AAAI 2024

2,864 papers

MetaMix: Meta-State Precision Searcher for Mixed-Precision Activation Quantization

Han-Byul Kim, Joo Hyung Lee, Sungjoo Yoo, Hong-Seok Kim

Adaptive Shortcut Debiasing for Online Continual Learning

Doyoung Kim, Dongmin Park, Yooju Shin, Jihwan Bang, Hwanjun Song

When Model Meets New Normals: Test-Time Adaptation for Unsupervised Time-Series Anomaly Detection

DONGMIN KIM, Sunghyun Park, Jaegul Choo

IOFM: Using the Interpolation Technique on the Over-Fitted Models to Identify Clean-Annotated Samples

Dongha Kim, Yongchan Choi, Kunwoong Kim, Ilsang Ohn, Yongdai Kim

Shaping Up SHAP: Enhancing Stability through Layer-Wise Neighbor Selection

Gwladys Kelodjou, Laurence Rozé, Véronique Masson, Luis Galárraga, Romaric Gaudel

Adversarially Balanced Representation for Continuous Treatment Effect Estimation

Amirreza Kazemi, Martin Ester

Communication-Efficient Collaborative Regret Minimization in Multi-Armed Bandits

Nikolai Karpov, Qin Zhang

SHAP@k: Efficient and Probably Approximately Correct (PAC) Identification of Top-K Features

Sanjay Kariyappa, Leonidas Tsepenekas, Freddy Lecue, Daniele Magazzeni

Neural Oscillators for Generalization of Physics-Informed Machine Learning

Taniya Kapoor, Abhishek Chandra, Daniel M. Tartakovsky, Hongrui Wang, Alfredo Nunez

Coupling Graph Neural Networks with Fractional Order Continuous Dynamics: A Robustness Study

Qiyu Kang, KAI ZHAO, Yang Song, Yihang Xie, Yanan Zhao

Recall-Oriented Continual Learning with Generative Adversarial Meta-Model

Haneol Kang, Dong-Wan Choi

Measuring Self-Supervised Representation Quality for Downstream Classification Using Discriminative Features

Neha Kalibhat, Kanika Narang, Hamed Firooz, Maziar Sanjabi, Soheil Feizi

NN-Steiner: A Mixed Neural-Algorithmic Approach for the Rectilinear Steiner Minimum Tree Problem

Andrew B. Kahng, Robert R. Nerem, Yusu Wang, Chien-Yi Yang

Patch-Wise Graph Contrastive Learning for Image Translation

Chanyong Jung, Gihyun Kwon, Jong Chul Ye

Towards Safe Policy Learning under Partial Identifiability: A Causal Approach

Shalmali Joshi, Junzhe Zhang, Elias Bareinboim

FLAME: A Small Language Model for Spreadsheet Formulas

Harshit Joshi, Abishai Ebenezer, José Cambronero Sanchez, Sumit Gulwani, Aditya Kanade

FoX: Formation-Aware Exploration in Multi-Agent Reinforcement Learning

Yonghyeon Jo, Sunwoo Lee, Junghyuk Yeom, Seungyul Han

Sterling: Synergistic Representation Learning on Bipartite Graphs

Baoyu Jing, Yuchen Yan, Kaize Ding, Chanyoung Park, Yada Zhu

GLDL: Graph Label Distribution Learning

Yufei Jin, Richard Gao, Yi He, Xingquan Zhu

Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs

Tianyuan Jin, Hao-Lun Hsu, William Chang, Pan Xu

Fractional Deep Reinforcement Learning for Age-Minimal Mobile Edge Computing

Lyudong Jin, Ming Tang, Meng Zhang, Hao Wang

Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts

Kun Jin, Tongxin Yin, Zhongzhu Chen, Zeyu Sun, Xueru Zhang

Provably Convergent Federated Trilevel Learning

Yang Jiao, Kai Yang, Tiancheng Wu, Chengtao Jian, Jianwei Huang

Deep Incomplete Multi-View Learning Network with Insufficient Label Information

Zhangqi Jiang, Tingjin Luo, Xinyan Liang

Learning Diverse Risk Preferences in Population-Based Self-Play

Yuhua Jiang, Qihan Liu, Xiaoteng Ma, Chenghao Li, Yiqin Yang

Racing Control Variable Genetic Programming for Symbolic Regression

Nan Jiang, Yexiang Xue

FMRNet: Image Deraining via Frequency Mutual Revision

Kui Jiang, Junjun Jiang, Xianming Liu, Xin Xu, Xianzheng Ma

DHGCN: Dynamic Hop Graph Convolution Network for Self-Supervised Point Cloud Learning

Jincen Jiang, Lizhi Zhao, Xuequan Lu, Wei Hu, Imran Razzak

Navigating Real-World Partial Label Learning: Unveiling Fine-Grained Images with Attributes

Haoran Jiang, Zhihao Sun, YingJie Tian

Which Is More Effective in Label Noise Cleaning, Correction or Filtering?

Gaoxia Jiang, Jia Zhang, Xuefei Bai, Wenjian Wang, Deyu Meng

Long-Tailed Partial Label Learning by Head Classifier and Tail Classifier Cooperation

Yuheng Jia, Xiaorui Peng, Ran Wang, Min-ling Zhang

FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter Sharing

Yongzhe Jia, Xuyun Zhang, Amin Beheshti, Wanchun Dou

Stratified GNN Explanations through Sufficient Expansion

Yuwen Ji, Lei Shi, Zhimeng Liu, Ge Wang

FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning

Xinyuan Ji, Zhaowei Zhu, Wei Xi, Olga Gadyatskaya, Zilong Song

MusER: Musical Element-Based Regularization for Generating Symbolic Music with Emotion

Shulei Ji, Xinyu Yang

Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective

Qirui Ji, Jiangmeng Li, Jie Hu, Rui Wang, Changwen Zheng

Meta-Learning-Based Adaptive Stability Certificates for Dynamical Systems

Amit Jena, Dileep Kalathil, Le Xie

Transportable Representations for Domain Generalization

Kasra Jalaldoust, Elias Bareinboim

Universal Weak Coreset

Ragesh Jaiswal, Amit Kumar

Instance-Conditional Timescales of Decay for Non-Stationary Learning

Nishant Jain, Pradeep Shenoy

GO-DICE: Goal-Conditioned Option-Aware Offline Imitation Learning via Stationary Distribution Correction Estimation

Abhinav Jain, Vaibhav Unhelkar

Unified Framework for Diffusion Generative Models in SO(3): Applications in Computer Vision and Astrophysics

Yesukhei Jagvaral, Francois Lanusse, Rachel Mandelbaum

Delivering Inflated Explanations

Yacine Izza, Alexey Ignatiev, Peter J. Stuckey, Joao Marques-Silva

Personalized Reinforcement Learning with a Budget of Policies

Dmitry Ivanov, Omer Ben-Porat

TMPNN: High-Order Polynomial Regression Based on Taylor Map Factorization

Andrei Ivanov, Stefan Ailuro

Fairness without Demographics through Shared Latent Space-Based Debiasing

Rashidul Islam, Huiyuan Chen, Yiwei Cai

New Classes of the Greedy-Applicable Arm Feature Distributions in the Sparse Linear Bandit Problem

Koji Ichikawa, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga

Non-exemplar Online Class-Incremental Continual Learning via Dual-Prototype Self-Augment and Refinement

Fushuo Huo, Wenchao Xu, Jingcai Guo, Haozhao Wang, Yunfeng Fan

ProCC: Progressive Cross-Primitive Compatibility for Open-World Compositional Zero-Shot Learning

Fushuo Huo, Wenchao Xu, Song Guo, Jingcai Guo, Haozhao Wang

Optimal Survival Trees: A Dynamic Programming Approach

Tim Huisman, Jacobus G. M. van der Linden, Emir Demirović

Binding-Adaptive Diffusion Models for Structure-Based Drug Design

Zhilin Huang, Ling Yang, ZAIXI ZHANG, Xiangxin Zhou, Yu Bao

Protein 3D Graph Structure Learning for Robust Structure-Based Protein Property Prediction

Yufei Huang, Siyuan Li, Lirong Wu, Jin Su, Haitao Lin

Higher-Order Graph Convolutional Network with Flower-Petals Laplacians on Simplicial Complexes

Yiming Huang, Yujie Zeng, Qiang Wu, Linyuan Lü

One Step Learning, One Step Review

Xiaolong Huang, Qiankun Li, Xueran Li, Xuesong Gao

Stochastic Bayesian Optimization with Unknown Continuous Context Distribution via Kernel Density Estimation

Xiaobin Huang, Lei Song, Ke Xue, Chao Qian

Factorized Explainer for Graph Neural Networks

Rundong Huang, Farhad Shirani, Dongsheng Luo

Measuring Task Similarity and Its Implication in Fine-Tuning Graph Neural Networks

Renhong Huang, Jiarong Xu, Xin Jiang, Chenglu Pan, Zhiming Yang

HDMixer: Hierarchical Dependency with Extendable Patch for Multivariate Time Series Forecasting

Qihe Huang, Lei Shen, Ruixin Zhang, Jiahuan Cheng, Shouhong Ding

PPO-Clip Attains Global Optimality: Towards Deeper Understandings of Clipping

Nai-Chieh Huang, Ping-Chun Hsieh, Kuo-Hao Ho, I-Chen Wu

eTag: Class-Incremental Learning via Embedding Distillation and Task-Oriented Generation

Libo Huang, Yan Zeng, Chuanguang Yang, Zhulin An, Boyu Diao

SEC: More Accurate Clustering Algorithm via Structural Entropy

Junyu Huang, Qilong Feng, Jiahui Wang, Ziyun Huang, Jinhui Xu

Energy Efficient Streaming Time Series Classification with Attentive Power Iteration

Hao Huang, Tapan Shah, Scott Evans, Shinjae Yoo

Terrain Diffusion Network: Climatic-Aware Terrain Generation with Geological Sketch Guidance

Zexin Hu, Kun Hu, Clinton Mo, Lei Pan, Zhiyong Wang

Spotting the Unseen: Reciprocal Consensus Network Guided by Visual Archetypes

Wenbo Hu, Hongjian Zhan, Xinchen Ma, Yue Lu, Ching Y. Suen

PA2D-MORL: Pareto Ascent Directional Decomposition Based Multi-Objective Reinforcement Learning

Tianmeng Hu, Biao Luo

PrefAce: Face-Centric Pretraining with Self-Structure Aware Distillation

Siyuan Hu, Zheng Wang, Peng Hu, Xi Peng, Jie Wu

FedMut: Generalized Federated Learning via Stochastic Mutation

Ming Hu, Yue Cao, Anran Li, Zhiming Li, Chengwei Liu

Sequential Fusion Based Multi-Granularity Consistency for Space-Time Transformer Tracking

Kun Hu, Wenjing Yang, Wanrong Huang, Xianchen Zhou, Mingyu Cao

Relax Image-Specific Prompt Requirement in SAM: A Single Generic Prompt for Segmenting Camouflaged Objects

Jian Hu, Jiayi Lin, Shaogang Gong, Weitong Cai

A Sequentially Fair Mechanism for Multiple Sensitive Attributes

Francois Hu, Philipp Ratz, Arthur Charpentier

Structured Probabilistic Coding

Dou Hu, Lingwei Wei, Yaxin Liu, Wei Zhou, Songlin Hu

Complete Neural Networks for Complete Euclidean Graphs

Snir Hordan, Tal Amir, Steven J. Gortler, Nadav Dym

Foreseeing Reconstruction Quality of Gradient Inversion: An Optimization Perspective

Hyeong Gwon Hong, Yooshin Cho, Hanbyel Cho, Jaesung Ahn, Junmo Kim

Colored Noise in PPO: Improved Exploration and Performance through Correlated Action Sampling

Jakob Hollenstein, Georg Martius, Justus Piater

Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-Based Similarity

Van Thuy Hoang, O-Joun Lee

Few-Shot Learning via Repurposing Ensemble of Black-Box Models

Minh Hoang, Trong Nghia Hoang

Imitate the Good and Avoid the Bad: An Incremental Approach to Safe Reinforcement Learning

Huy Hoang, Tien Mai, Pradeep Varakantham

Training-Free Quantum Architecture Search

Zhimin He, Maijie Deng, Shenggen Zheng, Lvzhou Li, Haozhen Situ

SoundCount: Sound Counting from Raw Audio with Dyadic Decomposition Neural Network

Yuhang He, Zhuangzhuang Dai, Niki Trigoni, Long Chen, Andrew Markham

Learning Only When It Matters: Cost-Aware Long-Tailed Classification

Yu-Cheng He, Yao-Xiang Ding, Han-Jia Ye, Zhi-Hua Zhou

Exploring Channel-Aware Typical Features for Out-of-Distribution Detection

Rundong He, Yue Yuan, Zhongyi Han, Fan Wang, Wan Su

Generative Calibration of Inaccurate Annotation for Label Distribution Learning

Liang He, Yunan Lu, Weiwei Li, Xiuyi Jia

Enhancing Semi-supervised Domain Adaptation via Effective Target Labeling

Jiujun He, Bin Liu, Guosheng Yin

Not All Tasks Are Equally Difficult: Multi-Task Deep Reinforcement Learning with Dynamic Depth Routing

Jinmin He, Kai Li, Yifan Zang, Haobo Fu, Qiang Fu

IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate Importance

Hongyi He, Longjun Liu, Haonan Zhang, Nanning Zheng

Decoupling Meta-Reinforcement Learning with Gaussian Task Contexts and Skills

Hongcai He, Anjie Zhu, Shuang Liang, Feiyu Chen, Jie Shao

Improving Distinguishability of Class for Graph Neural Networks

Dongxiao He, Shuwei Liu, Meng Ge, Zhizhi Yu, Guangquan Xu

A New Mechanism for Eliminating Implicit Conflict in Graph Contrastive Learning

Dongxiao He, Jitao Zhao, Cuiying Huo, Yongqi Huang, Yuxiao Huang

Fairness under Covariate Shift: Improving Fairness-Accuracy Tradeoff with Few Unlabeled Test Samples

Shreyas Havaldar, Jatin Chauhan, Karthikeyan Shanmugam, Jay Nandy, Aravindan Raghuveer

Selective Deep Autoencoder for Unsupervised Feature Selection

Wael Hassanieh, Abdallah Chehade

Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space

Mohsin Hasan, Guojun Zhang, Kaiyang Guo, Xi Chen, Pascal Poupart

Multiagent Gumbel MuZero: Efficient Planning in Combinatorial Action Spaces

Xiaotian Hao, Jianye Hao, Chenjun Xiao, Kai Li, Dong Li

Double-Layer Hybrid-Label Identification Feature Selection for Multi-View Multi-Label Learning

Pingting Hao, Kunpeng Liu, Wanfu Gao

Composite Active Learning: Towards Multi-Domain Active Learning with Theoretical Guarantees

Guang-Yuan Hao, Hengguan Huang, Haotian Wang, Jie Gao, Hao Wang

Complexity of Neural Network Training and ETR: Extensions with Effectively Continuous Functions

Teemu Hankala, Miika Hannula, Juha Kontinen, Jonni Virtema

Forced Exploration in Bandit Problems

Qi Han, Li Zhu, Fei Guo

Domain-Aware Fine-Tuning: Enhancing Neural Network Adaptability

Seokhyeon Ha, Sunbeom Jeong, Jungwoo Lee

From Past to Future: Rethinking Eligibility Traces

Dhawal Gupta, Scott M. Jordan, Shreyas Chaudhari, Bo Liu, Philip S. Thomas

Ternary Spike: Learning Ternary Spikes for Spiking Neural Networks

Yufei Guo, Yuanpei Chen, Xiaode Liu, Weihang Peng, Yuhan Zhang

FedCSL: A Scalable and Accurate Approach to Federated Causal Structure Learning

Xianjie Guo, Kui Yu, Lin Liu, Jiuyong Li