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07/06/2023
Finding Favourite Tuples on Data Streams with Provably Few Comparisons
One of the most fundamental tasks in data science is to assist a user wi...
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06/04/2023
Sparse Convolution for Approximate Sparse Instance
Computing the convolution A ⋆ B of two vectors of dimension n is one of ...
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05/15/2023
Deep-Unfolding for Next-Generation Transceivers
The stringent performance requirements of future wireless networks, such...
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02/25/2023
Partial Label Learning for Emotion Recognition from EEG
Fully supervised learning has recently achieved promising performance in...
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01/17/2023
Ranking with submodular functions on the fly
Maximizing submodular functions have been studied extensively for a wide...
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11/03/2022
A Convergence Theory for Federated Average: Beyond Smoothness
Federated learning enables a large amount of edge computing devices to l...
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08/23/2022
Regularized impurity reduction: Accurate decision trees with complexity guarantees
Decision trees are popular classification models, providing high accurac...
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06/08/2022
Robust Semantic Communications with Masked VQ-VAE Enabled Codebook
Although semantic communications have exhibited satisfactory performance...
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04/08/2022
Ranking with submodular functions on a budget
Submodular maximization has been the backbone of many important machine-...
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03/02/2022
Optimal deletion-robust coreset for submodular maximization
In recent years we have witnessed an increase on the development of meth...
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02/11/2022
PARSE: Pairwise Alignment of Representations in Semi-Supervised EEG Learning for Emotion Recognition
We propose PARSE, a novel semi-supervised architecture for learning stro...
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02/07/2022
Robust Semantic Communications Against Semantic Noise
Although the semantic communications have exhibited satisfactory perform...
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09/24/2021
Holistic Semi-Supervised Approaches for EEG Representation Learning
Recently, supervised methods, which often require substantial amounts of...
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07/28/2021
Deep Recurrent Semi-Supervised EEG Representation Learning for Emotion Recognition
EEG-based emotion recognition often requires sufficient labeled training...
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04/30/2021
Distilling EEG Representations via Capsules for Affective Computing
Affective computing with Electroencephalogram (EEG) is a challenging tas...
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08/19/2020
RFNet: Riemannian Fusion Network for EEG-based Brain-Computer Interfaces
This paper presents the novel Riemannian Fusion Network (RFNet), a deep ...
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06/17/2020
Diverse Rule Sets
While machine-learning models are flourishing and transforming many aspe...
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01/09/2020
Maximizing diversity over clustered data
Maximum diversity aims at selecting a diverse set of high-quality object...
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12/17/2019
Capsule Attention for Multimodal EEG and EOG Spatiotemporal Representation Learning with Application to Driver Vigilance Estimation
Driver vigilance estimation is an important task for transportation safe...
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08/06/2019
Classification of Hand Movements from EEG using a Deep Attention-based LSTM Network
Classifying limb movements using brain activity is an important task in ...
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06/10/2019