AAAI 2025

3,486 papers

ADELA: Accelerating Evolutionary Design of Machine Learning Pipelines with the Accompanying Surrogate Model

Yang Gu, Jian Cao, Hengyu You, Nengjun Zhu, Shiyou Qian

On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems

Alessio Gravina, Moshe Eliasof, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb

Deep Representation Learning for Forecasting Recursive and Multi-Relational Events in Temporal Networks

Tony Gracious, Ambedkar Dukkipati

Neural Temporal Point Processes for Forecasting Directional Relations in Evolving Hypergraphs

Tony Gracious, Arman Gupta, Ambedkar Dukkipati

Offline Safe Reinforcement Learning Using Trajectory Classification

Ze Gong, Akshat Kumar, Pradeep Varakantham

Efficient Graph Bandit Learning with Side-Observations and Switching Constraints

Xueping Gong, Jiheng Zhang

Conformal Prediction for Partial Label Learning

Xiuwen Gong, Nitin Bisht, Guandong Xu

DivGCL: A Graph Contrastive Learning Model for Diverse Recommendation

Wenwen Gong, Yangliao Geng, Dan Zhang, Yifan Zhu, Xiaolong Xu

Evolutionary Large Language Model for Automated Feature Transformation

Nanxu Gong, Chandan K Reddy, Wangyang Ying, Haifeng Chen, Yanjie Fu

Out-of-Distribution Detection with Prototypical Outlier Proxy

Mingrong Gong, Chaoqi Chen, Qingqiang Sun, Yue Wang, Hui Huang

An Optimal Transport-based Latent Mixer for Robust Multi-modal Learning

Fengjiiao Gong, Angxiao Yue, Hongteng Xu

Queries, Representation & Detection: The Next 100 Model Fingerprinting Schemes

Augustin Godinot, Erwan Le Merrer, Camilla Penzo, Francois Taiani, Gilles Tredan

Auditing and Enforcing Conditional Fairness via Optimal Transport

Mohsen Ghassemi, Alan Mishler, Niccolò Dalmasso, Luhao Zhang, Vamsi K. Potluru

Learning Physics Informed Neural ODEs with Partial Measurements

Paul Ghanem, Ahmet Demirkaya, Tales Imbiriba, Alireza Ramezani, Zachary Danziger

Personalized Clustering via Targeted Representation Learning

Xiwen Geng, Suyun Zhao, Yixin Yu, Borui Peng, Pan Du

CiTrus: Squeezing Extra Performance out of Low-data Bio-signal Transfer Learning

Eloy Geenjaar, Lie Lu

Extracting Interpretable Task-Specific Circuits from Large Language Models for Faster Inference

Jorge García-Carrasco, Alejandro Maté, Juan Trujillo

Maintaining Fairness in Logit-based Knowledge Distillation for Class-Incremental Learning

Zijian Gao, Shanhao Han, Xingxing Zhang, Kele Xu, Dulan Zhou

Asymmetric Reinforcing Against Multi-Modal Representation Bias

Xiyuan Gao, Bing Cao, Pengfei Zhu, Nannan Wang, Qinghua Hu

FLUE: Streamlined Uncertainty Estimation for Large Language Models

Shiqi Gao, Tianxiang Gong, Zijie Lin, Runhua Xu, Haoyi Zhou

Multimodal Fusion Using Multi-View Domains for Data Heterogeneity in Federated Learning

Min Gao, Haifeng Zheng, Xinxin Feng, Ran Tao

Auto-Regressive Moving Diffusion Models for Time Series Forecasting

Jiaxin Gao, Qinglong Cao, Yuntian Chen

Bootstrapping Heterogeneous Graph Representation Learning via Large Language Models: A Generalized Approach

Hang Gao, Chenhao Zhang, Fengge Wu, Changwen Zheng, Junsuo Zhao

QuARF: Quality-Adaptive Receptive Fields for Degraded Image Perception

Fei Gao, Ying Zhou, Ziyun Li, Wenwang Han, Jiaqi Shi

Scalable Decentralized Algorithms for Online Personalized Mean Estimation

Franco Galante, Giovanni Neglia, Emilio Leonardi

Accurate Estimation of Feature Importance Faithfulness for Tree Models

Mateusz Gajewski, Adam Karczmarz, Mateusz Rapicki, Piotr Sankowski

HYGENE: A Diffusion-Based Hypergraph Generation Method

Dorian Gailhard, Enzo Tartaglione, Lirida Naviner, Jhony H. Giraldo

Bi-Directional Multi-Scale Graph Dataset Condensation via Information Bottleneck

Xingcheng Fu, Yisen Gao, Beining Yang, Yuxuan Wu, Haodong Qian

Discrete Curvature Graph Information Bottleneck

Xingcheng Fu, Jian Wang, Yisen Gao, Qingyun Sun, Haonan Yuan

Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph Learning

Xingbo Fu, Zihan Chen, Yinhan He, Song Wang, Binchi Zhang

Beyond Federated Prototype Learning: Learnable Semantic Anchors with Hyperspherical Contrast for Domain-Skewed Data

Lele Fu, Sheng Huang, Yanyi Lai, Tianchi Liao, Chuanfu Zhang

Frequency-Masked Embedding Inference: A Non-Contrastive Approach for Time Series Representation Learning

En Fu, Yanyan Hu

A Unifying Information-theoretic Perspective on Evaluating Generative Models

Alexis Fox, Samarth Swarup, Abhijin Adiga

Universality of Real Minimal Complexity Reservoir

Robert Simon Fong, Boyu Li, Peter Tino

Incremental Nyström-based Multiple Kernel Clustering

Yu Feng, Weixuan Liang, Xinhang Wan, Jiyuan Liu, Suyuan Liu

DUO: Diverse, Uncertain, On-Policy Query Generation and Selection for Reinforcement Learning from Human Feedback

Xuening Feng, Zhaohui Jiang, Timo Kaufmann, Puchen Xu, Eyke Hüllermeier

MPQ-DM: Mixed Precision Quantization for Extremely Low Bit Diffusion Models

Weilun Feng, Haotong Qin, Chuanguang Yang, Zhulin An, Libo Huang

Scalable Federated One-Step Multi-View Clustering with Tensorized Regularization

Wei Feng, Danting Liu, Qianqian Wang, Wenqi Liang, Zheng Yan

Learning Nash Equilibrium of Markov Potential Games with a Shared Constraint via Primal-Dual Optimization

Songtao Feng, Michael Dorothy, Jie Fu

SADBA: Self-Adaptive Distributed Backdoor Attack Against Federated Learning

Jun Feng, Yuzhe Lai, Hong Sun, Bocheng Ren

An Item Is Worth a Prompt: Versatile Image Editing with Disentangled Control

Aosong Feng, Weikang Qiu, Jinbin Bai, Zhen Dong, Kaicheng Zhou

OmniMark: Efficient and Scalable Latent Diffusion Model Fingerprinting

Jianwei Fei, Yunshu Dai, Zhihua Xia, Fangjun Huang, Jiantao Zhou

Rapid Learning in Constrained Minimax Games with Negative Momentum

Zijian Fang, Zongkai Liu, Chao Yu, Chaohao Hu

Boosting Fine-Grained Visual Anomaly Detection with Coarse-Knowledge-Aware Adversarial Learning

Qingqing Fang, Qinliang Su, Wenxi Lv, Wenchao Xu, Jianxing Yu

3SAT: A Simple Self-Supervised Adversarial Training Framework

Jiang Fang, Haonan He, Jiyan Sun, Jiadong Fu, Zhaorui Guo

Large Language Models Enhanced Personalized Graph Neural Architecture Search in Federated Learning

Hui Fang, Yang Gao, Peng Zhang, Jiangchao Yao, Hongyang Chen

Towards Efficient Collaboration via Graph Modeling in Reinforcement Learning

Wenzhe Fan, Zishun Yu, Chengdong Ma, Changye Li, Yaodong Yang

Deep Generative Model for Mechanical System Configuration Design

Yasaman Etesam, Hyunmin Cheong, Mohammadmehdi Ataei, Pradeep Kumar Jayaraman

Free Lunch in the Forest: Functionally-Identical Pruning of Boosted Tree Ensembles

Youssouf Emine, Alexandre Forel, Idriss Malek, Thibaut Vidal

Causal Discovery by Interventions via Integer Programming

Abdelmonem Elrefaey, Rong Pan

Learning Regularization for Graph Inverse Problems

Moshe Eliasof, Md Shahriar Rahim Siddiqui, Carola-Bibiane Schönlieb, Eldad Haber

Designing Ambiguity Sets for Distributionally Robust Optimization Using Structural Causal Optimal Transport

Ahmad Reza Ehyaei, Golnoosh Farnadi, Samira Samadi

OAC: Output-adaptive Calibration for Accurate Post-training Quantization

Ali Edalati, Alireza Ghaffari, Mahsa Ghazvini Nejad, Lu Hou, Boxing Chen

Linking Industry Sectors and Financial Statements: A Hybrid Approach for Company Classification

Guy Stephane Waffo Dzuyo, Gaël Guibon, Christophe Cerisara, Luis Belmar-Letelier

Proportionally Fair Matching via Randomized Rounding

Sharmila Duppala, Nathaniel Grammel, Juan Luque, Calum MacRury, Aravind Srinivasan

Sweeping Heterogeneity with Smart MoPs: Mixture of Prompts for LLM Task Adaptation

Chen Dun, Mirian Del Carmen Hipolito Garcia, Guoqing Zheng, Ahmed Hassan Awadallah, Robert Sim

Active Reinforcement Learning Strategies for Offline Policy Improvement

Ambedkar Dukkipati, Ranga Shaarad Ayyagari, Bodhisattwa Dasgupta, Parag Dutta, Prabhas Reddy Onteru

Information-Theoretic Generative Clustering of Documents

Xin Du, Kumiko Tanaka-Ishii

Contrastive Auxiliary Learning with Structure Transformation for Heterogeneous Graphs

Wei Du, Hongmin Sun, Hang Gao, Gaoyang Li, Ying Li

OpenViewer: Openness-Aware Multi-View Learning

Shide Du, Zihan Fang, Yanchao Tan, Changwei Wang, Shiping Wang

Sharper Error Bounds in Late Fusion Multi-view Clustering with Eigenvalue Proportion Optimization

Liang Du, Henghui Jiang, Xiaodong Li, Yiqing Guo, Yan Chen

Rebalancing Multi-Label Class-Incremental Learning

Kaile Du, Yifan Zhou, Fan Lyu, Yuyang Li, Junzhou Xie

On the Hardness of Training Deep Neural Networks Discretely

Ilan Doron-Arad

AtomNet: Designing Tiny Models from Operators Under Extreme MCU Constraints

Zhiwei Dong, Mingzhu Shen, Shihao Bai, Xiuying Wei, Jinyang Guo

DCILP: A Distributed Approach for Large-Scale Causal Structure Learning

Shuyu Dong, Michele Sebag, Kento Uemura, Akito Fujii, Shuang Chang

Beyond Mandatory Federations: Balancing Egoism, Utilitarianism and Egalitarianism in Mixed-Motive Games

Shaokang Dong, CHAO LI, Shangdong Yang, Hongye Cao, Wanqi Yang

ParZC: Parametric Zero-Cost Proxies for Efficient NAS

Peijie Dong, Lujun Li, Zhenheng Tang, Xiang Liu, Zimian Wei

Combining Priors with Experience: Confidence Calibration Based on Binomial Process Modeling

Jinzong Dong, Zhaohui Jiang, Dong Pan, Haoyang Yu

Towards Unifying Evaluation of Counterfactual Explanations: Leveraging Large Language Models for Human-Centric Assessments

Marharyta Domnich, Julius Välja, Rasmus Moorits Veski, Giacomo Magnifico, Kadi Tulver

Bayesian Low-Rank Learning (Bella): A Practical Approach to Bayesian Neural Networks

Bao Gia Doan, Afshar Shamsi, Xiao-Yu Guo, Arash Mohammadi, Hamid Alinejad-Rokny

Architecture-Aware Learning Curve Extrapolation via Graph Ordinary Differential Equation

Yanna Ding, Zijie Huang, Xiao Shou, Yihang Guo, Yizhou Sun

How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning?

Wenjun Ding, Ying An, Lixing Chen, Shichao Kan, Fan Wu

Attribute Inference Attacks for Federated Regression Tasks

Francesco Diana, Othmane MARFOQ, CHUAN XU, Giovanni Neglia, Frédéric Giroire

The Surprising Effectiveness of Infinite-Width NTKs for Characterizing and Improving Model Training

Joshua DeOliveira, Walter Gerych, Elke Rundensteiner

Enhancing Multimodal Affective Analysis with Learned Live Comment Features

Zhaoyuan Deng, Amith Ananthram, Kathleen McKeown

Enhancing Online Reinforcement Learning with Meta-Learned Objective from Offline Data

Shilong Deng, Zetao Zheng, Hongcai He, Paul Weng, Jie Shao

Learning to Generate Gradients for Test-Time Adaptation via Test-Time Training Layers

Qi Deng, Shuaicheng Niu, Ronghao Zhang, Yaofo Chen, Runhao Zeng

VQ4DiT: Efficient Post-Training Vector Quantization for Diffusion Transformers

Juncan Deng, Shuaiting Li, Zeyu Wang, Hong Gu, Kedong Xu

Expected Hypervolume Improvement Is a Particular Hypervolume Improvement

Jingda Deng, Jianyong Sun, Qingfu Zhang, Hui Li

Asymptotic Unbiased Sample Sampling to Speed Up Sharpness-Aware Minimization

Jiaxin Deng, Junbiao Pang, Baochang Zhang, Guodong Guo

THESAURUS: Contrastive Graph Clustering by Swapping Fused Gromov-Wasserstein Couplings

Bowen Deng, Tong Wang, Lele Fu, Sheng Huang, Chuan Chen

Stochastic Online Instrumental Variable Regression: Regrets for Endogeneity and Bandit Feedback

Riccardo Della Vecchia, Debabrota Basu

Relational Neurosymbolic Markov Models

Lennert De Smet, Gabriele Venturato, Luc De Raedt, Giuseppe Marra

OneBatchPAM: A Fast and Frugal K-Medoids Algorithm

Antoine de Mathelin, Nicolas Enrique Cecchi, François Deheeger, Mathilde Mougeot, Nicolas Vayatis

CAGE: Unsupervised Visual Composition and Animation for Controllable Video Generation

Aram Davtyan, Sepehr Sameni, Bjorn Ommer, Paolo Favaro

Skill Disentanglement in Reproducing Kernel Hilbert Space

Vedant Dave, Elmar Rueckert

Federated Binary Matrix Factorization Using Proximal Optimization

Sebastian Dalleiger, Jilles Vreeken, Michael Kamp

Creating Coherence in Federated Non-Negative Matrix Factorization

Sebastian Dalleiger, Aristides Gionis

Synthetic Tabular Data Generation for Imbalanced Classification: The Surprising Effectiveness of an Overlap Class

Annie D'souza, Swetha M, Sunita Sarawagi

Few-Shot Audio-Visual Class-Incremental Learning with Temporal Prompting and Regularization

Yawen Cui, Li Liu, Zitong Yu, Guanjie Huang, Xiaopeng Hong

Neural Variable-Order Fractional Differential Equation Networks

Wenjun Cui, Qiyu Kang, Xuhao Li, KAI ZHAO, Wee Peng Tay

Fangming Cui, Jan Fong, Rongfei Zeng, Xinmei Tian, Jun Yu

Probabilistic Shielding for Safe Reinforcement Learning

Edwin Hamel-De le Court, Francesco Belardinelli, Alexander W. Goodall

Generalized Dimension Reduction Using Semi-Relaxed Gromov-Wasserstein Distance

Ranthony A. Clark, Tom Needham, Thomas Weighill

Cross-Validated Off-Policy Evaluation

Matej Cief, Branislav Kveton, Michal Kompan

Rethinking the Starting Point: Collaborative Pre-Training for Federated Downstream Tasks

Yun-Wei Chu, Dong-Jun Han, Seyyedali Hosseinalipour, Christopher G. Brinton

Deep Implicit Imitation Reinforcement Learning in Heterogeneous Action Settings

Iason Chrysomallis, Georgios Chalkiadakis, Ioannis Papamichail, Markos Papageorgiou

ZeroHAR: Sensor Context Augments Zero-Shot Wearable Action Recognition

Ranak Roy Chowdhury, Ritvik Kapila, Ameya Panse, Xiyuan Zhang, Diyan Teng

MimiQ: Low-Bit Data-Free Quantization of Vision Transformers with Encouraging Inter-Head Attention Similarity

Kanghyun Choi, Hyeyoon Lee, Dain Kwon, SunJong Park, Kyuyeun Kim

Unveiling the Threat of Fraud Gangs to Graph Neural Networks: Multi-Target Graph Injection Attacks Against GNN-Based Fraud Detectors

Jinhyeok Choi, Heehyeon Kim, Joyce Jiyoung Whang