Search Results for author:
Found 16 papers, 8 papers with code
You Only Forward Once: Prediction and Rationalization in A Single Forward Pass
In our framework, A pre-trained language model like BERT is deployed to simultaneously perform prediction and rationalization with less impact from interlocking or spurious correlations.
sasdim: self-adaptive noise scaling diffusion model for spatial time series imputation
Spatial time series imputation is critically important to many real applications such as intelligent transportation and air quality monitoring.
Inter-Instance Similarity Modeling for Contrastive Learning
In this paper, we propose a novel image mix method, PatchMix, for contrastive learning in Vision Transformer (ViT), to model inter-instance similarities among images.
Asymmetric Patch Sampling for Contrastive Learning
Asymmetric appearance between positive pair effectively reduces the risk of representation degradation in contrastive learning.
Modeling Global Distribution for Federated Learning with Label Distribution Skew
It introduces a global Generative Adversarial Network to model the global data distribution without access to local datasets, so the global model can be trained using the global information of data distribution without privacy leakage.
Coded Residual Transform for Generalizable Deep Metric Learning
To address this challenge, in this paper, we introduce a new method called coded residual transform (CRT) for deep metric learning to significantly improve its generalization capability.
TripHLApan: predicting HLA molecules binding peptides based on triple coding matrix and transfer learning
In conclusion, TripHLApan is a powerful tool for predicting the binding of HLA-I and HLA-II molecular peptides for the synthesis of tumor vaccines.
Exploring Contextual Relationships for Cervical Abnormal Cell Detection
To mimic these behaviors, we propose to explore contextual relationships to boost the performance of cervical abnormal cell detection.
Taxonomy and evolution predicting using deep learning in images
Molecular and morphological characters, as important parts of biological taxonomy, are contradictory but need to be integrated.
Mushroom image recognition and distance generation based on attention-mechanism model and genetic information
In this paper, we propose a new model based on attention-mechanism, MushroomNet, which applies the lightweight network MobileNetV3 as the backbone model, combined with the attention structure proposed by us, and has achieved excellent performance in the mushroom recognition task.
Optimal Activation Functions for the Random Features Regression Model
The asymptotic mean squared test error and sensitivity of the Random Features Regression model (RFR) have been recently studied.
MRI-based Multi-task Decoupling Learning for Alzheimer's Disease Detection and MMSE Score Prediction: A Multi-site Validation
First, a multi-task learning network is proposed to implement AD detection and MMSE score prediction, which exploits feature correlation by adding three multi-task interaction layers between the backbones of the two tasks.
Graph-Based Stock Recommendation by Time-Aware Relational Attention Network
For a given group of stocks, the proposed TRAN model can output the ranking results of stocks according to their return ratios.
ARSC-Net: Adventitious Respiratory Sound Classification Network Using Parallel Paths with Channel-Spatial Attention
The two types of features are entered into the parallel encoders paths with residual attention for extracting feature representation, and then fused into a channel-spatial attention module to adaptively focus on the important features between channel and spatial part for the classification task.
Ranked #9 on
Audio Classification
on ICBHI Respiratory Sound Database
(using extra training data)
Time Complexity Analysis of Evolutionary Algorithms for 2-Hop (1,2)-Minimum Spanning Tree Problem
Following how evolutionary algorithms are applied to solve the MSTP, we first consider the evolutionary algorithms with search points in edge-based representation adapted to the 2H-(1, 2)-MSTP (including the (1+1) EA, Global Simple Evolutionary Multi-Objective Optimizer and its two variants).
Runtime Performances of Randomized Search Heuristics for the Dynamic Weighted Vertex Cover Problem
Randomized search heuristics such as evolutionary algorithms are frequently applied to dynamic combinatorial optimization problems.
