AAAI 2024

2,864 papers

G-Adapter: Towards Structure-Aware Parameter-Efficient Transfer Learning for Graph Transformer Networks

Anchun Gui, Jinqiang Ye, Han Xiao

Summarizing Stream Data for Memory-Constrained Online Continual Learning

Jianyang Gu, Kai Wang, Wei Jiang, Yang You

Taming the Sigmoid Bottleneck: Provably Argmaxable Sparse Multi-Label Classification

Andreas Grivas, Antonio Vergari, Adam Lopez

DeepSaDe: Learning Neural Networks That Guarantee Domain Constraint Satisfaction

Kshitij Goyal, Sebastijan Dumancic, Hendrik Blockeel

Fast and Controllable Post-training Sparsity: Learning Optimal Sparsity Allocation with Global Constraint in Minutes

Ruihao Gong, Yang Yong, Zining Wang, Jinyang Guo, Xiuying Wei

Layer Compression of Deep Networks with Straight Flows

Chengyue Gong, Xiaocong Du, Bhargav Bhushanam, Lemeng Wu, Xingchao Liu

Interactive Hyperparameter Optimization in Multi-Objective Problems via Preference Learning

Joseph Giovanelli, Alexander Tornede, Tanja Tornede, Marius Lindauer

Eliciting Kemeny Rankings

Anne-Marie George, Christos Dimitrakakis

AVSegFormer: Audio-Visual Segmentation with Transformer

Shengyi Gao, Zhe Chen, Guo Chen, Wenhai Wang, Tong Lu

Rethinking Causal Relationships Learning in Graph Neural Networks

Hang Gao, Chengyu Yao, Jiangmeng Li, Lingyu Si, Yifan Jin

Get a Head Start: On-Demand Pedagogical Policy Selection in Intelligent Tutoring

Ge Gao, Xi Yang, Min Chi

ACT: Empowering Decision Transformer with Dynamic Programming via Advantage Conditioning

Chen-Xiao Gao, Chenyang Wu, Mingjun Cao, Rui Kong, Zongzhang Zhang

Compressing Image-to-Image Translation GANs Using Local Density Structures on Their Learned Manifold

Alireza Ganjdanesh, Shangqian Gao, Hirad Alipanah, Heng Huang

Online Sensitivity Optimization in Differentially Private Learning

Filippo Galli, Catuscia Palamidessi, Tommaso Cucinotta

Learning Small Decision Trees with Few Outliers: A Parameterized Perspective

Harmender Gahlawat, Meirav Zehavi

Noise-Aware Image Captioning with Progressively Exploring Mismatched Words

Zhongtian Fu, Kefei Song, Luping Zhou, Yang Yang

DTL: Disentangled Transfer Learning for Visual Recognition

Minghao Fu, Ke Zhu, Jianxin Wu

QLABGrad: A Hyperparameter-Free and Convergence-Guaranteed Scheme for Deep Learning

Minghan Fu, Fang-Xiang Wu

REGLO: Provable Neural Network Repair for Global Robustness Properties

Feisi Fu, Zhilu Wang, Weichao Zhou, Yixuan Wang, Jiameng Fan

Combinatorial Stochastic-Greedy Bandit

Fares Fourati, Christopher John Quinn, Mohamed-Slim Alouini, Vaneet Aggarwal

Fast Machine Unlearning without Retraining through Selective Synaptic Dampening

Jack Foster, Stefan Schoepf, Alexandra Brintrup

Symbolic Regression Enhanced Decision Trees for Classification Tasks

Kei Sen Fong, Mehul Motani

Beyond Expected Return: Accounting for Policy Reproducibility When Evaluating Reinforcement Learning Algorithms

Manon Flageat, Bryan Lim, Antoine Cully

Learning Broadcast Protocols

Dana Fisman, Noa Izsak, Swen Jacobs

Graph Learning in 4D: A Quaternion-Valued Laplacian to Enhance Spectral GCNs

Stefano Fiorini, Stefano Coniglio, Michele Ciavotta, Enza Messina

Harnessing Manycore Processors with Distributed Memory for Accelerated Training of Sparse and Recurrent Models

Jan Finkbeiner, Thomas Gmeinder, Mark Pupilli, Alexander Titterton, Emre Neftci

Partial Multi-View Clustering via Self-Supervised Network

Wei Feng, Guoshuai Sheng, Qianqian Wang, Quanxue Gao, Zhiqiang Tao

Latent Diffusion Transformer for Probabilistic Time Series Forecasting

Shibo Feng, Chunyan Miao, Zhong Zhang, Peilin Zhao

BaCon: Boosting Imbalanced Semi-supervised Learning via Balanced Feature-Level Contrastive Learning

Qianhan Feng, Lujing Xie, Shijie Fang, Tong Lin

SUF: Stabilized Unconstrained Fine-Tuning for Offline-to-Online Reinforcement Learning

Jiaheng Feng, Mingxiao Feng, Haolin Song, Wengang Zhou, Houqiang Li

Improving GNN Calibration with Discriminative Ability: Insights and Strategies

Yujie Fang, Xin Li, Qianyu Chen, Mingzhong Wang

Backdoor Adjustment via Group Adaptation for Debiased Coupon Recommendations

Junpeng Fang, Gongduo Zhang, Qing Cui, Caizhi Tang, Lihong Gu

Selective Focus: Investigating Semantics Sensitivity in Post-training Quantization for Lane Detection

Yunqian Fan, Xiuying Wei, Ruihao Gong, Yuqing Ma, Xiangguo Zhang

Dynamic Sub-graph Distillation for Robust Semi-supervised Continual Learning

Yan Fan, Yu Wang, Pengfei Zhu, Qinghua Hu

Neural Gaussian Similarity Modeling for Differential Graph Structure Learning

Xiaolong Fan, Maoguo Gong, Yue Wu, Zedong Tang, Jieyi Liu

Non-parametric Representation Learning with Kernels

Pascal Esser, Maximilian Fleissner, Debarghya Ghoshdastidar

PAC-Bayes Generalisation Bounds for Dynamical Systems including Stable RNNs

Deividas Eringis, John Leth, Zheng-Hua Tan, Rafael Wisniewski, Mihaly Petreczky

Learning Hybrid Dynamics Models with Simulator-Informed Latent States

Katharina Ensinger, Sebastian Ziesche, Sebastian Trimpe

Exact Inference for Continuous-Time Gaussian Process Dynamics

Katharina Ensinger, Nicholas Tagliapietra, Sebastian Ziesche, Sebastian Trimpe

Feature Transportation Improves Graph Neural Networks

Moshe Eliasof, Eldad Haber, Eran Treister

A Score-Based Deterministic Diffusion Algorithm with Smooth Scores for General Distributions

Karthik Elamvazhuthi, Xuechen Zhang, Matthew Jacobs, Samet Oymak, Fabio Pasqualetti

Double-Descent Curves in Neural Networks: A New Perspective Using Gaussian Processes

Ouns El Harzli, Bernardo Cuenca Grau, Guillermo Valle-Pérez, Ard A. Louis

Causal Adversarial Perturbations for Individual Fairness and Robustness in Heterogeneous Data Spaces

Ahmad-Reza Ehyaei, Kiarash Mohammadi, Amir-Hossein Karimi, Samira Samadi, Golnoosh Farnadi

Provably Powerful Graph Neural Networks for Directed Multigraphs

Beni Egressy, Luc von Niederhäusern, Jovan Blanuša, Erik Altman, Roger Wattenhofer

Roll with the Punches: Expansion and Shrinkage of Soft Label Selection for Semi-supervised Fine-Grained Learning

Yue Duan, Zhen Zhao, Lei Qi, Luping Zhou, Lei Wang

DGA-GNN: Dynamic Grouping Aggregation GNN for Fraud Detection

Mingjiang Duan, Tongya Zheng, Yang Gao, Gang Wang, Zunlei Feng

Shrinking Your TimeStep: Towards Low-Latency Neuromorphic Object Recognition with Spiking Neural Networks

Yongqi Ding, Lin Zuo, Mengmeng Jing, Pei He, Yongjun Xiao

Turning Waste into Wealth: Leveraging Low-Quality Samples for Enhancing Continuous Conditional Generative Adversarial Networks

Xin Ding, Yongwei Wang, Zuheng Xu

Multi-View Randomized Kernel Classification via Nonconvex Optimization

Xiaojian Ding, Fan Yang

Exploiting Label Skews in Federated Learning with Model Concatenation

Yiqun Diao, Qinbin Li, Bingsheng He

Conformal Autoregressive Generation: Beam Search with Coverage Guarantees

Nicolas Deutschmann, Marvin Alberts, María Rodríguez Martínez

Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations

Cedric Derstroff, Mattia Cerrato, Jannis Brugger, Jan Peters, Stefan Kramer

Semi-supervised TEE Segmentation via Interacting with SAM Equipped with Noise-Resilient Prompting

Sen Deng, Yidan Feng, Haoneng Lin, Yiting Fan, Alex Pui-Wai Lee

Self-Interpretable Graph Learning with Sufficient and Necessary Explanations

Jiale Deng, Yanyan Shen

SEA-GWNN: Simple and Effective Adaptive Graph Wavelet Neural Network

Swakshar Deb, Sejuti Rahman, Shafin Rahman

Iterative Regularization with k-support Norm: An Important Complement to Sparse Recovery

William de Vazelhes, Bhaskar Mukhoty, Xiao-Tong Yuan, Bin Gu

Learn the Force We Can: Enabling Sparse Motion Control in Multi-Object Video Generation

Aram Davtyan, Paolo Favaro

Inverse Weight-Balancing for Deep Long-Tailed Learning

Wenqi Dang, Zhou Yang, Weisheng Dong, Xin Li, GUANGMING Shi

Continual Vision-Language Retrieval via Dynamic Knowledge Rectification

Zhenyu Cui, Yuxin Peng, Xun Wang, Manyu Zhu, Jiahuan Zhou

Deletion-Robust Submodular Maximization with Knapsack Constraints

Shuang Cui, Kai Han, He Huang

BadRL: Sparse Targeted Backdoor Attack against Reinforcement Learning

Jing Cui, Yufei Han, Yuzhe Ma, Jianbin Jiao, Junge Zhang

Time-Aware Knowledge Representations of Dynamic Objects with Multidimensional Persistence

Baris Coskunuzer, Ignacio Segovia-Dominguez, Yuzhou Chen, Yulia R. Gel

Big Learning Expectation Maximization

Yulai Cong, Sijia Li

RLfOLD: Reinforcement Learning from Online Demonstrations in Urban Autonomous Driving

Daniel Coelho, Miguel Oliveira, Vitor Santos

Resource Efficient Deep Learning Hardware Watermarks with Signature Alignment

Joseph Clements, Yingjie Lao

Task-Driven Causal Feature Distillation: Towards Trustworthy Risk Prediction

Zhixuan Chu, Mengxuan Hu, Qing Cui, Longfei Li, Sheng Li

Meta-Reinforcement Learning via Exploratory Task Clustering

Zhendong Chu, Renqin Cai, Hongning Wang

Make RepVGG Greater Again: A Quantization-Aware Approach

Xiangxiang Chu, Liang Li, Bo Zhang

Lyapunov-Stable Deep Equilibrium Models

Haoyu Chu, Shikui Wei, Ting Liu, Yao Zhao, Yuto Miyatake

Graph-Based Prediction and Planning Policy Network (GP3Net) for Scalable Self-Driving in Dynamic Environments Using Deep Reinforcement Learning

Jayabrata Chowdhury, Venkataramanan Shivaraman, Suresh Sundaram, PB Sujit

A Provably Accurate Randomized Sampling Algorithm for Logistic Regression

Agniva Chowdhury, Pradeep Ramuhalli

Consistency-Guided Temperature Scaling Using Style and Content Information for Out-of-Domain Calibration

Wonjeong Choi, Jungwuk Park, Dong-Jun Han, Younghyun Park, Jaekyun Moon

DUEL: Duplicate Elimination on Active Memory for Self-Supervised Class-Imbalanced Learning

Won-Seok Choi, Hyundo Lee, Dong-Sig Han, Junseok Park, Heeyeon Koo

Unsupervised Object Interaction Learning with Counterfactual Dynamics Models

Jongwook Choi, Sungtae Lee, Xinyu Wang, Sungryull Sohn, Honglak Lee

SNN-PDE: Learning Dynamic PDEs from Data with Simplicial Neural Networks

Jae Choi, Yuzhou Chen, Huikyo Lee, Hyun Kim, Yulia R. Gel

Make Prompts Adaptable: Bayesian Modeling for Vision-Language Prompt Learning with Data-Dependent Prior

Youngjae Cho, HeeSun Bae, Seungjae Shin, Yeo Dong Youn, Weonyoung Joo

Operator-Learning-Inspired Modeling of Neural Ordinary Differential Equations

Woojin Cho, Seunghyeon Cho, Hyundong Jin, Jinsung Jeon, Kookjin Lee

Generalized Variational Inference via Optimal Transport

Jinjin Chi, Zhichao Zhang, Zhiyao Yang, Jihong Ouyang, Hongbin Pei

CUTS+: High-Dimensional Causal Discovery from Irregular Time-Series

Yuxiao Cheng, Lianglong Li, Tingxiong Xiao, Zongren Li, Jinli Suo

Arithmetic Feature Interaction Is Necessary for Deep Tabular Learning

Yi Cheng, Renjun Hu, Haochao Ying, Xing Shi, Jian Wu

Clarifying the Behavior and the Difficulty of Adversarial Training

Xu Cheng, Hao Zhang, Yue Xin, Wen Shen, Quanshi Zhang

FedGCR: Achieving Performance and Fairness for Federated Learning with Distinct Client Types via Group Customization and Reweighting

Shu-Ling Cheng, Chin-Yuan Yeh, Ting-An Chen, Eliana Pastor, Ming-syan Chen

Hierarchize Pareto Dominance in Multi-Objective Stochastic Linear Bandits

Ji Cheng, Bo Xue, Jiaxiang Yi, Qingfu Zhang

Instrumental Variable Estimation for Causal Inference in Longitudinal Data with Time-Dependent Latent Confounders

Debo Cheng, Ziqi Xu, Jiuyong Li, Lin Liu, Jixue Liu

Diagnosing and Rectifying Fake OOD Invariance: A Restructured Causal Approach

Ziliang Chen, Yongsen Zheng, Zhao-Rong Lai, Quanlong Guan, Liang Lin

Continuous Rotation Group Equivariant Network Inspired by Neural Population Coding

Zhiqiang Chen, Yang Chen, Xiaolong Zou, Shan Yu

TopoGCL: Topological Graph Contrastive Learning

Yuzhou Chen, Jose Frias, Yulia R. Gel

Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity

Yiyue Chen, Haris Vikalo, Chianing Wang

Pushing the Limit of Fine-Tuning for Few-Shot Learning: Where Feature Reusing Meets Cross-Scale Attention

Ying-Yu Chen, Jun-Wei Hsieh, Xin Li, Ming-Ching Chang

Progressive Poisoned Data Isolation for Training-Time Backdoor Defense

Yiming Chen, Haiwei Wu, Jiantao Zhou

Exact Policy Recovery in Offline RL with Both Heavy-Tailed Rewards and Data Corruption

Yiding Chen, Xuezhou Zhang, Qiaomin Xie, Xiaojin Zhu

Meta-Inverse Reinforcement Learning for Mean Field Games via Probabilistic Context Variables

Yang Chen, Xiao Lin, Bo Yan, Libo Zhang, Jiamou Liu

Exploiting Symmetric Temporally Sparse BPTT for Efficient RNN Training

Xi Chen, Chang Gao, Zuowen Wang, Longbiao Cheng, Sheng Zhou

DGPO: Discovering Multiple Strategies with Diversity-Guided Policy Optimization

Wentse Chen, Shiyu Huang, Yuan Chiang, Tim Pearce, Wei-Wei Tu

PG-LBO: Enhancing High-Dimensional Bayesian Optimization with Pseudo-Label and Gaussian Process Guidance

Taicai Chen, Yue Duan, Dong Li, Lei Qi, Yinghuan Shi

On the Unstable Convergence Regime of Gradient Descent

Shuo Chen, Jiaying Peng, Xiaolong Li, Yao Zhao

Deep Contrastive Graph Learning with Clustering-Oriented Guidance

Mulin Chen, Bocheng Wang, Xuelong Li

Audio Scanning Network: Bridging Time and Frequency Domains for Audio Classification

Liangwei Chen, Xiren Zhou, Huanhuan Chen

Efficient Algorithms for Non-gaussian Single Index Models with Generative Priors

Junren Chen, Zhaoqiang Liu

Discriminative Forests Improve Generative Diversity for Generative Adversarial Networks

Junjie Chen, Jiahao Li, Chen Song, Bin Li, Qingcai Chen