Most Cited AAAI "style mimicry attacks" Papers
5,317 papers found • Page 20 of 27
Conference
Improving Deep Learning Speed and Performance Through Synaptic Neural Balance
Antonios Alexos, Ian Domingo, Pierre Baldi
Unleashing the Potential of Model Bias for Generalized Category Discovery
Wenbin An, Haonan Lin, Jiahao Nie et al.
On the Robustness of Distributed Machine Learning Against Transfer Attacks
Sebastien Andreina, Pascal Zimmer, Ghassan Karame
Gaussian Graphical Modelling Without Independence Assumptions for Uncentered Data
Bailey Andrew, David R. Westhead, Luisa Cutillo
Parallel-Learning of Invariant and Tempo-variant Attributes of Single-Lead Cardiac Signals: PLITA
Adrian Atienza, Jakob E. Bardram, Sadasivan Puthusserypady
List Update with Prediction
Yossi Azar, Shahar Lewkowicz, Varun Suriyanarayana
Cradle-VAE: Enhancing Single-Cell Gene Perturbation Modeling with Counterfactual Reasoning-based Artifact Disentanglement
Seungheun Baek, Soyon Park, Yan Ting Chok et al.
FSL-Rectifier: Rectify Outliers in Few-Shot Learning via Test-Time Augmentation
Yunwei Bai, Ying Kiat Tan, Shiming Chen et al.
Improved Fixed-Parameter Bounds for Min-Sum-Radii and Diameters k-Clustering and Their Fair Variants
Sandip Banerjee, Yair Bartal, Lee-Ad Gottlieb et al.
EFSkip: A New Error Feedback with Linear Speedup for Compressed Federated Learning with Arbitrary Data Heterogeneity
Hongyan Bao, Pengwen Chen, Ying Sun et al.
On the Trainability and Classical Simulability of Learning Matrix Product States Variationally
Afrad Basheer, Yuan Feng, Christopher Ferrie et al.
Deep-Union Completion
Siddharth Baskar, Karan Vikyath Veeranna Rupashree, Daniel L. Pimentel-Alarcón
A (1+ε)-Approximation for Ultrametric Embedding in Subquadratic Time
Gabriel Bathie, Guillaume Lagarde
Generalized Convergence Analysis of Tsetlin Automaton Based Algorithms: A Probabilistic Approach to Concept Learning
Mohamed-Bachir Belaid, Jivitesh Sharma, Lei Jiao et al.
Teaching Models to Improve on Tape
Liat Bezalel, Eyal Orgad, Amir Globerson
Learnability of Parameter-Bounded Bayes Nets
Arnab Bhattacharyya, Davin Choo, Sutanu Gayen et al.
Neural Conjugate Flows: A Physics-Informed Architecture with Flow Structure
Arthur Bizzi, Lucas Nissenbaum, João M. Pereira
Weighted Embeddings for Low-Dimensional Graph Representation
Thomas Bläsius, Jean-Pierre von der Heydt, Maximilian Katzmann et al.
Conditional Feature Importance with Generative Modeling Using Adversarial Random Forests
Kristin Blesch, Niklas Koenen, Jan Kapar et al.
The Indoor-Training Effect: Unexpected Gains from Distribution Shifts in the Transition Function
Serena Bono, Spandan Madan, Ishaan Grover et al.
Leveraging Constraint Violation Signals for Action Constrained Reinforcement Learning
Janaka Chathuranga Brahmanage, Jiajing Ling, Akshat Kumar
Disentangling Long-Short Term State Under Unknown Interventions for Online Time Series Forecasting
Ruichu Cai, Haiqin Huang, Zhifan Jiang et al.
Fairness Shields: Safeguarding against Biased Decision Makers
Filip Cano, Thomas A. Henzinger, Bettina Könighofer et al.
Differentiable Adversarial Attacks for Marked Temporal Point Processes
Pritish Chakraborty, Vinayak Gupta, Rahul R et al.
Global Graph Propagation with Hierarchical Information Transfer for Incomplete Contrastive Multi-view Clustering
Guoqing Chao, Kaixin Xu, Xijiong Xie et al.
Constraint-Adaptive Policy Switching for Offline Safe Reinforcement Learning
Yassine Chemingui, Aryan Deshwal, Honghao Wei et al.
Efficient Anomaly Detection of Irregular Sequences in Ct-Echo Model Space
Ao Chen, Xiren Zhou, Huanhuan Chen
JEN-1 DreamStyler: Customized Musical Concept Learning via Pivotal Parameters Tuning
Boyu Chen, Peike Li, Yao Yao et al.
Biased Incomplete Multi-View Learning
Haishun Chen, Cai Xu, Ziyu Guan et al.
FedPop: Federated Population-based Hyperparameter Tuning
Haokun Chen, Denis Krompaß, Jindong Gu et al.
Semi-Supervised Multimodal Classification Through Learning from Modal and Strategic Complementarities
Junchi Chen, Richong Zhang, Junfan Chen
Federated Foundation Models on Heterogeneous Time Series
Shengchao Chen, Guodong Long, Jing Jiang et al.
Learnware Specification via Label-Aware Neural Embedding
Wei Chen, Jun-Xiang Mao, Min-Ling Zhang
The Distributional Reward Critic Framework for Reinforcement Learning Under Perturbed Rewards
Xi Chen, Zhihui Zhu, Andrew Perrault
DualGFL: Federated Learning with a Dual-Level Coalition-Auction Game
Xiaobing Chen, Xiangwei Zhou, Songyang Zhang et al.
MIETT: Multi-Instance Encrypted Traffic Transformer for Encrypted Traffic Classification
Xu-Yang Chen, Lu Han, De-Chuan Zhan et al.
Novelty-Guided Data Reuse for Efficient and Diversified Multi-Agent Reinforcement Learning
Yangkun Chen, Kai Yang, Jian Tao et al.
Beyond Homophily: Graph Contrastive Learning with Macro-Micro Message Passing
Yiyuan Chen, Donghai Guan, Weiwei Yuan et al.
GeCC: Generalized Contrastive Clustering with Domain Shifts Modeling
Yujie Chen, Wenhui Wu, Le Ou-Yang et al.
WatE: A Wasserstein t-distributed Embedding Method for Information-enriched Graph Visualization
Minjie Cheng, Dixin Luo, Hongteng Xu
Deep Implicit Imitation Reinforcement Learning in Heterogeneous Action Settings
Iason Chrysomallis, Georgios Chalkiadakis, Ioannis Papamichail et al.
Rethinking the Starting Point: Collaborative Pre-Training for Federated Downstream Tasks
Yun-Wei Chu, Dong-Jun Han, Seyyedali Hosseinalipour et al.
Probabilistic Shielding for Safe Reinforcement Learning
Edwin Hamel-De le Court, Francesco Belardinelli, Alexander W. Goodall
Neural Variable-Order Fractional Differential Equation Networks
Wenjun Cui, Qiyu Kang, Xuhao Li et al.
Few-Shot Audio-Visual Class-Incremental Learning with Temporal Prompting and Regularization
Yawen Cui, Li Liu, Zitong Yu et al.
Synthetic Tabular Data Generation for Imbalanced Classification: The Surprising Effectiveness of an Overlap Class
Annie D'souza, Swetha M, Sunita Sarawagi
Creating Coherence in Federated Non-Negative Matrix Factorization
Sebastian Dalleiger, Aristides Gionis
Federated Binary Matrix Factorization Using Proximal Optimization
Sebastian Dalleiger, Jilles Vreeken, Michael Kamp
Skill Disentanglement in Reproducing Kernel Hilbert Space
Vedant Dave, Elmar Rueckert
CAGE: Unsupervised Visual Composition and Animation for Controllable Video Generation
Aram Davtyan, Sepehr Sameni, Björn Ommer et al.
Relational Neurosymbolic Markov Models
Lennert De Smet, Gabriele Venturato, Luc De Raedt et al.
THESAURUS: Contrastive Graph Clustering by Swapping Fused Gromov-Wasserstein Couplings
Bowen Deng, Tong Wang, Lele Fu et al.
Expected Hypervolume Improvement Is a Particular Hypervolume Improvement
Jingda Deng, Jianyong Sun, Qingfu Zhang et al.
Enhancing Online Reinforcement Learning with Meta-Learned Objective from Offline Data
Shilong Deng, Zetao Zheng, Hongcai He et al.
Enhancing Multimodal Affective Analysis with Learned Live Comment Features
Zhaoyuan Deng, Amith Ananthram, Kathleen McKeown
How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning?
Wenjun Ding, Ying An, Lixing Chen et al.
Beyond Mandatory Federations: Balancing Egoism, Utilitarianism and Egalitarianism in Mixed-Motive Games
Shaokang Dong, Chao Li, Shangdong Yang et al.
DCILP: A Distributed Approach for Large-Scale Causal Structure Learning
Shuyu Dong, Michele Sebag, Kento Uemura et al.
AtomNet: Designing Tiny Models from Operators Under Extreme MCU Constraints
Zhiwei Dong, Mingzhu Shen, Shihao Bai et al.
On the Hardness of Training Deep Neural Networks Discretely
Ilan Doron-Arad
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.
PA3Fed: Period-Aware Adaptive Aggregation for Improved Federated Learning
Chengxiang Huang, Bingyan Liu
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
Don’t Think It Twice: Exploit Shift Invariance for Efficient Online Streaming Inference of CNNs
Christodoulos Kechris, Jonathan Dan, Jose Miranda et al.
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.
Efficient Event-Based Semantic Segmentation via Exploiting Frame-Event Fusion: A Hybrid Neural Network Approach
Hebei Li, Yansong Peng, Jiahui Yuan 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