Most Cited AAAI "neural integral process" Papers
5,317 papers found • Page 20 of 27
Conference
Contrastive Auxiliary Learning with Structure Transformation for Heterogeneous Graphs
Wei Du, Hongmin Sun, Hang Gao et al.
Active Reinforcement Learning Strategies for Offline Policy Improvement
Ambedkar Dukkipati, Ranga Shaarad Ayyagari, Bodhisattwa Dasgupta et al.
Sweeping Heterogeneity with Smart MoPs: Mixture of Prompts for LLM Task Adaptation
Chen Dun, Mirian Del Carmen Hipolito Garcia, Guoqing Zheng et al.
Proportionally Fair Matching via Randomized Rounding
Sharmila Duppala, Nathaniel Grammel, Juan Luque et al.
Linking Industry Sectors and Financial Statements: A Hybrid Approach for Company Classification
Guy Stephane Waffo Dzuyo, Gaël Guibon, Christophe Cerisara et al.
OAC: Output-adaptive Calibration for Accurate Post-training Quantization
Ali Edalati, Alireza Ghaffari, Mahsa Ghazvini Nejad et al.
Designing Ambiguity Sets for Distributionally Robust Optimization Using Structural Causal Optimal Transport
Ahmad Reza Ehyaei, Golnoosh Farnadi, Samira Samadi
Deep Generative Model for Mechanical System Configuration Design
Yasaman Etesam, Hyunmin Cheong, Mohammadmehdi Ataei et al.
Towards Efficient Collaboration via Graph Modeling in Reinforcement Learning
Wenzhe Fan, Zishun Yu, Chengdong Ma et al.
Large Language Models Enhanced Personalized Graph Neural Architecture Search in Federated Learning
Hui Fang, Yang Gao, Peng Zhang et al.
3SAT: A Simple Self-Supervised Adversarial Training Framework
Jiang Fang, Haonan He, Jiyan Sun et al.
Rapid Learning in Constrained Minimax Games with Negative Momentum
Zijian Fang, Zongkai Liu, Chao Yu et al.
Learning Nash Equilibrium of Markov Potential Games with a Shared Constraint via Primal-Dual Optimization
Songtao Feng, Michael Dorothy, Jie Fu
Scalable Federated One-Step Multi-View Clustering with Tensorized Regularization
Wei Feng, Danting Liu, Qianqian Wang et al.
MPQ-DM: Mixed Precision Quantization for Extremely Low Bit Diffusion Models
Weilun Feng, Haotong Qin, Chuanguang Yang et al.
Incremental Nyström-based Multiple Kernel Clustering
Yu Feng, Weixuan Liang, Xinhang Wan et al.
A Unifying Information-theoretic Perspective on Evaluating Generative Models
Alexis Fox, Samarth Swarup, Abhijin Adiga
Beyond Federated Prototype Learning: Learnable Semantic Anchors with Hyperspherical Contrast for Domain-Skewed Data
Lele Fu, Sheng Huang, Yanyi Lai et al.
Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph Learning
Xingbo Fu, Zihan Chen, Yinhan He et al.
Accurate Estimation of Feature Importance Faithfulness for Tree Models
Mateusz Gajewski, Adam Karczmarz, Mateusz Rapicki et al.
Scalable Decentralized Algorithms for Online Personalized Mean Estimation
Franco Galante, Giovanni Neglia, Emilio Leonardi
QuARF: Quality-Adaptive Receptive Fields for Degraded Image Perception
Fei Gao, Ying Zhou, Ziyun Li et al.
Multimodal Fusion Using Multi-View Domains for Data Heterogeneity in Federated Learning
Min Gao, Haifeng Zheng, Xinxin Feng et al.
Asymmetric Reinforcing Against Multi-Modal Representation Bias
Xiyuan Gao, Bing Cao, Pengfei Zhu et al.
Maintaining Fairness in Logit-based Knowledge Distillation for Class-Incremental Learning
Zijian Gao, Shanhao Han, Xingxing Zhang et al.
Personalized Clustering via Targeted Representation Learning
Xiwen Geng, Suyun Zhao, Yixin Yu et al.
An Optimal Transport-based Latent Mixer for Robust Multi-modal Learning
Fengjiiao Gong, Angxiao Yue, Hongteng Xu
Conformal Prediction for Partial Label Learning
Xiuwen Gong, Nitin Bisht, Guandong Xu
Efficient Graph Bandit Learning with Side-Observations and Switching Constraints
Xueping Gong, Jiheng Zhang
Offline Safe Reinforcement Learning Using Trajectory Classification
Ze Gong, Akshat Kumar, Pradeep Varakantham
Neural Temporal Point Processes for Forecasting Directional Relations in Evolving Hypergraphs
Tony Gracious, Arman Gupta, Ambedkar Dukkipati
On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems
Alessio Gravina, Moshe Eliasof, Claudio Gallicchio et al.
Heterogeneous Graph Neural Network on Semantic Tree
Mingyu Guan, Jack W Stokes, Qinlong Luo et al.
Enhancing Multivariate Time-Series Domain Adaptation via Contrastive Frequency Graph Discovery and Language-Guided Adversary Alignment
Haoren Guo, Haiyue Zhu, Jiahui Wang et al.
Federated Causally Invariant Feature Learning
Xianjie Guo, Kui Yu, Lizhen Cui et al.
CFDM: Contrastive Fusion and Disambiguation for Multi-View Partial-Label Learning
Qiuru Hai, Yongjian Deng, Yuena Lin et al.
Who’s the (Multi-)Fairest of Them All: Rethinking Interpolation-Based Data Augmentation Through the Lens of Multicalibration
Karina Halevy, Karly Hou, Charumathi Badrinath
DrugHash: Hashing Based Contrastive Learning for Virtual Screening
Jin Han, Yun Hong, Wu-Jun Li
Scalable Acceleration for Classification-Based Derivative-Free Optimization
Tianyi Han, Jingya Li, Zhipeng Guo et al.
Content-aware Balanced Spectrum Encoding in Masked Modeling for Time Series Classification
Yudong Han, Haocong Wang, Yupeng Hu et al.
DCHM: Dynamic Collaboration of Heterogeneous Models Through Isomerism Learning in a Blockchain-Powered Federated Learning Framework
Zhihao Hao, Bob Zhang, Haisheng Li
FedAA: A Reinforcement Learning Perspective on Adaptive Aggregation for Fair and Robust Federated Learning
Jialuo He, Wei Chen, Xiaojin Zhang
Gradient-Based Sample Selection for Black-Box Universal Domain Adaptation
Qiuyan He, Minghua Deng
MARS: Mixture of Auto-Regressive Models for Fine-grained Text-to-image Synthesis
Wanggui He, Siming Fu, Mushui Liu et al.
CAMH: Advancing Model Hijacking Attack in Machine Learning
Xing He, Jiahao Chen, Yuwen Pu et al.
Highly Parallelized Reinforcement Learning Training with Relaxed Assignment Dependencies
Zhouyu He, Peng Qiao, Rongchun Li et al.
Bi-Level Optimization for Semi-Supervised Learning with Pseudo-Labeling
Marzi Heidari, Yuhong Guo
Data Augmentation for Instruction Following Policies via Trajectory Segmentation
Niklas Hoepner, Ilaria Tiddi, Herke van Hoof
KernelMatmul: Scaling Gaussian Processes to Large Time Series
Tilman Hoffbauer, Holger H. Hoos, Jakob Bossek
Multimodal Promptable Token Merging for Diffusion Models
Cheng-Yao Hong, Tyng-Luh Liu
Self-Attentive Spatio-Temporal Calibration for Precise Intermediate Layer Matching in ANN-to-SNN Distillation
Di Hong, Yueming Wang
Structural Entropy Guided Unsupervised Graph Out-Of-Distribution Detection
Yue Hou, He Zhu, Ruomei Liu et al.
Adaptive Multimodal Fusion: Dynamic Attention Allocation for Intent Recognition
Bo Hu, Kai Zhang, Yanghai Zhang et al.
An Information-theoretic Multi-task Representation Learning Framework for Natural Language Understanding
Dou Hu, Lingwei Wei, Wei Zhou et al.
Unsupervised Kernel-based Multi-view Feature Selection with Robust Self-representation and Binary Hashing
Rongyao Hu, Jiangzhang Gan, Mengmeng Zhan et al.
Transfer Learning Meets Functional Linear Regression: No Negative Transfer Under Posterior Drift
Xiaoyu Hu, Zhenhua Lin
Adaptive Multi-Scale Decomposition Framework for Time Series Forecasting
Yifan Hu, Peiyuan Liu, Peng Zhu et al.
R-DTI: Drug Target Interaction Prediction Based on Second-Order Relevance Exploration
Yang Hua, Tianyang Xu, Xiaoning Song et al.
TinyFoA: Memory Efficient Forward-Only Algorithm for On-Device Learning
Baichuan Huang, Amir Aminifar
Multi-view Evidential Learning-based Medical Image Segmentation
Chao Huang, Yushu Shi, Waikeung Wong et al.
GBRIP: Granular Ball Representation for Imbalanced Partial Label Learning
Jintao Huang, Yiu-ming Cheung, Chi-man Vong et al.
Analytical-Chemistry-Informed Transformer for Infrared Spectra Modeling
Shiluo Huang, Yining Jin, Wei Jin et al.
Enhance Vision-Language Alignment with Noise
Sida Huang, Hongyuan Zhang, Xuelong Li
GapMatch: Bridging Instance and Model Perturbations for Enhanced Semi-Supervised Medical Image Segmentation
Wei Huang, Lei Zhang, Zizhou Wang et al.
Graph Mixture of Experts and Memory-augmented Routers for Multivariate Time Series Anomaly Detection
Xiaoyu Huang, Weidong Chen, Bo Hu et al.
SoLA: Leveraging Soft Activation Sparsity and Low-Rank Decomposition for Large Language Model Compression
Xinhao Huang, You-Liang Huang, Zeyi Wen
Does GCL Need a Large Number of Negative Samples? Enhancing Graph Contrastive Learning with Effective and Efficient Negative Sampling
Yongqi Huang, Jitao Zhao, Dongxiao He et al.
Approximate State Abstraction for Markov Games
Hiroki Ishibashi, Kenshi Abe, Atsushi Iwasaki
Discovering Options That Minimize Average Planning Time
Alexander Ivanov, Akhil Bagaria, George Konidaris
TAIL-MIL: Time-Aware and Instance-Learnable Multiple Instance Learning for Multivariate Time Series Anomaly Detection
Jaeseok Jang, Hyuk-Yoon Kwon
Read, Watch and Scream! Sound Generation from Text and Video
Yujin Jeong, Yunji Kim, Sanghyuk Chun et al.
Association Pattern-enhanced Molecular Representation Learning
Lingxiang Jia, Yuchen Ying, Tian Qiu et al.
Balancing Privacy and Performance: A Many-in-One Approach for Image Anonymization
Xuemei Jia, Jiawei Du, Hui Wei et al.
Collaborative Similarity Fusion and Consistency Recovery for Incomplete Multi-view Clustering
Bingbing Jiang, Chenglong Zhang, Xinyan Liang et al.
Active Symbolic Discovery of Ordinary Differential Equations via Phase Portrait Sketching
Nan Jiang, Md Nasim, Yexiang Xue
M3Net: Efficient Time-Frequency Integration Network with Mirror Attention for Audio Classification on Edge
Xuanming Jiang, Baoyi An, Guoshuai Zhao et al.
A Knowledge Distillation-Based Approach to Enhance Transparency of Classifier Models
Yuchen Jiang, Xinyuan Zhao, Yihang Wu et al.
FedCFA: Alleviating Simpson’s Paradox in Model Aggregation with Counterfactual Federated Learning
Zhonghua Jiang, Jimin Xu, Shengyu Zhang et al.
BigMac: A Communication-Efficient Mixture-of-Experts Model Structure for Fast Training and Inference
Zewen Jin, Shengnan Wang, Jiaan Zhu et al.
IsUMap: Manifold Learning and Data Visualization Leveraging Vietoris-Rips Filtrations
Parvaneh Joharinad, Hannaneh Fahimi, Lukas Silvester Barth et al.
Discovering Symmetries of ODEs by Symbolic Regression
Paul Kahlmeyer, Niklas Merk, Joachim Giesen
Equal Merit Does Not Imply Equality: Discrimination at Equilibrium in a Hiring Market with Symmetric Agents
Serafina Kamp, Benjamin Fish
AudioGenX: Explainability on Text-to-Audio Generative Models
Hyunju Kang, Geonhee Han, Yoonjae Jeong et al.
Nearly Tight Bounds for Exploration in Streaming Multi-Armed Bandits with Known Optimality Gap
Nikolai Karpov, Chen Wang
GenPlan: Generative Sequence Models as Adaptive Planners
Akash Karthikeyan, Yash Vardhan Pant
On the Asymptotic Optimality of Confidence Interval Based Algorithms for Fixed Confidence MABs
Kushal Kejriwal, Nikhil Karamchandani, Jayakrishnan Nair
ExPERT: Modeling Human Behavior Under External Stimuli Aware Personalized MTPP
Subhendu Khatuya, Ritvik Vij, Paramita Koley et al.
Learning Structural Causal Models from Ordering: Identifiable Flow Models
Minh Khoa Le, Kien Do, Truyen Tran
T-MDML: Triplet-based Multiple Distance Metric Learning for Multi-Instance Multi-Label Classification with Label Correlation
Dongyeon Kim, Yejin Kan, Gangman Yi
Accurate Link Prediction for Edge-Incomplete Graphs via PU Learning
Junghun Kim, Ka Hyun Park, Hoyoung Yoon et al.
To Predict or Not to Predict? Proportionally Masked Autoencoders for Tabular Data Imputation
Jungkyu Kim, Kibok Lee, Taeyoung Park
Diffusion-Based Active Learning for Distributed Client Manifolds
Kwang In Kim
Sample-aware Adaptive Structured Pruning for Large Language Models
Jun Kong, Xinge Ma, Jin Wang et al.
Selective Uncertainty Propagation in Offline RL
Sanath Kumar Krishnamurthy, Tanmay Gangwani, Sumeet Katariya et al.
Crossfire: An Elastic Defense Framework for Graph Neural Networks Under Bit Flip Attacks
Lorenz Kummer, Samir Moustafa, Wilfried Gansterer et al.
pFedGPA: Diffusion-based Generative Parameter Aggregation for Personalized Federated Learning
Jiahao Lai, Jiaqi Li, Jian Xu et al.
CoffeeBoost: Gradient Boosting Native Conformal Inference for Bayesian Optimization
Yuanhao Lai, Pengfei Zheng, Chenpeng Ji et al.
De-singularity Subgradient for the q-th-Powered lₚ-Norm Weber Location Problem
Zhao-Rong Lai, Xiaotian Wu, Liangda Fang et al.
Explainable Neural Networks with Guarantee: A Sparse Estimation Approach
Antoine Ledent, Peng Liu
Kolmogorov-Arnold Networks Still Catastrophically Forget but Differently from MLP
Anton Lee, Heitor Murilo Gomes, Yaqian Zhang et al.
Truncated Gaussian Policy for Debiased Continuous Control
Ganghun Lee, Minji Kim, Minsu Lee et al.
TimeCAP: Learning to Contextualize, Augment, and Predict Time Series Events with Large Language Model Agents
Geon Lee, Wenchao Yu, Kijung Shin et al.
HYBOOD: A Hybrid Generative Model for Out-of-Distribution Detection with Corruption Estimation
Giwoong Lee, Jiseung Ahn, Jeongyeol Choe
Fourier Guided Adaptive Adversarial Augmentation for Generalization in Visual Reinforcement Learning
Jeong Woon Lee, Hyoseok Hwang
DomCLP: Domain-wise Contrastive Learning with Prototype Mixup for Unsupervised Domain Generalization
Jin-Seop Lee, Noo-ri Kim, Jee-Hyong Lee
DiffIM: Differentiable Influence Minimization with Surrogate Modeling and Continuous Relaxation
Junghun Lee, Hyunju Kim, Fanchen Bu et al.
Q-MAML: Quantum Model-Agnostic Meta-Learning for Variational Quantum Algorithms
Junyong Lee, Jeihee Cho, Shiho Kim
CG-TGAN: Conditional Generative Adversarial Networks with Graph Neural Networks for Tabular Data Synthesizing
Seungcheol Lee, Moohong Min
Maximizing the Position Embedding for Vision Transformers with Global Average Pooling
Wonjun Lee, Bumsub Ham, Suhyun Kim
Learning Strategy Representation for Imitation Learning in Multi-Agent Games
Shiqi Lei, Kanghoon Lee, Linjing Li et al.
Mining In-distribution Attributes in Outliers for Out-of-distribution Detection
Yutian Lei, Luping Ji, Pei Liu
Towards Trustable SHAP Scores
Olivier Létoffé, Xuanxiang Huang, Joao Marques-Silva
Distributionally Robust Policy Evaluation and Learning for Continuous Treatment with Observational Data
Cheuk Hang Leung, Yiyan Huang, Yijun Li et al.
Unlocking Better Closed-Set Alignment Based on Neural Collapse for Open-Set Recognition
Chaohua Li, Enhao Zhang, Chuanxing Geng et al.
FedMSGL: A Self-Expressive Hypergraph Based Federated Multi-View Learning
Daoyuan Li, Zuyuan Yang, Shengli Xie
Marginal Benefit Driven RL Teacher for Unsupervised Environment Design
Dexun Li, Wenjun Li, Pradeep Varakantham
AIA: Autoregression-Based Injection Attacks Against Text2SQL Models
Deyin Li, Xiang Ling, Changjiang Li et al.
k-HyperEdge Medoids for Clustering Ensemble
Feijiang Li, Jieting Wang, Liuya Zhang et al.
AdvDisplay: Adversarial Display Assembled by Thermoelectric Cooler for Fooling Thermal Infrared Detectors
Hao Li, Fanggao Wan, Yue Su et al.
Learning Causal Transition Matrix for Instance-dependent Label Noise
Jiahui Li, Tai-Wei Chang, Kun Kuang et al.
HEP-NAS: Towards Efficient Few-shot Neural Architecture Search via Hierarchical Edge Partitioning
Jianfeng Li, Jiawen Zhang, Feng Wang et al.
Modeling All Response Surfaces in One for Conditional Search Spaces
Jiaxing Li, Wei Liu, Chao Xue et al.
Multi-Label Ranking Loss Minimization for Matrix Completion
Jiaxuan Li, Xiaoyan Zhu, Hongrui Wang et al.
An Efficient and Accurate Dynamic Sparse Training Framework Based on Parameter-Freezing
Lei Li, Haochen Yang, Jiacheng Guo et al.
Adaptive Decision Boundary for Few-Shot Class-Incremental Learning
Linhao Li, Yongzhang Tan, Siyuan Yang et al.
GTDE: Grouped Training with Decentralized Execution for Multi-agent Actor-Critic
Mengxian Li, Qi Wang, Yongjun Xu
Deep Hypergraph Neural Networks with Tight Framelets
Ming Li, Yujie Fang, Yi Wang et al.
On the Power of Convolution-Augmented Transformer
Mingchen Li, Xuechen Zhang, Yixiao Huang et al.
Detecting and Corrupting Convolution-based Unlearnable Examples
Minghui Li, Xianlong Wang, Zhifei Yu et al.
Dynamic Clustering Convolutional Neural Network
Tanzhe Li, Baochang Zhang, Jiayi Lyu et al.
Adaptive Dual Guidance Knowledge Distillation
Tong Li, Long Liu, Kang Liu et al.
Unravelling Causal Genetic Biomarkers of Alzheimer’s Disease via Neuron to Gene-token Backtracking in Neural Architecture: A Groundbreaking Reverse-Gene-Finder Approach
Victor O. K. Li, Yang Han, Jacqueline C. K. Lam
Riemann-based Multi-scale Attention Reasoning Network for Text-3D Retrieval
Wenrui Li, Wei Han, Yandu Chen et al.
Optimizing Quantized Diffusion Models via Distillation with Cross-Timestep Error Correction
Yanxi Li, Chengbin Du
Community-Centric Graph Unlearning
Yi Li, Shichao Zhang, Guixian Zhang et al.
Complex-Cycle-Consistent Diffusion Model for Monaural Speech Enhancement
Yi Li, Yang Sun, Plamen P Angelov
Edge Contrastive Learning: An Augmentation-Free Graph Contrastive Learning Model
Yujun Li, Hongyuan Zhang, Yuan Yuan
Calibrated Disambiguation for Partial Multi-label Learning
Zhuoming Li, Yuheng Jia, Mi Yu et al.
Noise-Injected Spiking Graph Convolution for Energy-Efficient 3D Point Cloud Denoising
Zikuan Li, Qiaoyun Wu, Jialin Zhang et al.
Metric-Agnostic Continual Learning for Sustainable Group Fairness
Heng Lian, Chen Zhao, Zhong Chen et al.
TTA-FedDG: Leveraging Test-Time Adaptation to Address Federated Domain Generalization
Haoyuan Liang, Xinyu Zhang, Shilei Cao et al.
GNN-Transformer Cooperative Architecture for Trustworthy Graph Contrastive Learning
Jianqing Liang, Xinkai Wei, Min Chen et al.
Label Noise Correction via Fuzzy Learning Machine
Jiye Liang, Yixiao Li, Junbiao Cui
Till the Layers Collapse: Compressing a Deep Neural Network Through the Lenses of Batch Normalization Layers.
Zhu Liao, Nour Hezbri, Victor Quétu et al.
Learning Local Neighborhoods of Non-Gaussian Graphical Models
Sarah Liaw, Rebecca Morrison, Youssef Marzouk et al.
Convergence Analysis of Federated Learning Methods Using Backward Error Analysis
Jinwoo Lim, Suhyun Kim, Soo-Mook Moon
Local Causal Discovery Without Causal Sufficiency
Zhaolong Ling, Jiale Yu, Yiwen Zhang et al.
Graph Agent Network: Empowering Nodes with Inference Capabilities for Adversarial Resilience
Ao Liu, Wenshan Li, Tao Li et al.
Grimm: A Plug-and-Play Perturbation Rectifier for Graph Neural Networks Defending Against Poisoning Attacks
Ao Liu, Wenshan Li, Beibei Li et al.
An Enhanced Levenberg--Marquardt Method via Gram Reduction
Chengchang Liu, Luo Luo, John C.S. Lui
TimeCMA: Towards LLM-Empowered Multivariate Time Series Forecasting via Cross-Modality Alignment
Chenxi Liu, Qianxiong Xu, Hao Miao et al.
Asymmetric Learning for Spectral Graph Neural Networks
Fangbing Liu, Qing Wang
Learning Disentangled Equivariant Representation for Explicitly Controllable 3D Molecule Generation
Haoran Liu, Youzhi Luo, Tianxiao Li et al.
LiD-FL: Towards List-Decodable Federated Learning
Hong Liu, Liren Shan, Han Bao et al.
Reducing AUV Energy Consumption Through Dynamic Sensor Directions Switching via Deep Reinforcement Learning
Jiawei Liu, Yuanbo Xu, Shanshan Song et al.
Federated Graph-Level Clustering Network
Jingxin Liu, Jieren Cheng, Renda Han et al.
CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning
Peiyuan Liu, Hang Guo, Tao Dai et al.
Fine-Grained Graph Representation Learning for Heterogeneous Mobile Networks with Attentive Fusion and Contrastive Learning
Shengheng Liu, Tianqi Zhang, Ningning Fu et al.
Probability-Density-aware Semi-supervised Learning
Shuyang Liu, Ruiqiu Zheng, Yunhang Shen et al.
Integrating Co-Training with Edge Discrimination to Enhance Graph Neural Networks Under Heterophily
Siqi Liu, Dongxiao He, Zhizhi Yu et al.
Non-stochastic Budgeted Online Pricing with Semi-Bandit Feedback
Xiang Liu, Hau Chan, Minming Li et al.
AFiRe: Anatomy-Driven Self-Supervised Learning for Fine-Grained Representation in Radiographic Images
Yihang Liu, Lianghua He, Ying Wen et al.
Multi-Objective Molecular Design Through Learning Latent Pareto Set
Yiping Liu, Jiahao Yang, Xuanbai Ren et al.
GCAD: Anomaly Detection in Multivariate Time Series from the Perspective of Granger Causality
Zehao Liu, Mengzhou Gao, Pengfei Jiao
Adversarial Contrastive Graph Augmentation with Counterfactual Regularization
Tao Long, Lei Zhang, Liang Zhang et al.
SLR-MVTC: Smooth Low-Rank Multi-View Tensor Clustering
Zhen Long, Yipeng Liu, Yazhou Ren et al.
FedCross: Intertemporal Federated Learning Under Evolutionary Games
Jianfeng Lu, Ying Zhang, Riheng Jia et al.
VVRec: Reconstruction Attacks on DL-based Volumetric Video Upstreaming via Latent Diffusion Model with Gamma Distribution
Rui Lu, Bihai Zhang, Dan Wang
Adaptive-Grained Label Distribution Learning
Yunan Lu, Weiwei Li, Dun Liu et al.
Collaborative Semantic Consistency Alignment for Blended-Target Domain Adaptation
Yuwu Lu, Xue Hu, Waikeung Wong et al.
Invertible Projection and Conditional Alignment for Multi-Source Blended-Target Domain Adaptation
Yuwu Lu, Haoyu Huang, Waikeung Wong et al.
Bidirectional Logits Tree: Pursuing Granularity Reconcilement in Fine-Grained Classification
Zhiguang Lu, Qianqian Xu, Shilong Bao et al.
Emergence-Inspired Multi-Granularity Causal Learning
Hanwen Luo, Guoxian Yu, Jun Wang et al.
Like an Ophthalmologist: Dynamic Selection Driven Multi-View Learning for Diabetic Retinopathy Grading
Xiaoling Luo, Qihao Xu, Huisi Wu et al.
Effects of Momentum in Implicit Bias of Gradient Flow for Diagonal Linear Networks
Bochen Lyu, He Wang, Zheng Wang et al.
Addressing Multi-Label Learning with Partial Labels: From Sample Selection to Label Selection
Gengyu Lyu, Bohang Sun, Xiang Deng et al.
TSVC: Tripartite Learning with Semantic Variation Consistency for Robust Image-Text Retrieval
Shuai Lyu, Zijing Tian, Zhonghong Ou et al.
SSE-SAM: Balancing Head and Tail Classes Gradually Through Stage-Wise SAM
Xingyu Lyu, Qianqian Xu, Zhiyong Yang et al.
Vision-Based Generic Potential Function for Policy Alignment in Multi-Agent Reinforcement Learning
Hao Ma, Shijie Wang, Zhiqiang Pu et al.
Data-Free Black-Box Federated Learning via Zeroth-Order Gradient Estimation
Xinge Ma, Jin Wang, Xuejie Zhang
ComprehendEdit: A Comprehensive Dataset and Evaluation Framework for Multimodal Knowledge Editing
Yaohui Ma, Xiaopeng Hong, Shizhou Zhang et al.
RoPaSS: Robust Watermarking for Partial Screen-Shooting Scenarios
Zehua Ma, Han Fang, Xi Yang et al.
Local Causal Discovery for Structural Evidence of Direct Discrimination
Jacqueline Maasch, Kyra Gan, Violet Chen et al.
Sequential Conditional Transport on Probabilistic Graphs for Interpretable Counterfactual Fairness
Agathe Fernandes Machado, Arthur Charpentier, Ewen Gallic
The Gradient of Algebraic Model Counting
Jaron Maene, Luc De Raedt
PALM: Pushing Adaptive Learning Rate Mechanisms for Continual Test-Time Adaptation
Sarthak Kumar Maharana, Baoming Zhang, Yunhui Guo
TabGLM: Tabular Graph Language Model for Learning Transferable Representations Through Multi-Modal Consistency Minimization
Anay Majee, Maria Xenochristou, Wei-Peng Chen
HyperDefender: A Robust Framework for Hyperbolic GNNs
Nikita Malik, Rahul Gupta, Sandeep Kumar
Harnessing Event Sensory Data for Error Pattern Prediction in Vehicles: A Language Model Approach
Hugo Math, Rainer Lienhart, Robin Schön
Eco Search: A No-delay Best-First Search Algorithm for Program Synthesis
Théo Matricon, Nathanaël Fijalkow, Guillaume Lagarde
ID-GMLM: Intelligent Decision-Making with Integrated Graph Models and Large Language Models
Zhenhua Meng, Fanshen Meng, Rongheng Lin et al.
Query-efficient Attack for Black-box Image Inpainting Forensics via Reinforcement Learning
Xianbo Mo, Shunquan Tan, Bin Li et al.
Unlocking the Game: Estimating Games in Möbius Representation for Explanation and High-Order Interaction Detection
Majid Mohammadi, Ilaria Tiddi, Annette Ten Teije
Adaptive Sampling to Reduce Epistemic Uncertainty Using Prediction Interval-Generation Neural Networks
Giorgio Morales, John W. Sheppard
GLEN: Generalized Focal Loss Ensemble of Low-Rank Networks for Calibrated Visual Question Answering
Mahsa Mozaffari, Hitesh Sapkota, Qi Yu
SLACE: A Monotone and Balance-Sensitive Loss Function for Ordinal Regression
Inbar Nachmani, Bar Genossar, Coral Scharf et al.
Entropy Regularized Task Representation Learning for Offline Meta-Reinforcement Learning
Mohammadreza Nakhaeinezhadfard, Aidan Scannell, Joni Pajarinen
Regional Expected Improvement for Efficient Trust Region Selection in High-Dimensional Bayesian Optimization
Nobuo Namura, Sho Takemori
Decoupled Policy Actor-Critic: Bridging Pessimism and Risk Awareness in Reinforcement Learning
Michal Nauman, Marek Cygan
Autonomous Option Invention for Continual Hierarchical Reinforcement Learning and Planning
Rashmeet Kaur Nayyar, Siddharth Srivastava