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09/15/2023
Adaptive Priority Reweighing for Generalizing Fairness Improvement
With the increasing penetration of machine learning applications in crit...
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06/16/2023
Structured Cooperative Learning with Graphical Model Priors
We study how to train personalized models for different tasks on decentr...
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04/27/2023
Moderately Distributional Exploration for Domain Generalization
Domain generalization (DG) aims to tackle the distribution shift between...
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04/12/2023
Semantic-Aware Mixup for Domain Generalization
Deep neural networks (DNNs) have shown exciting performance in various t...
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04/07/2023
On Efficient Training of Large-Scale Deep Learning Models: A Literature Review
The field of deep learning has witnessed significant progress, particula...
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11/02/2022
Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach
Data augmentation is a critical contributing factor to the success of de...
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09/29/2022
Towards Lightweight Black-Box Attacks against Deep Neural Networks
Black-box attacks can generate adversarial examples without accessing th...
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07/19/2022
Self-Supervision Can Be a Good Few-Shot Learner
Existing few-shot learning (FSL) methods rely on training with a large l...
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06/21/2022
Bi-Calibration Networks for Weakly-Supervised Video Representation Learning
The leverage of large volumes of web videos paired with the searched que...
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06/01/2022
DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse Training
Personalized federated learning is proposed to handle the data heterogen...
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05/06/2022
Prompt Distribution Learning
We present prompt distribution learning for effectively adapting a pre-t...
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12/14/2021
A Style and Semantic Memory Mechanism for Domain Generalization
Mainstream state-of-the-art domain generalization algorithms tend to pri...
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12/14/2021
Transferrable Contrastive Learning for Visual Domain Adaptation
Self-supervised learning (SSL) has recently become the favorite among fe...
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07/01/2021
Revisiting Knowledge Distillation: An Inheritance and Exploration Framework
Knowledge Distillation (KD) is a popular technique to transfer knowledge...
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06/29/2021
Domain-Class Correlation Decomposition for Generalizable Person Re-Identification
Domain generalization in person re-identification is a highly important ...
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06/11/2021
Adversarial Robustness through the Lens of Causality
The adversarial vulnerability of deep neural networks has attracted sign...
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11/26/2020
Spatio-Temporal Inception Graph Convolutional Networks for Skeleton-Based Action Recognition
Skeleton-based human action recognition has attracted much attention wit...
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08/31/2020
Learning to Localize Actions from Moments
With the knowledge of action moments (i.e., trimmed video clips that eac...
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11/28/2019
Transform-Invariant Convolutional Neural Networks for Image Classification and Search
Convolutional neural networks (CNNs) have achieved state-of-the-art resu...
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11/28/2019
Patch Reordering: a Novel Way to Achieve Rotation and Translation Invariance in Convolutional Neural Networks
Convolutional Neural Networks (CNNs) have demonstrated state-of-the-art ...
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11/28/2019
Continuous Dropout
Dropout has been proven to be an effective algorithm for training robust...
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11/21/2019
Quantization Networks
Although deep neural networks are highly effective, their high computati...
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09/09/2019
Gaussian Temporal Awareness Networks for Action Localization
Temporally localizing actions in a video is a fundamental challenge in v...
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08/26/2019
Mocycle-GAN: Unpaired Video-to-Video Translation
Unsupervised image-to-image translation is the task of translating an im...
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06/13/2019
Learning Spatio-Temporal Representation with Local and Global Diffusion
Convolutional Neural Networks (CNN) have been regarded as a powerful cla...
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04/25/2019
Exploring Object Relation in Mean Teacher for Cross-Domain Detection
Rendering synthetic data (e.g., 3D CAD-rendered images) to generate anno...
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04/06/2019
Camera Lens Super-Resolution
Existing methods for single image super-resolution (SR) are typically ev...
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04/03/2019
On Better Exploring and Exploiting Task Relationships in Multi-Task Learning: Joint Model and Feature Learning
Multitask learning (MTL) aims to learn multiple tasks simultaneously thr...
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09/05/2018
Towards a Better Match in Siamese Network Based Visual Object Tracker
Recently, Siamese network based trackers have received tremendous intere...
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07/23/2018
Domain Generalization via Conditional Invariant Representation
Domain generalization aims to apply knowledge gained from multiple label...
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02/24/2018
A Twofold Siamese Network for Real-Time Object Tracking
Observing that Semantic features learned in an image classification task...
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03/14/2011
