AAAI 2023

2,023 papers

Design Amortization for Bayesian Optimal Experimental Design

Noble Kennamer, Steven Walton, Alexander Ihler

Variable-Based Calibration for Machine Learning Classifiers

Markelle Kelly, Padhraic Smyth

Communication-Efficient Collaborative Best Arm Identification

Nikolai Karpov, Qin Zhang

On the Sample Complexity of Vanilla Model-Based Offline Reinforcement Learning with Dependent Samples

Mustafa O. Karabag, Ufuk Topcu

PIXEL: Physics-Informed Cell Representations for Fast and Accurate PDE Solvers

Namgyu Kang, Byeonghyeon Lee, Youngjoon Hong, Seok-Bae Yun, Eunbyung Park

Identifying Selection Bias from Observational Data

David Kaltenpoth, Jilles Vreeken

Towards More Robust Interpretation via Local Gradient Alignment

Sunghwan Joo, SeokHyeon Jeong, Juyeon Heo, Adrian Weller, Taesup Moon

An Efficient Algorithm for Fair Multi-Agent Multi-Armed Bandit with Low Regret

Matthew Jones, Huy Nguyen, Thy Nguyen

POEM: Polarization of Embeddings for Domain-Invariant Representations

Sang-Yeong Jo, Sung Whan Yoon

Knowledge-Constrained Answer Generation for Open-Ended Video Question Answering

Yao Jin, Guocheng Niu, Xinyan Xiao, Jian Zhang, Xi Peng

Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problem

Yan Jin, Yuandong Ding, Xuanhao Pan, Kun He, Li Zhao

On Solution Functions of Optimization: Universal Approximation and Covering Number Bounds

Ming Jin, Vanshaj Khattar, Harshal Kaushik, Bilgehan Sel, Ruoxi Jia

Trafformer: Unify Time and Space in Traffic Prediction

Di Jin, Jiayi Shi, Rui Wang, Yawen Li, Yuxiao Huang

Local-Global Defense against Unsupervised Adversarial Attacks on Graphs

Di Jin, Bingdao Feng, Siqi Guo, Xiaobao Wang, Jianguo Wei

Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs

Rui Jiao, Jiaqi Han, Wenbing Huang, Yu Rong, Yang Liu

Complement Sparsification: Low-Overhead Model Pruning for Federated Learning

Xiaopeng Jiang, Cristian Borcea

Spatio-Temporal Meta-Graph Learning for Traffic Forecasting

Renhe Jiang, Zhaonan Wang, Jiawei Yong, Puneet Jeph, Quanjun Chen

Multi-View MOOC Quality Evaluation via Information-Aware Graph Representation Learning

Lu Jiang, Yibin Wang, Jianan Wang, Pengyang Wang, Minghao Yin

Robust Domain Adaptation for Machine Reading Comprehension

Liang Jiang, Zhenyu Huang, Jia Liu, Zujie Wen, Xi Peng

Online Tuning for Offline Decentralized Multi-Agent Reinforcement Learning

Jiechuan Jiang, Zongqing Lu

Learning from Training Dynamics: Identifying Mislabeled Data beyond Manually Designed Features

Qingrui Jia, Xuhong Li, Lei Yu, Jiang Bian, Penghao Zhao

MNER-QG: An End-to-End MRC Framework for Multimodal Named Entity Recognition with Query Grounding

Meihuizi Jia, Lei Shen, Xin Shen, Lejian Liao, Meng Chen

DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery – a Focus on Affinity Prediction Problems with Noise Annotations

Yuanfeng Ji, Lu Zhang, Jiaxiang Wu, Bingzhe Wu, Lanqing Li

Learnable Path in Neural Controlled Differential Equations

Sheo Yon Jhin, Minju Jo, Seungji Kook, Noseong Park

Confidence-Aware Training of Smoothed Classifiers for Certified Robustness

Jongheon Jeong, Seojin Kim, Jinwoo Shin

Audio-Visual Contrastive Learning with Temporal Self-Supervision

Simon Jenni, Alexander Black, John Collomosse

Neural Representations Reveal Distinct Modes of Class Fitting in Residual Convolutional Networks

Michał Jamroż, Marcin Kurdziel

Fast Regularized Discrete Optimal Transport with Group-Sparse Regularizers

Yasutoshi Ida, Sekitoshi Kanai, Kazuki Adachi, Atsutoshi Kumagai, Yasuhiro Fujiwara

Model-Based Reinforcement Learning with Multinomial Logistic Function Approximation

Taehyun Hwang, Min-hwan Oh

XClusters: Explainability-First Clustering

Hyunseung Hwang, Steven Euijong Whang

Learning Noise-Induced Reward Functions for Surpassing Demonstrations in Imitation Learning

Liangyu Huo, Zulin Wang, Mai Xu

Reward-Biased Maximum Likelihood Estimation for Neural Contextual Bandits: A Distributional Learning Perspective

Yu-Heng Hung, Ping-Chun Hsieh

Self-Supervised Graph Attention Networks for Deep Weighted Multi-View Clustering

Zongmo Huang, Yazhou Ren, Xiaorong Pu, Shudong Huang, Zenglin Xu

Enabling Knowledge Refinement upon New Concepts in Abductive Learning

Yu-Xuan Huang, Wang-Zhou Dai, Yuan Jiang, Zhi-Hua Zhou

Background-Mixed Augmentation for Weakly Supervised Change Detection

Rui Huang, Ruofei Wang, Qing Guo, Jieda Wei, Yuxiang Zhang

RLEKF: An Optimizer for Deep Potential with Ab Initio Accuracy

Siyu Hu, Wentao Zhang, Qiuchen Sha, Feng Pan, Lin-Wang Wang

Compressed Decentralized Learning of Conditional Mean Embedding Operators in Reproducing Kernel Hilbert Spaces

Boya Hou, Sina Sanjari, Nathan Dahlin, Subhonmesh Bose

Federated Robustness Propagation: Sharing Adversarial Robustness in Heterogeneous Federated Learning

Junyuan Hong, Haotao Wang, Zhangyang Wang, Jiayu Zhou

Towards Better Visualizing the Decision Basis of Networks via Unfold and Conquer Attribution Guidance

Jung-Ho Hong, Woo-Jeoung Nam, Kyu-Sung Jeon, Seong-Whan Lee

Improving Pareto Front Learning via Multi-Sample Hypernetworks

Long P. Hoang, Dung D. Le, Tran Anh Tuan, Tran Ngoc Thang

Self-Supervised Learning for Anomalous Channel Detection in EEG Graphs: Application to Seizure Analysis

Thi Kieu Khanh Ho, Narges Armanfard

Improving Long-Horizon Imitation through Instruction Prediction

Joey Hejna, Pieter Abbeel, Lerrel Pinto

Safeguarded Learned Convex Optimization

Howard Heaton, Xiaohan Chen, Zhangyang Wang, Wotao Yin

NAS-LID: Efficient Neural Architecture Search with Local Intrinsic Dimension

XIN HE, Jiangchao Yao, Yuxin Wang, Zhenheng Tang, Ka Chun Cheung

Estimating Regression Predictive Distributions with Sample Networks

Ali Harakeh, Jordan Sir Kwang Hu, Naiqing Guan, Steven Waslander, Liam Paull

Astromorphic Self-Repair of Neuromorphic Hardware Systems

Zhuangyu Han, A N M Nafiul Islam, Abhronil Sengupta

Discriminability and Transferability Estimation: A Bayesian Source Importance Estimation Approach for Multi-Source-Free Domain Adaptation

Zhongyi Han, Zhiyan Zhang, Fan Wang, Rundong He, Wan Su

Dream to Generalize: Zero-Shot Model-Based Reinforcement Learning for Unseen Visual Distractions

Jeongsoo Ha, Kyungsoo Kim, Yusung Kim

Boosting Graph Neural Networks via Adaptive Knowledge Distillation

Zhichun Guo, Chunhui Zhang, Yujie Fan, Yijun Tian, Chuxu Zhang

Self-Supervised Bidirectional Learning for Graph Matching

Wenqi Guo, Lin Zhang, Shikui Tu, Lei Xu

Graph Knows Unknowns: Reformulate Zero-Shot Learning as Sample-Level Graph Recognition

Jingcai Guo, Song Guo, Qihua ZHOU, Ziming Liu, Xiaocheng Lu

Interpolating Graph Pair to Regularize Graph Classification

Hongyu Guo, Yongyi Mao

An Adaptive Layer to Leverage Both Domain and Task Specific Information from Scarce Data

Gaël Guibon, Matthieu Labeau, Luce Lefeuvre, Chloé Clavel

Dynamic Representation Learning with Temporal Point Processes for Higher-Order Interaction Forecasting

Tony Gracious, Ambedkar Dukkipati

Deep Latent Regularity Network for Modeling Stochastic Partial Differential Equations

Shiqi Gong, Peiyan Hu, Qi Meng, Yue Wang, Rongchan Zhu

Adaptive Hierarchy-Branch Fusion for Online Knowledge Distillation

Linrui Gong, Shaohui Lin, Baochang Zhang, Yunhang Shen, Ke Li

Improving Uncertainty Quantification of Deep Classifiers via Neighborhood Conformal Prediction: Novel Algorithm and Theoretical Analysis

Subhankar Ghosh, Taha Belkhouja, Yan Yan, Janardhan Rao Doppa

Local Intrinsic Dimensional Entropy

Rohan Ghosh, Mehul Motani

DiFA: Differentiable Feature Acquisition

Aritra Ghosh, Andrew Lan

Differentially Private Heatmaps

Badih Ghazi, Junfeng He, Kai Kohlhoff, Ravi Kumar, Pasin Manurangsi

Multi-Classifier Adversarial Optimization for Active Learning

Lin Geng, Ningzhong Liu, Jie Qin

Semi-transductive Learning for Generalized Zero-Shot Sketch-Based Image Retrieval

Ce Ge, Jingyu Wang, Qi Qi, Haifeng Sun, Tong Xu

Learning Program Synthesis for Integer Sequences from Scratch

Thibault Gauthier, Josef Urban

Reinforced Approximate Exploratory Data Analysis

Shaddy Garg, Subrata Mitra, Tong Yu, Yash Gadhia, Arjun Kashettiwar

Handling Missing Data via Max-Entropy Regularized Graph Autoencoder

Ziqi Gao, Yifan Niu, Jiashun Cheng, Jianheng Tang, Lanqing Li

Long-Tail Cross Modal Hashing

Zijun Gao, Jun Wang, Guoxian Yu, Zhongmin Yan, Carlotta Domeniconi

Towards Decision-Friendly AUC: Learning Multi-Classifier with AUCµ

Peifeng Gao, Qianqian Xu, Peisong Wen, HuiYang Shao, Yuan He

Robust Causal Graph Representation Learning against Confounding Effects

Hang Gao, Jiangmeng Li, Wenwen Qiang, Lingyu Si, Bing Xu

Fast Counterfactual Inference for History-Based Reinforcement Learning

Haichuan Gao, Tianren Zhang, Zhile Yang, Yuqing Guo, Jinsheng Ren

EffConv: Efficient Learning of Kernel Sizes for Convolution Layers of CNNs

Alireza Ganjdanesh, Shangqian Gao, Heng Huang

Decorate the Newcomers: Visual Domain Prompt for Continual Test Time Adaptation

Yulu Gan, Yan Bai, Yihang Lou, Xianzheng Ma, Renrui Zhang

Estimating Average Causal Effects from Patient Trajectories

Dennis Frauen, Tobias Hatt, Valentyn Melnychuk, Stefan Feuerriegel

Optimal Decision Diagrams for Classification

Alexandre M. Florio, Pedro Martins, Maximilian Schiffer, Thiago Serra, Thibaut Vidal

SigMaNet: One Laplacian to Rule Them All

Stefano Fiorini, Stefano Coniglio, Michele Ciavotta, Enza Messina

Scalable Attributed-Graph Subspace Clustering

Chakib Fettal, lazhar labiod, Mohamed NADIF

Combinatorial Causal Bandits

Shi Feng, Wei Chen

Wasserstein Graph Distance Based on L1–Approximated Tree Edit Distance between Weisfeiler–Lehman Subtrees

Zhongxi Fang, Jianming Huang, Xun Su, Hiroyuki Kasai

Learning Decomposed Spatial Relations for Multi-Variate Time-Series Modeling

Yuchen Fang, Kan Ren, Caihua Shan, Yifei Shen, You Li

Dish-TS: A General Paradigm for Alleviating Distribution Shift in Time Series Forecasting

Wei Fan, Pengyang Wang, Dongkun Wang, Dongjie Wang, Yuanchun Zhou

Directed Acyclic Graph Structure Learning from Dynamic Graphs

Shaohua Fan, Shuyang Zhang, Xiao Wang, Chuan Shi

Goal-Conditioned Generators of Deep Policies

Francesco Faccio, Vincent Herrmann, Aditya Ramesh, Louis Kirsch, Jürgen Schmidhuber

FairFed: Enabling Group Fairness in Federated Learning

Yahya H. Ezzeldin, Shen Yan, Chaoyang He, Emilio Ferrara, A. Salman Avestimehr

Andrew Estornell, Sanmay Das, Brendan Juba, Yevgeniy Vorobeychik

Combining Slow and Fast: Complementary Filtering for Dynamics Learning

Katharina Ensinger, Sebastian Ziesche, Barbara Rakitsch, Michael Tiemann, Sebastian Trimpe

Diffeomorphic Information Neural Estimation

Bao Duong, Thin Nguyen

Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View

Jingcan Duan, Siwei Wang, Pei Zhang, En Zhu, Jingtao Hu

Robust and Fast Measure of Information via Low-Rank Representation

Yuxin Dong, Tieliang Gong, Shujian Yu, Hong Chen, Chen Li

Interpreting Unfairness in Graph Neural Networks via Training Node Attribution

Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li

Can Label-Specific Features Help Partial-Label Learning?

Ruo-Jing Dong, Jun-Yi Hang, Tong Wei, Min-ling Zhang

Model-Based Offline Reinforcement Learning with Local Misspecification

Kefan Dong, Yannis Flet-Berliac, Allen Nie, Emma Brunskill

SKDBERT: Compressing BERT via Stochastic Knowledge Distillation

Zixiang Ding, Guoqing Jiang, SHUAI ZHANG, Lin Guo, Wei LIN

Non-stationary Risk-Sensitive Reinforcement Learning: Near-Optimal Dynamic Regret, Adaptive Detection, and Separation Design

Yuhao Ding, Ming Jin, Javad Lavaei

Provably Efficient Primal-Dual Reinforcement Learning for CMDPs with Non-stationary Objectives and Constraints

Yuhao Ding, Javad Lavaei

Incremental Reinforcement Learning with Dual-Adaptive ε-Greedy Exploration

Wei Ding, Siyang Jiang, Hsi-Wen Chen, Ming-syan Chen

Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning

Kaize Ding, Yancheng Wang, Yingzhen Yang, Huan Liu

C-NTPP: Learning Cluster-Aware Neural Temporal Point Process

Fangyu Ding, Junchi Yan, Haiyang Wang

Black-Box Adversarial Attack on Time Series Classification

Daizong Ding, Mi Zhang, Fuli Feng, Yuanmin Huang, Erling Jiang

Integer Subspace Differential Privacy

Prathamesh Dharangutte, Jie Gao, Ruobin Gong, Fang-Yi Yu

Stability-Based Generalization Analysis of the Asynchronous Decentralized SGD

Xiaoge Deng, Tao Sun, Shengwei Li, Dongsheng Li

Non-reversible Parallel Tempering for Deep Posterior Approximation

Wei Deng, Qian Zhang, Qi Feng, Faming Liang, Guang Lin