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07/28/2023
Private-Library-Oriented Code Generation with Large Language Models
Large language models (LLMs), such as Codex and GPT-4, have recently sho...
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06/14/2023
Improving Generalization in Meta-Learning via Meta-Gradient Augmentation
Meta-learning methods typically follow a two-loop framework, where each ...
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06/02/2023
Recent Advances of Local Mechanisms in Computer Vision: A Survey and Outlook of Recent Work
Inspired by the fact that human brains can emphasize discriminative part...
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05/09/2023
Towards Understanding Generalization of Macro-AUC in Multi-label Learning
Macro-AUC is the arithmetic mean of the class-wise AUCs in multi-label l...
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03/11/2023
MetaViewer: Towards A Unified Multi-View Representation
Existing multi-view representation learning methods typically follow a s...
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03/04/2023
Fine-Grained Classification with Noisy Labels
Learning with noisy labels (LNL) aims to ensure model generalization giv...
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09/16/2022
Topological Structure Learning for Weakly-Supervised Out-of-Distribution Detection
Out-of-distribution (OOD) detection is the key to deploying models safel...
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08/24/2022
Self-Filtering: A Noise-Aware Sample Selection for Label Noise with Confidence Penalization
Sample selection is an effective strategy to mitigate the effect of labe...
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06/12/2022
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement
Remote photoplethysmography (rPPG) based physiological measurement has g...
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06/07/2022
Neural Network Compression via Effective Filter Analysis and Hierarchical Pruning
Network compression is crucial to making the deep networks to be more ef...
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05/22/2022
Active Source Free Domain Adaptation
Source free domain adaptation (SFDA) aims to transfer a trained source m...
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03/22/2022
Exploring Linear Feature Disentanglement For Neural Networks
Non-linear activation functions, e.g., Sigmoid, ReLU, and Tanh, have ach...
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03/18/2022
Series Photo Selection via Multi-view Graph Learning
Series photo selection (SPS) is an important branch of the image aesthet...
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11/08/2021
Learning to Rectify for Robust Learning with Noisy Labels
Label noise significantly degrades the generalization ability of deep mo...
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08/13/2021
Learning Transferable Parameters for Unsupervised Domain Adaptation
Unsupervised domain adaptation (UDA) enables a learning machine to adapt...
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07/22/2021
Tri-Branch Convolutional Neural Networks for Top-k Focused Academic Performance Prediction
Academic performance prediction aims to leverage student-related informa...
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05/14/2021
Attentional Prototype Inference for Few-Shot Semantic Segmentation
This paper aims to address few-shot semantic segmentation. While existin...
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05/08/2021
MetaKernel: Learning Variational Random Features with Limited Labels
Few-shot learning deals with the fundamental and challenging problem of ...
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04/01/2021
A Survey on Natural Language Video Localization
Natural language video localization (NLVL), which aims to locate a targe...
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12/23/2020
Direct Estimation of Spinal Cobb Angles by Structured Multi-Output Regression
The Cobb angle that quantitatively evaluates the spinal curvature plays ...
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10/07/2020
Attention Model Enhanced Network for Classification of Breast Cancer Image
Breast cancer classification remains a challenging task due to inter-cla...
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10/07/2020
Learning Binary Semantic Embedding for Histology Image Classification and Retrieval
With the development of medical imaging technology and machine learning,...
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06/11/2020
Learning to Learn Kernels with Variational Random Features
In this work, we introduce kernels with random Fourier features in the m...
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04/28/2020
Unifying Neural Learning and Symbolic Reasoning for Spinal Medical Report Generation
Automated medical report generation in spine radiology, i.e., given spin...
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04/27/2020
Towards Accurate and Robust Domain Adaptation under Noisy Environments
In non-stationary environments, learning machines usually confront the d...
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04/24/2020
Reinforcing Short-Length Hashing
Due to the compelling efficiency in retrieval and storage, similarity-pr...
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09/04/2019
PISEP^2: Pseudo Image Sequence Evolution based 3D Pose Prediction
Pose prediction is to predict future poses given a window of previous po...
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10/01/2018
Fusion Hashing: A General Framework for Self-improvement of Hashing
Hashing has been widely used for efficient similarity search based on it...
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01/27/2016