Search Results for author:
Found 12 papers, 0 papers with code
A Multi-Gate Encoder for Joint Entity and Relation Extraction
“Named entity recognition and relation extraction are core sub-tasks of relational triple extraction.
Ranked #1 on
Relation Extraction
on ACE 2005
(Sentence Encoder metric)
Joint Entity and Relation Extraction
named-entity-recognition
+4
Improved Motor Imagery Classification Using Adaptive Spatial Filters Based on Particle Swarm Optimization Algorithm
The classification accuracy of the proposed method has reached 74. 61% and 81. 19% on datasets 2a and 2b, respectively.
Enhancing Motor Imagery Decoding in Brain Computer Interfaces using Riemann Tangent Space Mapping and Cross Frequency Coupling
Objective: Motor Imagery (MI) serves as a crucial experimental paradigm within the realm of Brain Computer Interfaces (BCIs), aiming to decoding motor intentions from electroencephalogram (EEG) signals.
Popularity, face and voice: Predicting and interpreting livestreamers' retail performance using machine learning techniques
Livestreaming commerce, a hybrid of e-commerce and self-media, has expanded the broad spectrum of traditional sales performance determinants.
RA-CLIP: Retrieval Augmented Contrastive Language-Image Pre-Training
This process can be considered as an open-book exam: with the reference set as a cheat sheet, the proposed method doesn't need to memorize all visual concepts in the training data.
New volatility evolution model after extreme events
Empirical study of the evolutionary behaviors of volatility after endogenous and exogenous events further demonstrates the descriptive power of our new model.
Capped norm linear discriminant analysis and its applications
To improve the robustness of LDA, in this paper, we introduce capped l_{2, 1}-norm of a matrix, which employs non-squared l_2-norm and "capped" operation, and further propose a novel capped l_{2, 1}-norm linear discriminant analysis, called CLDA.
Preventing crash in stock market: The role of economic policy uncertainty during COVID-19
This paper investigates the impact of economic policy uncertainty (EPU) on the crash risk of US stock market during the COVID-19 pandemic.
Visibility graph analysis of economy policy uncertainty indices
Uncertainty plays an important role in the global economy.
The role of global economic policy uncertainty in predicting crude oil futures volatility: Evidence from a two-factor GARCH-MIDAS model
For single-factor models, the GEPU index and its changes, as well as realized volatility, are consistent effective factors in predicting the volatility of crude oil futures.
The impact of economic policy uncertainties on the volatility of European carbon market
The European Union Emission Trading Scheme is a carbon emission allowance trading system designed by Europe to achieve emission reduction targets.
Multi-user Resource Control with Deep Reinforcement Learning in IoT Edge Computing
By leveraging the concept of mobile edge computing (MEC), massive amount of data generated by a large number of Internet of Things (IoT) devices could be offloaded to MEC server at the edge of wireless network for further computational intensive processing.
