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ORCID28th PAKDD 2024: Taipei, Taiwan - Part II
- De-Nian Yang
, Xing Xie, Vincent S. Tseng, Jian Pei, Jen-Wei Huang, Jerry Chun-Wei Lin:
Advances in Knowledge Discovery and Data Mining - 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, May 7-10, 2024, Proceedings, Part II. Lecture Notes in Computer Science 14646, Springer 2024, ISBN 978-981-97-2252-5
Deep Learning
- Yan-Ting Ye, Ting-An Chen, Ming-Syan Chen:
AdaPQ: Adaptive Exploration Product Quantization with Adversary-Aware Block Size Selection Toward Compression Efficiency. 3-14 - Ziheng Zhou, Ying Zhao, Haojia Zuo, Wenguang Chen:
Ranking Enhanced Supervised Contrastive Learning for Regression. 15-27 - Xiaofeng Lin, Guoxi Zhang, Xiaotian Lu, Hisashi Kashima:
Treatment Effect Estimation Under Unknown Interference. 28-42 - Alexandru Ghita, Radu Tudor Ionescu:
A New Loss for Image Retrieval: Class Anchor Margin. 43-54 - Yu-Hsiu Chen, Zhi Rui Tam, Hong-Han Shuai:
Personalized EDM Subject Generation via Co-factored User-Subject Embedding. 55-67 - Dimuthu Lakmal, Kushani Perera, Renata Borovica-Gajic, Shanika Karunasekera:
Spatial-Temporal Bipartite Graph Attention Network for Traffic Forecasting. 68-80 - Zhijie Qu, Juan Li, Zerui Ma, Jianqiang Li:
CMed-GPT: Prompt Tuning for Entity-Aware Chinese Medical Dialogue Generation. 81-92 - Lin Chen, Yuxin Zhou, Xiaobo Zhang, Zhehao Zhang, Hailong Zheng:
MvRNA: A New Multi-view Deep Neural Network for Predicting Parkinson's Disease. 93-104 - Ziye Luo, Ying Xiong, Buzhou Tang:
Path-Aware Cross-Attention Network for Question Answering. 105-117 - Andrzej Bedychaj, Jacek Tabor, Marek Smieja:
StyleAutoEncoder for Manipulating Image Attributes Using Pre-trained StyleGAN. 118-130 - Binh Minh Le, Simon S. Woo:
SEE: Spherical Embedding Expansion for Improving Deep Metric Learning. 131-143 - Nicholas Majeske, Ariful Azad:
Multi-modal Recurrent Graph Neural Networks for Spatiotemporal Forecasting. 144-157 - Bokyeong Yoon, Yoonsang Han, Gordon Euhyun Moon:
Layer-Wise Sparse Training of Transformer via Convolutional Flood Filling. 158-170 - Yi Zhang, Sen Wang, Zhi Chen, Xuwei Xu, Stano Funiak, Jiajun Liu:
Towards Cost-Efficient Federated Multi-agent RL with Learnable Aggregation. 171-183 - Kyeongman Park, Nakyeong Yang, Kyomin Jung:
LongStory: Coherent, Complete and Length Controlled Long Story Generation. 184-196 - Jeongho Kim, Simon S. Woo:
Relation-Aware Label Smoothing for Self-KD. 197-209 - Man-Jie Yuan, Zheng Zou, Wei Gao:
Bi-CryptoNets: Leveraging Different-Level Privacy for Encrypted Inference. 210-222 - Hanane Ariouat, Youcef Sklab, Marc Pignal, Florian Jabbour, Régine Vignes-Lebbe, Edi Prifti, Jean-Daniel Zucker, Eric Chenin:
Enhancing YOLOv7 for Plant Organs Detection Using Attention-Gate Mechanism. 223-234 - Chi Hong, Robert Birke, Pin-Yu Chen, Lydia Y. Chen:
On Dark Knowledge for Distilling Generators. 235-247 - Chi-Chang Li, Jay Huang, Wing-Kai Hon, Che-Rung Lee:
RPH-PGD: Randomly Projected Hessian for Perturbed Gradient Descent. 248-259 - Debolena Basak, P. K. Srijith, Maunendra Sankar Desarkar:
Transformer based Multitask Learning for Image Captioning and Object Detection. 260-272 - Fengda Zhu, Vincent CS Lee, Rui Liu:
Communicative and Cooperative Learning for Multi-agent Indoor Navigation. 273-285 - Hanbing Liu, Jingge Wang, Xuan Zhang, Ye Guo, Yang Li:
Enhancing Continuous Domain Adaptation with Multi-path Transfer Curriculum. 286-298
Graphs and Networks
- Lili Wang, Chenghan Huang, Ruiye Yao, Chongyang Gao, Weicheng Ma, Soroush Vosoughi:
Enhancing Network Role Modeling: Introducing Attributed Multiplex Structural Role Embedding for Complex Networks. 301-313 - Guangmo Tong, Peng Zhao, Mina Samizadeh:
Query-Decision Regression Between Shortest Path and Minimum Steiner Tree. 314-326 - Yunchao Zhang, Kewen Liao, Zhibin Liao, Longkun Guo:
Enhancing Policy Gradient for Traveling Salesman Problem with Data Augmented Behavior Cloning. 327-338 - Hui-Ju Hung, Wang-Chien Lee, Chih-Ya Shen, Fang He, Zhen Lei:
Leveraging Transfer Learning for Enhancing Graph Optimization Problem Solving. 339-351 - Xianren Zhang, Jing Ma, Yushun Dong, Chen Chen, Min Gao, Jundong Li:
SD-Attack: Targeted Spectral Attacks on Graphs. 352-363 - Mi Wen, Hongwei Wang, Yunsheng Xue, Yi Wu, Hong Wen:
Improving Structural and Semantic Global Knowledge in Graph Contrastive Learning with Distillation. 364-375 - Tai Hasegawa, Sukwon Yun, Xin Liu, Yin Jun Phua, Tsuyoshi Murata:
DEGNN: Dual Experts Graph Neural Network Handling both Edge and Node Feature Noise. 376-389 - Dongzhuoran Zhou, Hui Yang, Bo Xiong, Yue Ma, Evgeny Kharlamov:
Alleviating Over-Smoothing via Aggregation over Compact Manifolds. 390-404 - Qiang Sun, Du Q. Huynh, Mark Reynolds, Wei Liu:
Are Graph Embeddings the Panacea? - An Empirical Survey from the Data Fitness Perspective. 405-417 - Jae Won Choi, Yuzhou Chen, José Frías, Joel Castillo, Yulia R. Gel:
Revisiting Link Prediction with the Dowker Complex. 418-430 - Rui Shang, Siji Chen, Zhiqian Chen, Chang-Tien Lu:
GraphNILM: A Graph Neural Network for Energy Disaggregation. 431-443 - Yinon Horev, Shiraz Shay, Sarel Cohen, Tobias Friedrich, Davis Issac, Lior Kamma, Aikaterini Niklanovits, Kirill Simonov:
A Contraction Tree SAT Encoding for Computing Twin-Width. 444-456
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