
-
Graph Embedding with Data Uncertainty
spectral-based subspace learning is a common data preprocessing step in ...
read it
-
Attention-based Neural Bag-of-Features Learning for Sequence Data
In this paper, we propose 2D-Attention (2DA), a generic attention formul...
read it
-
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...
read it
-
Heterogeneous Knowledge Distillation using Information Flow Modeling
Knowledge Distillation (KD) methods are capable of transferring the know...
read it
-
deepsing: Generating Sentiment-aware Visual Stories using Cross-modal Music Translation
In this paper we propose a deep learning method for performing attribute...
read it
-
Reversible Privacy Preservation using Multi-level Encryption and Compressive Sensing
Security monitoring via ubiquitous cameras and their more extended in in...
read it
-
Bag of Color Features For Color Constancy
In this paper, we propose a novel color constancy approach, called Bag o...
read it
-
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...
read it
-
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...
read it
-
Deep Supervised Hashing leveraging Quadratic Spherical Mutual Information for Content-based Image Retrieval
Several deep supervised hashing techniques have been proposed to allow f...
read it
-
Style Decomposition for Improved Neural Style Transfer
Universal Neural Style Transfer (NST) methods are capable of performing ...
read it
-
Interactive dimensionality reduction using similarity projections
Recent advances in machine learning allow us to analyze and describe the...
read it
-
Decoding Generic Visual Representations From Human Brain Activity using Machine Learning
Among the most impressive recent applications of neural decoding is the ...
read it
-
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...
read it
-
Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data
Forecasting the movements of stock prices is one the most challenging pr...
read it
-
Probabilistic Knowledge Transfer for Deep Representation Learning
Knowledge Transfer (KT) techniques tackle the problem of transferring th...
read it
-
Learning Bag-of-Features Pooling for Deep Convolutional Neural Networks
Convolutional Neural Networks (CNNs) are well established models capable...
read it
-
Dimensionality Reduction using Similarity-induced Embeddings
The vast majority of Dimensionality Reduction (DR) techniques rely on se...
read it