Titlebook: Neural Information Processing; 30th International C Biao Luo,Long Cheng,Chaojie Li Conference proceedings 2024 The Editor(s) (if applicable

有機(jī)體

Brain-Inspired Binaural Sound Source Localization Method Based on?Liquid State Machinea leap in machine learning. However, prior approaches lack the ability to make a trade-off between parameter size and accuracy, which is a primary obstacle to their further implementation on resource-constrained devices. Spiking Neural Network (SNN)-based models have also emerged due to their inhere

幻想

A Causality-Based Interpretable Cognitive Diagnosis Model Nevertheless, deep learning-based CDMs are inherently opaque, posing challenges in providing psychological insights into the reasoning behind predicted outcomes. We address this by creating three interpretable parameters: skill mastery, exercise difficulty, and exercise discrimination. Inspired by

tolerance

RoBrain: Towards Robust Brain-to-Image Reconstruction via?Cross-Domain Contrastive Learningbrain has attracted more and more attention. Neural reconstruction task, which intends to reconstruct stimulus images from fMRI, is one of the most challenging tasks in neural decoding. Due to the instability of neural signals, trials of fMRI collected under the same stimulus prove to be very differ

裙帶關(guān)系

MTLAN: Multi-Task Learning and?Auxiliary Network for?Enhanced Sentence Embeddingets, including STS and SICK, to evaluate both monolingual sentence similarity and cross-lingual semantic similarity. The empirical results demonstrate the significant superiority of our proposed model over state-of-the-art methods.

Exclaim

Correlated Online k-Nearest Neighbors Regressor Chain for?Online Multi-output Regressiont CONNRC consistently outperforms the other algorithms in terms of average Mean Absolute Error, demonstrating its superior accuracy in multi-output regression tasks. However, the time performance of CONNRC requires further improvement, indicating an area for future research and optimization.

暫時(shí)休息

Evolutionary Computation for Berth Allocation Problems: A SurveySecond, this paper introduces three typical EC algorithms (including genetic algorithm, particle swarm optimization, and ant colony optimization) and analyzes the existing studies of using these EC algorithms to solve BAPs. Finally, this paper analyzes the future research directions of the EC algori

拾落穗

盟軍

A Fine-Grained Domain Adaptation Method for Cross-Session Vigilance Estimation in SSVEP-Based BCI, the graph convolution network (GCN) was built to extract deep features of EEG. The fined-grained feature alignment was proposed to highlight the importance of the different channels figured out by the attention weights mechanism and aligns the feature distributions between source and target domain

背書

RMPE:Reducing Residual Membrane Potential Error for?Enabling High-Accuracy and?Ultra-low-latency Spiate RMPE. Finally, a two-stage ANN-SNN conversion scheme is proposed to eliminate the quantization error, the truncation error, and the RMPE separately. We evaluate our method on CIRFARs and ImageNet, and the experimental results show that the proposed ANN-SNN conversion method has a significant red

繁榮中國(guó)