research
∙
06/12/2023
Feature Fusion from Head to Tail: an Extreme Augmenting Strategy for Long-Tailed Visual Recognition
The imbalanced distribution of long-tailed data poses a challenge for de...
share
research
∙
05/19/2023
Long-tailed Visual Recognition via Gaussian Clouded Logit Adjustment
Long-tailed data is still a big challenge for deep neural networks, even...
research
∙
05/18/2023
Feature-Balanced Loss for Long-Tailed Visual Recognition
Deep neural networks frequently suffer from performance degradation when...
research
∙
05/18/2023
Adjusting Logit in Gaussian Form for Long-Tailed Visual Recognition
It is not uncommon that real-world data are distributed with a long tail...
research
∙
04/03/2023
Long-Tailed Visual Recognition via Self-Heterogeneous Integration with Knowledge Excavation
Deep neural networks have made huge progress in the last few decades. Ho...
research
∙
03/04/2023
Federated Semi-Supervised Learning with Annotation Heterogeneity
Federated Semi-Supervised Learning (FSSL) aims to learn a global model f...
research
∙
02/03/2023
Uniform tensor clustering by jointly exploring sample affinities of various orders
Conventional clustering methods based on pairwise affinity usually suffe...
research
∙
08/21/2022
Combating Noisy-Labeled and Imbalanced Data by Two Stage Bi-Dimensional Sample Selection
Robust learning on noisy-labeled data has been an important task in real...
research
∙
05/03/2022
Compact Neural Networks via Stacking Designed Basic Units
Unstructured pruning has the limitation of dealing with the sparse and i...
research
∙
04/30/2022
FEDIC: Federated Learning on Non-IID and Long-Tailed Data via Calibrated Distillation
Federated learning provides a privacy guarantee for generating good deep...
research
∙
03/03/2022
Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-wise Distributed Data
Despite enormous research interest and rapid application of federated le...
research
∙
05/15/2021
FDDH: Fast Discriminative Discrete Hashing for Large-Scale Cross-Modal Retrieval
Cross-modal hashing, favored for its effectiveness and efficiency, has r...
research
∙
10/19/2019
Solving Dynamic Multi-objective Optimization Problems Using Incremental Support Vector Machine
The main feature of the Dynamic Multi-objective Optimization Problems (D...
research
∙
01/29/2019
Bayes Imbalance Impact Index: A Measure of Class Imbalanced Dataset for Classification Problem
Recent studies have shown that imbalance ratio is not the only cause of ...
research
∙
05/04/2018
MTFH: A Matrix Tri-Factorization Hashing Framework for Efficient Cross-Modal Retrieval
Hashing has recently sparked a great revolution in cross-modal retrieval...
research
∙
11/05/2017