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09/06/2023
MCM: Multi-condition Motion Synthesis Framework for Multi-scenario
The objective of the multi-condition human motion synthesis task is to i...
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09/02/2023
Regularly Truncated M-estimators for Learning with Noisy Labels
The sample selection approach is very popular in learning with noisy lab...
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07/14/2023
Exploiting Counter-Examples for Active Learning with Partial labels
This paper studies a new problem, active learning with partial labels (A...
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07/12/2023
Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation
Generating unlabeled data has been recently shown to help address the fe...
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07/11/2023
Unleashing the Potential of Regularization Strategies in Learning with Noisy Labels
In recent years, research on learning with noisy labels has focused on d...
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06/20/2023
A Universal Unbiased Method for Classification from Aggregate Observations
In conventional supervised classification, true labels are required for ...
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06/15/2023
On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation
Although powerful graph neural networks (GNNs) have boosted numerous rea...
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06/12/2023
Making Binary Classification from Multiple Unlabeled Datasets Almost Free of Supervision
Training a classifier exploiting a huge amount of supervised data is exp...
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06/06/2023
Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability
Out-of-distribution (OOD) detection is an indispensable aspect of secure...
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05/28/2023
BadLabel: A Robust Perspective on Evaluating and Enhancing Label-noise Learning
Label-noise learning (LNL) aims to increase the model's generalization g...
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05/25/2023
Detecting Adversarial Data by Probing Multiple Perturbations Using Expected Perturbation Score
Adversarial detection aims to determine whether a given sample is an adv...
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05/16/2023
AMD: Autoregressive Motion Diffusion
Human motion generation aims to produce plausible human motion sequences...
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05/14/2023
SongDriver2: Real-time Emotion-based Music Arrangement with Soft Transition
Real-time emotion-based music arrangement, which aims to transform a giv...
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04/30/2023
Assessing Vulnerabilities of Adversarial Learning Algorithm through Poisoning Attacks
Adversarial training (AT) is a robust learning algorithm that can defend...
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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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04/22/2023
Towards Understanding Feature Learning in Out-of-Distribution Generalization
A common explanation for the failure of out-of-distribution (OOD) genera...
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04/06/2023
SketchFFusion: Sketch-guided image editing with diffusion model
Sketch-guided image editing aims to achieve local fine-tuning of the ima...
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03/24/2023
Hard Sample Matters a Lot in Zero-Shot Quantization
Zero-shot quantization (ZSQ) is promising for compressing and accelerati...
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03/23/2023
Robust Generalization against Photon-Limited Corruptions via Worst-Case Sharpness Minimization
Robust generalization aims to tackle the most challenging data distribut...
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03/09/2023
Out-of-distribution Detection with Implicit Outlier Transformation
Outlier exposure (OE) is powerful in out-of-distribution (OOD) detection...
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03/04/2023
Exploit CAM by itself: Complementary Learning System for Weakly Supervised Semantic Segmentation
Weakly Supervised Semantic Segmentation (WSSS) with image-level labels h...
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03/04/2023
Federated Semi-Supervised Learning with Annotation Heterogeneity
Federated Semi-Supervised Learning (FSSL) aims to learn a global model f...
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03/01/2023
Combating Exacerbated Heterogeneity for Robust Models in Federated Learning
Privacy and security concerns in real-world applications have led to the...
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02/19/2023
Latent Class-Conditional Noise Model
Learning with noisy labels has become imperative in the Big Data era, wh...
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02/17/2023
Towards Zero-trust Security for the Metaverse
By focusing on immersive interaction among users, the burgeoning Metaver...
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01/31/2023
Zero3D: Semantic-Driven Multi-Category 3D Shape Generation
Semantic-driven 3D shape generation aims to generate 3D objects conditio...
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01/22/2023
Dance2MIDI: Dance-driven multi-instruments music generation
Dance-driven music generation aims to generate musical pieces conditione...
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11/23/2022
NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension
One-shot neural architecture search (NAS) substantially improves the sea...
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11/01/2022
Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks
Adversarial training (AT) with imperfect supervision is significant but ...
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10/26/2022
Is Out-of-Distribution Detection Learnable?
Supervised learning aims to train a classifier under the assumption that...
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10/04/2022
Strength-Adaptive Adversarial Training
Adversarial training (AT) is proved to reliably improve network's robust...
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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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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...
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07/25/2022
Improving Adversarial Robustness via Mutual Information Estimation
Deep neural networks (DNNs) are found to be vulnerable to adversarial no...
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07/15/2022
FRAS: Federated Reinforcement Learning empowered Adaptive Point Cloud Video Streaming
Point cloud video transmission is challenging due to high encoding/decod...
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07/07/2022
Harnessing Out-Of-Distribution Examples via Augmenting Content and Style
Machine learning models are vulnerable to Out-Of-Distribution (OOD) exam...
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07/07/2022
Device-Cloud Collaborative Recommendation via Meta Controller
On-device machine learning enables the lightweight deployment of recomme...
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06/27/2022
Efficient Private SCO for Heavy-Tailed Data via Clipping
We consider stochastic convex optimization for heavy-tailed data with th...
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06/17/2022
Understanding Robust Overfitting of Adversarial Training and Beyond
Robust overfitting widely exists in adversarial training of deep network...
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06/15/2022
Pareto Invariant Risk Minimization
Despite the success of invariant risk minimization (IRM) in tackling the...
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06/15/2022
Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack
The AutoAttack (AA) has been the most reliable method to evaluate advers...
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06/11/2022
Bilateral Dependency Optimization: Defending Against Model-inversion Attacks
Through using only a well-trained classifier, model-inversion (MI) attac...
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06/06/2022
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning
In federated learning (FL), model performance typically suffers from cli...
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06/06/2022
Instance-Dependent Label-Noise Learning with Manifold-Regularized Transition Matrix Estimation
In label-noise learning, estimating the transition matrix has attracted ...
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06/04/2022
MSR: Making Self-supervised learning Robust to Aggressive Augmentations
Most recent self-supervised learning methods learn visual representation...
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05/30/2022
Learning Adaptive Propagation for Knowledge Graph Reasoning
Due to the success of Graph Neural Networks (GNNs) in learning from grap...
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05/30/2022
Robust Weight Perturbation for Adversarial Training
Overfitting widely exists in adversarial robust training of deep network...
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05/27/2022
Counterfactual Fairness with Partially Known Causal Graph
Fair machine learning aims to avoid treating individuals or sub-populati...
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05/25/2022
Contrastive Learning with Boosted Memorization
Self-supervised learning has achieved a great success in the representat...
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05/20/2022