Search Results for author:
Found 13 papers, 2 papers with code
AADNet: Exploring EEG Spatiotemporal Information for Fast and Accurate Orientation and Timbre Detection of Auditory Attention Based on A Cue-Masked Paradigm
To obtain high decoding accuracy with low latency, an end-to-end deep learning model, AADNet, was proposed to exploit the spatiotemporal information from the short time window of EEG signals.
Alterations of electrocortical activity during hand movements induced by motor cortex glioma
Glioma cells can reshape functional neuronal networks by hijacking neuronal synapses, leading to partial or complete neurological dysfunction.
Learning on Multimodal Graphs: A Survey
This survey paper conducts a comparative analysis of existing works in multimodal graph learning, elucidating how multimodal learning is achieved across different graph types and exploring the characteristics of prevalent learning techniques.
Principles from Clinical Research for NLP Model Generalization
The NLP community typically relies on performance of a model on a held-out test set to assess generalization.
Effects of Human Adversarial and Affable Samples on BERT Generalization
BERT-based models have had strong performance on leaderboards, yet have been demonstrably worse in real-world settings requiring generalization.
A Survey on Class Imbalance in Federated Learning
We first introduce various types of class imbalance in federated learning, after which we review existing methods for estimating the extent of class imbalance without the need of knowing the actual data to preserve data privacy.
Beyond Just Vision: A Review on Self-Supervised Representation Learning on Multimodal and Temporal Data
Unlike existing reviews of SSRL that have pre-dominately focused upon methods in the fields of CV or NLP for a single modality, we aim to provide the first comprehensive review of multimodal self-supervised learning methods for temporal data.
Open Access Dataset for Electromyography based Multi-code Biometric Authentication
In this study, forearm and wrist EMG data were collected from 43 participants over three different days with long separation while they performed static hand and wrist gestures.
Memorization vs. Generalization : Quantifying Data Leakage in NLP Performance Evaluation
Public datasets are often used to evaluate the efficacy and generalizability of state-of-the-art methods for many tasks in natural language processing (NLP).
ChEMU-Ref: A Corpus for Modeling Anaphora Resolution in the Chemical Domain
Chemical patents contain rich coreference and bridging links, which are the target of this research.
Performance Optimization of Surface Electromyography (sEMG) based Biometric Sensing System for both Verification and Identification
Thus, the combination of the TD feature set and a four-channel sEMG system with one of the electrodes positioned on the FCU are recommended for optimal authentication performance.
Memorization vs. Generalization: Quantifying Data Leakage in NLP Performance Evaluation
Public datasets are often used to evaluate the efficacy and generalizability of state-of-the-art methods for many tasks in natural language processing (NLP).
A Jointly Learned Context-Aware Place of Interest Embedding for Trip Recommendations
We propose two trip recommendation algorithms based on our context-aware POI embedding.
