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11/01/2022
Recognition of Defective Mineral Wool Using Pruned ResNet Models
Mineral wool production is a non-linear process that makes it hard to co...
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07/23/2022
Augmented Bilinear Network for Incremental Multi-Stock Time-Series Classification
Deep Learning models have become dominant in tackling financial time-ser...
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07/04/2022
Variational Neural Networks
Bayesian Neural Networks (BNNs) provide a tool to estimate the uncertain...
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03/15/2022
How informative is the Order Book Beyond the Best Levels? Machine Learning Perspective
Research on limit order book markets has been rapidly growing and nowada...
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01/14/2022
Multi-head Temporal Attention-Augmented Bilinear Network for Financial time series prediction
Financial time-series forecasting is one of the most challenging domains...
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09/02/2021
Remote Multilinear Compressive Learning with Adaptive Compression
Multilinear Compressive Learning (MCL) is an efficient signal acquisitio...
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09/01/2021
Bilinear Input Normalization for Neural Networks in Financial Forecasting
Data normalization is one of the most important preprocessing steps when...
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03/31/2021
Knowledge Distillation By Sparse Representation Matching
Knowledge Distillation refers to a class of methods that transfers the k...
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09/22/2020
Performance Indicator in Multilinear Compressive Learning
Recently, the Multilinear Compressive Learning (MCL) framework was propo...
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05/25/2020
Attention-based Neural Bag-of-Features Learning for Sequence Data
In this paper, we propose 2D-Attention (2DA), a generic attention formul...
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03/01/2020
Data Normalization for Bilinear Structures in High-Frequency Financial Time-series
Financial time-series analysis and forecasting have been extensively stu...
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02/17/2020
Multilinear Compressive Learning with Prior Knowledge
The recently proposed Multilinear Compressive Learning (MCL) framework c...
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02/17/2020
Subset Sampling For Progressive Neural Network Learning
Progressive Neural Network Learning is a class of algorithms that increm...
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05/17/2019
Multilinear Compressive Learning
Compressive Learning is an emerging topic that combines signal acquisiti...
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03/05/2019
Data-driven Neural Architecture Learning For Financial Time-series Forecasting
Forecasting based on financial time-series is a challenging task since m...
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08/20/2018
Progressive Operational Perceptron with Memory
Generalized Operational Perceptron (GOP) was proposed to generalize the ...
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04/13/2018
Heterogeneous Multilayer Generalized Operational Perceptron
The traditional Multilayer Perceptron (MLP) using McCulloch-Pitts neuron...
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12/04/2017
Temporal Attention augmented Bilinear Network for Financial Time-Series Data Analysis
Financial time-series forecasting has long been a challenging problem be...
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10/29/2017
Multilinear Class-Specific Discriminant Analysis
There has been a great effort to transfer linear discriminant techniques...
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09/28/2017
Improving Efficiency in Convolutional Neural Network with Multilinear Filters
The excellent performance of deep neural networks has enabled us to solv...
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09/05/2017
