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ORCID33rd ICANN 2024: Lugano, Switzerland - Part I
- Michael Wand
, Kristína Malinovská, Jürgen Schmidhuber, Igor V. Tetko:
Artificial Neural Networks and Machine Learning - ICANN 2024 - 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17-20, 2024, Proceedings, Part I. Lecture Notes in Computer Science 15016, Springer 2024, ISBN 978-3-031-72331-5
Theory of Neural Networks and Machine Learning
- Yunya Zhou, Bin Yuan, Yan Zhong, Yuling Li:
Multi-label Robust Feature Selection via Subspace-Sparsity Learning. 3-17 - Dominique Martinez, Mohamed Boutayeb:
Nullspace-Based Metric for Classification of Dynamical Systems and Sensors. 18-29 - Jan Kalina, Petra Vidneroá:
On the Bayesian Interpretation of Robust Regression Neural Networks. 30-40 - Theodore Papamarkou, Alexey Lindo:
Probability-Generating Function Kernels for Spherical Data. 41-59 - Ye Li, Ting Du, Zhongyi Huang:
Tailored Finite Point Operator Networks for Interface Problems. 60-72
Novel Methods in Machine Learning
- Qian Qiao, Yu Xie, Shaoyao Huang, Fanzhang Li:
A Simple Task-Aware Contrastive Local Descriptor Selection Strategy for Few-Shot Learning Between Inter Class and Intra Class. 75-88 - Gabriela Sejnova, Michal Vavrecka, Karla Stépánová:
Adaptive Compression of the Latent Space in Variational Autoencoders. 89-101 - Dominik Olszewski:
Asymmetric Isomap for Dimensionality Reduction and Data Visualization. 102-115 - Lorenzo S. Querol, Hajime Nagahara, Hideaki Hayashi:
CALICO: Confident Active Learning with Integrated Calibration. 116-130 - Mengyu Luo, Jianxia Chen, Qi Yan, Gaohang Jiang, Shi Dong, Liang Xiao, Zhongwei Huang:
Improved Multi-hop Reasoning Through Sampling and Aggregating. 131-146 - Alan A. Lahoud, Erik Schaffernicht, Johannes A. Stork:
Learning Solutions of Stochastic Optimization Problems with Bayesian Neural Networks. 147-162 - Kathleen Anderson, Thomas Martinetz:
Revealing Unintentional Information Leakage in Low-Dimensional Facial Portrait Representations. 163-177 - Diwen Liu, Xiaodong Yue, Zhikang Xu:
Safe Data Resampling Method Based on Counterfactuals Analysis. 178-193 - Ryo Ishiyama, Takahiro Shirakawa, Seiichi Uchida, Shinnosuke Matsuo:
Test-Time Augmentation for Traveling Salesperson Problem. 194-208
Novel Neural Architectures
- Robert Deibel, Shahram Eivazi, Matrin V. Butz, Sebastian Otte:
Resonator-Gated RNNs. 211-225 - Matej Fandl, Martin Takác:
Towards a Model of Associative Memory with Learned Distributed Representations. 226-241
Neural Architecture Search
- Houssem Ouertatani, Cristian Maxim, Smaïl Niar, El-Ghazali Talbi:
Accelerated NAS via Pretrained Ensembles and Multi-fidelity Bayesian Optimization. 245-260 - Di Wang, Xunzhi Xiang, Kun Jing, Jungang Xu:
Feature Activation-Driven Zero-Shot NAS: A Contrastive Learning Framework. 261-276 - Di Wang, Kun Jing, Jungang Xu:
NAS-Bench-Compre: A Comprehensive Neural Architecture Search Benchmark with Customizable Components. 277-291 - Kazuki Hemmi, Yuki Tanigaki, Masaki Onishi:
NAVIGATOR-D3: Neural Architecture Search Using VarIational Graph Auto-encoder Toward Optimal aRchitecture Design for Diverse Datasets. 292-307 - Julian Burghoff, Matthias Rottmann, Jill von Conta, Sebastian Schoenen, Andreas Witte, Hanno Gottschalk:
ResBuilder: Automated Learning of Depth with Residual Structures. 308-323
Self-Organization
- Alberto Ortiz:
A Neuron Coverage-Based Self-organizing Approach for RBFNNs in Multi-class Classification Tasks. 327-342 - Kazuki Irie, Róbert Csordás, Jürgen Schmidhuber:
Self-organising Neural Discrete Representation Learning à la Kohonen. 343-362
Neural Processes
- Jinyang Tai, Yike Guo:
Combined Global and Local Information Diffusion of Neural Processes. 365-380 - Jinyang Tai, Yike Guo:
Topology of Neural Processes. 381-401
Novel Architectures for Computer Vision
- Shanshan Zhong, Wushao Wen, Jinghui Qin, Zhongzhan Huang:
DEEPAM: Toward Deeper Attention Module in Residual Convolutional Neural Networks. 405-418 - Xinshuang Liu, Yue Zhao:
Differentiable Largest Connected Component Layer for Image Matting. 419-431 - Christoph Linse, Beatrice Brückner, Thomas Martinetz:
Enhancing Generalization in Convolutional Neural Networks Through Regularization with Edge and Line Features. 432-446 - Zhenhai Wang, Hui Chen, Lutao Yuan, Ying Ren, Hongyu Tian:
Transformer Tracker Based on Multi-level Residual Perception Structure. 447-460
Fairness in Machine Learning
- Simiao Zhang, Jitao Bai, Menghong Guan, Yueling Zhang, Jun Sun, Yihao Huang, Jiaping Wang, ChengCheng Wan, Ting Su, Geguang Pu:
CFP: A Reinforcement Learning Framework for Comprehensive Fairness-Performance Trade-Off in Machine Learning. 463-477
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