8 citations · 18 across the 3 of their papers we have counts for
6 papers
Performance Indicator in Multilinear Compressive Learning
Dat Thanh Tran, Moncef Gabbouj, Alexandros Iosifidis
Recently, the Multilinear Compressive Learning (MCL) framework was proposed to efficiently optimize the sensing and learning steps when working with multidimensional signals, i.e.…
Attention-based Neural Bag-of-Features Learning for Sequence Data
Dat Thanh Tran, Nikolaos Passalis, Anastasios Tefas +2
In this paper, we propose 2D-Attention (2DA), a generic attention formulation for sequence data, which acts as a complementary computation block that can detect and focus on releva…
Data Normalization for Bilinear Structures in High-Frequency Financial Time-series
Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj +1
Financial time-series analysis and forecasting have been extensively studied over the past decades, yet still remain as a very challenging research topic. Since the financial marke…
Multilinear Compressive Learning with Prior Knowledge
Dat Thanh Tran, Moncef Gabbouj, Alexandros Iosifidis
The recently proposed Multilinear Compressive Learning (MCL) framework combines Multilinear Compressive Sensing and Machine Learning into an end-to-end system that takes into accou…
Subset Sampling For Progressive Neural Network Learning
Dat Thanh Tran, Moncef Gabbouj, Alexandros Iosifidis
Progressive Neural Network Learning is a class of algorithms that incrementally construct the network's topology and optimize its parameters based on the training data. While this…
Data-driven Neural Architecture Learning For Financial Time-series Forecasting
Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj +1
Forecasting based on financial time-series is a challenging task since most real-world data exhibits nonstationary property and nonlinear dependencies. In addition, different data…