Cross-modal Music Translation

Reversible Privacy Preservation using Multi-level Encryption and Compressive Sensing

Bag of Color Features For Color Constancy

Deep Adaptive Input Normalization for Price Forecasting using Limit Order Book Data

Temporal Logistic Neural Bag-of-Features for Financial Time series Forecasting leveraging Limit Order Book Data

Deep Supervised Hashing leveraging Quadratic Spherical Mutual Information for Content-based Image Retrieval

Style Decomposition for Improved Neural Style Transfer

Interactive dimensionality reduction using similarity projections

Decoding Generic Visual Representations From Human Brain Activity using Machine Learning

Using Deep Learning for price prediction by exploiting stationary limit order book features

Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data

Probabilistic Knowledge Transfer for Deep Representation Learning

Learning Bag-of-Features Pooling for Deep Convolutional Neural Networks

Dimensionality Reduction using Similarity-induced Embeddings