IJCAI 2024

1,048 papers

Delocate: Detection and Localization for Deepfake Videos with Randomly-Located Tampered Traces

Juan Hu, Xin Liao, Difei Gao, Satoshi Tsutsui, Qian Wang

Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activations

Nima Hosseini Dashtbayaz, Ghazal Farhani, Boyu Wang, Charles X. Ling

Dynamicity-aware Social Bot Detection with Dynamic Graph Transformers

Buyun He, Yingguang Yang, Qi Wu, Hao Liu, Renyu Yang

InstructME: An Instruction Guided Music Edit Framework with Latent Diffusion Models

Bing Han, Junyu Dai, Weituo Hao, Xinyan He, Dong Guo

Enhancing Fine-Grained Urban Flow Inference via Incremental Neural Operator

Qiang Gao, Xiaolong Song, Li Huang, Goce Trajcevski, Fan Zhou

VF-Detector: Making Multi-Granularity Code Changes on Vulnerability Fix Detector Robust to Mislabeled Changes

Zhenkan Fu, Shikai Guo, Hui Li, Rong Chen, Xiaochen Li

MMGNN: A Molecular Merged Graph Neural Network for Explainable Solvation Free Energy Prediction

Wenjie Du, SHUAI ZHANG, Di Wu, Jun Xia, Ziyuan Zhao

Linear-Time Optimal Deadlock Detection for Efficient Scheduling in Multi-Track Railway Networks

Hastyn Doshi, Ayush Tripathi, Keshav Agarwal, Harshad Khadilkar, Shivaram Kalyanakrishnan

Geometry-Guided Conditional Adaptation for Surrogate Models of Large-Scale 3D PDEs on Arbitrary Geometries

Jingyang Deng, Xingjian Li, Haoyi Xiong, Xiaoguang Hu, Jinwen Ma

Shadow-Free Membership Inference Attacks: Recommender Systems Are More Vulnerable Than You Thought

Xiaoxiao Chi, Xuyun Zhang, Yan Wang, Lianyong Qi, Amin Beheshti

Federated Prompt Learning for Weather Foundation Models on Devices

Shengchao Chen, Guodong Long, Tao Shen, Jing Jiang, Chengqi Zhang

Predictive Modeling with Temporal Graphical Representation on Electronic Health Records

Jiayuan Chen, Changchang Yin, Yuanlong Wang, Ping Zhang

Balancing Multimodal Learning via Online Logit Modulation

Daoming Zong, Chaoyue Ding, Baoxiang Li, Jiakui Li, Ken Zheng

PrivSGP-VR: Differentially Private Variance-Reduced Stochastic Gradient Push with Tight Utility Bounds

Zehan Zhu, Yan Huang, Xin Wang, Jinming Xu

Efficient Tuning and Inference for Large Language Models on Textual Graphs

Yun Zhu, Yaoke Wang, Haizhou Shi, Siliang Tang

vMFER: Von Mises-Fisher Experience Resampling Based on Uncertainty of Gradient Directions for Policy Improvement

Yiwen Zhu, Jinyi Liu, Wenya Wei, Qianyi Fu, Yujing Hu

FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning

Yinlin Zhu, Xunkai Li, Zhengyu Wu, Di Wu, Miao Hu

AnchorGT: Efficient and Flexible Attention Architecture for Scalable Graph Transformers

Wenhao Zhu, Guojie Song, Liang Wang, ShaoGuo Liu

Towards Sharper Risk Bounds for Minimax Problems

Bowei Zhu, Shaojie Li, Yong Liu

SDformer: Transformer with Spectral Filter and Dynamic Attention for Multivariate Time Series Long-term Forecasting

Ziyu Zhou, Gengyu Lyu, Yiming Huang, Zihao Wang, Ziyu Jia

Rethinking Centered Kernel Alignment in Knowledge Distillation

Zikai Zhou, Yunhang Shen, Shitong Shao, Linrui Gong, Shaohui Lin

Large Language Model as a Policy Teacher for Training Reinforcement Learning Agents

Zihao Zhou, Bin Hu, Chenyang Zhao, Pu Zhang, Bin Liu

Learning in CubeRes Model Space for Anomaly Detection in 3D GPR Data

Xiren Zhou, Shikang Liu, Ao Chen, Huanhuan Chen

Boosting Model Resilience via Implicit Adversarial Data Augmentation

Xiaoling Zhou, Wei Ye, Zhemg Lee, Rui Xie, Shikun Zhang

Denoising-Aware Contrastive Learning for Noisy Time Series

Shuang Zhou, Daochen Zha, Xiao Shen, Xiao Huang, Rui Zhang

Delve into Base-Novel Confusion: Redundancy Exploration for Few-Shot Class-Incremental Learning

Haichen Zhou, Yixiong Zou, Ruixuan Li, Yuhua Li, Kui Xiao

SCAT: A Time Series Forecasting with Spectral Central Alternating Transformers

Chengjie Zhou, Chao Che, pengfei wang, Qiang Zhang

Cross-View Contrastive Fusion for Enhanced Molecular Property Prediction

YAN ZHENG, Song Wu, Junyu Lin, Yazhou Ren, Jing He

Constrained Intrinsic Motivation for Reinforcement Learning

Xiang Zheng, Xingjun Ma, Chao Shen, Cong Wang

Learning Robust Classifiers with Self-Guided Spurious Correlation Mitigation

Guangtao Zheng, Wenqian Ye, Aidong Zhang

Protecting Split Learning by Potential Energy Loss

Fei Zheng, Chaochao Chen, Lingjuan Lyu, Xinyi Fu, Xing Fu

Towards Robust Multi-Label Learning against Dirty Label Noise

Yuhai Zhao, Yejiang Wang, Zhengkui Wang, Wen Shan, Miaomiao Huang

NanoAdapt: Mitigating Negative Transfer in Test Time Adaptation with Extremely Small Batch Sizes

Shiji Zhao, Shao-Yuan Li, Sheng-jun Huang

ENOTO: Improving Offline-to-Online Reinforcement Learning with Q-Ensembles

KAI ZHAO, Jianye Hao, Yi Ma, Jinyi Liu, YAN ZHENG

Active Deep Multi-view Clustering

Helin Zhao, Wei Chen, Peng Zhou

Reconfigurability-Aware Selection for Contrastive Active Domain Adaptation

Zeyu Zhang, Chun Shen, Shuai Lu, Shaojie Zhang

Pre-training General User Representation with Multi-type APP Behaviors

Yuren Zhang, Min Hou, Kai Zhang, Yuqing Yuan, Chao Song

Personalized Federated Learning for Cross-City Traffic Prediction

Yu Zhang, Hua Lu, Ning Liu, Yonghui Xu, Qingzhong Li

Visual Attention Prompted Prediction and Learning

Yifei Zhang, Bo Pan, Siyi Gu, Guangji Bai, Meikang Qiu

Fine-grained Analysis of Stability and Generalization for Stochastic Bilevel Optimization

Xuelin Zhang, Hong Chen, Bin Gu, Tieliang Gong, Feng Zheng

Skip-Timeformer: Skip-Time Interaction Transformer for Long Sequence Time-Series Forecasting

Wenchang Zhang, Hua Wang, Fan Zhang

Exploring Cross-Domain Few-Shot Classification via Frequency-Aware Prompting

Tiange Zhang, Qing Cai, Feng Gao, Lin Qi, Junyu Dong

CONC: Complex-noise-resistant Open-set Node Classification with Adaptive Noise Detection

Qin Zhang, Jiexin Lu, Xiaowei Li, Huisi Wu, Shirui Pan

Learning from Long-Tailed Noisy Data with Sample Selection and Balanced Loss

Lefan Zhang, Zhang-Hao Tian, Wujun Zhou, Wei Wang

LSPAN: Spectrally Localized Augmentation for Graph Consistency Learning

Heng-Kai Zhang, Yi-Ge Zhang, Zhi Zhou, Yu-feng Li

Federated Adaptation for Foundation Model-based Recommendations

Chunxu Zhang, Guodong Long, Hongkuan Guo, Xiao Fang, Yang Song

Efficient Multi-view Unsupervised Feature Selection with Adaptive Structure Learning and Inference

Chenglong Zhang, Yang Fang, Xinyan Liang, Han Zhang, Peng Zhou

Continual Multi-View Clustering with Consistent Anchor Guidance

Chao Zhang, Deng Xu, Xiuyi Jia, Chunlin Chen, Huaxiong Li

Task-Agnostic Self-Distillation for Few-Shot Action Recognition

Bin Zhang, Yuanjie Dang, Peng Chen, Ronghua Liang, Nan Gao

FedES: Federated Early-Stopping for Hindering Memorizing Heterogeneous Label Noise

Bixiao Zeng, Xiaodong Yang, Yiqiang Chen, Zhiqi Shen, Hanchao Yu

BoostDream: Efficient Refining for High-Quality Text-to-3D Generation from Multi-View Diffusion

Yonghao Yu, Shunan Zhu, Huai Qin, Haorui Li

Bandits with Concave Aggregated Reward

Yingqi Yu, Sijia Zhang, Shaoang Li, Lan Zhang, Wei Xie

EC-SNN: Splitting Deep Spiking Neural Networks for Edge Devices

Di Yu, Xin Du, Linshan Jiang, Wentao Tong, Shuiguang Deng

Pointsoup: High-Performance and Extremely Low-Decoding-Latency Learned Geometry Codec for Large-Scale Point Cloud Scenes

Kang You, Kai Liu, Li Yu, Pan Gao, Dandan Ding

FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning

Liping Yi, Han Yu, Zhuan Shi, Gang Wang, Xiaoguang Liu

Bridging the Gap: Learning Pace Synchronization for Open-World Semi-Supervised Learning

Bo Ye, Kai Gan, Tong Wei, Min-ling Zhang

A Deep Probabilistic Spatiotemporal Framework for Dynamic Graph Representation Learning with Application to Brain Disorder Identification

Sin-Yee Yap, Junn Yong Loo, Chee-Ming Ting, Fuad Noman, Raphael C.-W. Phan

Boosting Efficiency in Task-Agnostic Exploration through Causal Knowledge

Yupei Yang, Biwei Huang, Shikui Tu, Lei Xu

VCformer: Variable Correlation Transformer with Inherent Lagged Correlation for Multivariate Time Series Forecasting

Yingnan Yang, Qingling Zhu, Jianyong Chen

Navigating Continual Test-time Adaptation with Symbiosis Knowledge

Xu Yang, Moqi Li, Jie Yin, Kun Wei, Cheng Deng

Approximate Algorithms for k-Sparse Wasserstein Barycenter with Outliers

Qingyuan Yang, Hu Ding

Dynamic against Dynamic: An Open-Set Self-Learning Framework

Haifeng Yang, Chuanxing Geng, Pong C. Yuen, Songcan Chen

Reinforcement Learning from Diverse Human Preferences

Wanqi Xue, Bo An, Shuicheng Yan, Zhongwen Xu

FBLG: A Local Graph Based Approach for Handling Dual Skewed Non-IID Data in Federated Learning

Yi Xu, Ying Li, Haoyu Luo, Xiaoliang Fan, Xiao Liu

FedFa: A Fully Asynchronous Training Paradigm for Federated Learning

Haotian Xu, Zhaorui Zhang, Sheng Di, Benben Liu, Khalid Ayed Alharthi

Minimizing Weighted Counterfactual Regret with Optimistic Online Mirror Descent

Hang Xu, Kai Li, Bingyun Liu, Haobo Fu, Qiang Fu

Trusted Multi-view Learning with Label Noise

Cai Xu, Yilin Zhang, Ziyu Guan, Wei Zhao

Exploring Learngene via Stage-wise Weight Sharing for Initializing Variable-sized Models

Shi-Yu Xia, Wenxuan Zhu, Xu Yang, Xin Geng

AllMatch: Exploiting All Unlabeled Data for Semi-Supervised Learning

Zhiyu Wu, Jinshi Cui

Large Language Model-Enhanced Algorithm Selection: Towards Comprehensive Algorithm Representation

Xingyu Wu, Yan Zhong, Jibin Wu, Bingbing Jiang, Kay Chen Tan

TAI++: Text as Image for Multi-Label Image Classification by Co-Learning Transferable Prompt

Xiangyu Wu, Qing-Yuan Jiang, Yang Yang, Yi-Feng Wu, Qing-Guo Chen

Synthesizing Programmatic Policy for Generalization within Task Domain

Tianyi Wu, Liwei Shen, Zhen Dong, Xin Peng, Wenyun Zhao

PACIA: Parameter-Efficient Adapter for Few-Shot Molecular Property Prediction

Shiguang Wu, Yaqing Wang, Quanming Yao

From Optimization to Generalization: Fair Federated Learning against Quality Shift via Inter-Client Sharpness Matching

Nannan Wu, Zhuo Kuang, Zengqiang Yan, Li Yu

Towards Sharper Generalization Bounds for Adversarial Contrastive Learning

Wen Wen, Han Li, Tieliang Gong, Hong Chen

PDENNEval: A Comprehensive Evaluation of Neural Network Methods for Solving PDEs

Ping Wei, Menghan Liu, Jianhuan Cen, Ziyang Zhou, Liao Chen

Cross-Talk Reduction

Zhong-Qiu Wang, Anurag Kumar, Shinji Watanabe

Nonconvex Multiview Subspace Clustering Framework with Efficient Method Designs and Theoretical Analysis

Zhi Wang, Zhuo Liu, Dong Hu, Tao Jia

Subgraph Pooling: Tackling Negative Transfer on Graphs

Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye

Atomic Recovery Property for Multi-view Subspace-Preserving Recovery

Yulong Wang

Self-adaptive Extreme Penalized Loss for Imbalanced Time Series Prediction

Yiyang Wang, Yuchen Han, Yuhan Guo

Scale and Direction Guided GAN for Inertial Sensor Signal Enhancement

Yifeng Wang, Yi Zhao

Self-Supervised Learning for Enhancing Spatial Awareness in Free-Hand Sketches

Xin Wang, Tengjie Li, Sicong Zang, Shikui Tu, Lei Xu

Joint Input and Output Coordination for Class-Incremental Learning

Shuai Wang, Yibing Zhan, Yong Luo, Han Hu, Wei Yu

A Grassmannian Manifold Self-Attention Network for Signal Classification

Rui Wang, Chen Hu, Ziheng Chen, Xiao-Jun Wu, Xiaoning Song

Reconstruction Weighting Principal Component Analysis with Fusion Contrastive Learning

Qianqian Wang, Meiling Liu, Wei Feng, Mengping Jiang, Haiming Xu

Finite-Time Convergence Rates of Decentralized Local Markovian Stochastic Approximation

pengfei wang, Nenggan Zheng

Strengthening Layer Interaction via Dynamic Layer Attention

Kaishen Wang, Xun Xia, Jian Liu, Zhang Yi, Tao He

Hacking Task Confounder in Meta-Learning

Jingyao Wang, Yi Ren, Zeen Song, Jianqi Zhang, Changwen Zheng

Contrastive and View-Interaction Structure Learning for Multi-view Clustering

Jing Wang, Songhe Feng

MOSER: Learning Sensory Policy for Task-specific Viewpoint via View-conditional World Model

Shenghua Wan, Hai-Hang Sun, Le Gan, De-Chuan Zhan

Interpretable Tensor Fusion

Saurabh Varshneya, Antoine Ledent, Philipp Liznerski, Andriy Balinskyy, Purvanshi Mehta

Proximal Curriculum with Task Correlations for Deep Reinforcement Learning

Georgios Tzannetos, Parameswaran Kamalaruban, Adish Singla

Enabling Mixed Effects Neural Networks for Diverse, Clustered Data Using Monte Carlo Methods

Andrej Tschalzev, Paul Nitschke, Lukas Kirchdorfer, Stefan Lüdtke, Christian Bartelt

Redefining Contributions: Shapley-Driven Federated Learning

Nurbek Tastan, Samar Fares, Toluwani Aremu, Samuel Horváth, Karthik Nandakumar

Unlearning from Weakly Supervised Learning

Yi Tang, Yi Gao, Yong-gang Luo, Ju-Cheng Yang, Miao Xu

A Bias-Free Revenue-Maximizing Bidding Strategy for Data Consumers in Auction-based Federated Learning

Xiaoli Tang, Han Yu, Zengxiang Li, Xiaoxiao Li

Dual Calibration-based Personalised Federated Learning

Xiaoli Tang, Han Yu, Run Tang, Chao Ren, Anran Li

Exploiting Conjugate Label Information for Multi-Instance Partial-Label Learning

Wei Tang, Weijia Zhang, Min-ling Zhang

Deep Hierarchical Graph Alignment Kernels

Shuhao Tang, Hao Tian, Xiaofeng Cao, Wei Ye