
Remote Multilinear Compressive Learning with Adaptive Compression
Multilinear Compressive Learning (MCL) is an efficient signal acquisitio...
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Bilinear Input Normalization for Neural Networks in Financial Forecasting
Data normalization is one of the most important preprocessing steps when...
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Knowledge Distillation By Sparse Representation Matching
Knowledge Distillation refers to a class of methods that transfers the k...
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Performance Indicator in Multilinear Compressive Learning
Recently, the Multilinear Compressive Learning (MCL) framework was propo...
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Attentionbased Neural BagofFeatures Learning for Sequence Data
In this paper, we propose 2DAttention (2DA), a generic attention formul...
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Data Normalization for Bilinear Structures in HighFrequency Financial Timeseries
Financial timeseries analysis and forecasting have been extensively stu...
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Multilinear Compressive Learning with Prior Knowledge
The recently proposed Multilinear Compressive Learning (MCL) framework c...
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Subset Sampling For Progressive Neural Network Learning
Progressive Neural Network Learning is a class of algorithms that increm...
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Multilinear Compressive Learning
Compressive Learning is an emerging topic that combines signal acquisiti...
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Datadriven Neural Architecture Learning For Financial Timeseries Forecasting
Forecasting based on financial timeseries is a challenging task since m...
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Progressive Operational Perceptron with Memory
Generalized Operational Perceptron (GOP) was proposed to generalize the ...
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Heterogeneous Multilayer Generalized Operational Perceptron
The traditional Multilayer Perceptron (MLP) using McCullochPitts neuron...
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Temporal Attention augmented Bilinear Network for Financial TimeSeries Data Analysis
Financial timeseries forecasting has long been a challenging problem be...
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Multilinear ClassSpecific Discriminant Analysis
There has been a great effort to transfer linear discriminant techniques...
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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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Tensor Representation in HighFrequency Financial Data for Price Change Prediction
Nowadays, with the availability of massive amount of trade data collecte...
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Dat Thanh Tran
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