Artificial Neural Networks and Machine Learning ICANN 2023: 32nd International Conference on Artificial Neural Networks, Heraklion, Crete, Greece, September 2629, 2023, Proceedings, Part III 1st ed. 2023 [Mīkstie vāki]

Anomaly Detection in Directed Dynamic Graphs via RDGCN and
LSTAN.- Anomaly-Based Insider Threat Detection via Hierarchical Information
Fusion.- CSEDesc: CyberSecurity Event Detection with Event
Description.- GanNeXt: A New Convolutional GAN for Anomaly Detection.- K-Fold
Cross-Valuation for Machine Learning Using Shapley Value.- Malicious Domain
Detection Based on Self-supervised HGNNs with Contrastive Learning.- Time
Series Anomaly Detection with Reconstruction-Based State-Space
Models.- ReDualSVG: Refined Scalable Vector Graphics Generation.- Rethinking
Feature Context in Learning Image-guided Depth Completion.- Semantic and
Frequency Representation Mining for Face Manipulation Detection.- Single
image dehazing network based on serial feature attention.- SS-Net: 3D
Spatial-Spectral Network for Cerebrovascular Segmentation in TOF-MRA.- STAN:
Spatio-Temporal Alignment Network for No-Reference Video Quality
Assessment.- Style Expansion without Forgetting for Handwritten Character
Recognition.- TransVQ-VAE: Generating Diverse Images using Hierarchical
Representation Learning.- UG-Net: Unsupervised-Guided Network for Biomedical
Image Segmentation and Classification.- Unsupervised Shape Enhancement and
Factorization Machine Network for 3D Face Reconstruction.- Visible-Infrared
Person Re-Identification via Modality Augmentation and Center
Constraints.- Water Conservancy Remote Sensing Image Classification Based on
Target-Scene Deep Semantic Enhancement.- A Partitioned Detection Architecture
for Oriented Objects.- A Personalized Federated Multi-Task Learning Scheme
for Encrypted Traffic Classification.- Addressing delays in Reinforcement
Learning via Delayed Adversarial Imitation Learning.- An Evaluation of
Self-Supervised Learning for Portfolio Diversification.- An
exploitation-enhanced Bayesian optimization algorithm for high-dimensional
expensive problems.- Balancing Selection and Diversity in Ensemble Learning
with Exponential Mixture Model.- CIPER: Combining Invariant and Equivariant
Representations Using Contrastive and Predictive Learning.- Contrastive
Learning and the Emergence of Attributes Associations.- Contrastive Learning
for Sleep Staging based on Inter Subject Correlation.- Diffusion Policies as
Multi-Agent Reinforcement Learning Strategies.- Dynamic Memory-based
Continual Learning with Generating and Screening.- Enhancing Text2SQL
Generation with Syntactic Infor-mation and Multi-Task Learning.- Fast
Generalizable Novel View Synthesis with Uncertainty-Aware Sampling.- Find
Important Training Dataset by Observing the Training Sequence
Similarity.- Generating Question-Answer Pairs for Few-shot
Learning.- GFedKRL: Graph Federated Knowledge Re-Learning for Effective
Molecular Property Prediction via Privacy Protection.- Gradient-Boosted Based
Structured and UnstructuredLearning.- Graph Federated Learning Based on the
Decentralized Framework.- Heterogeneous Federated Learning Based on Graph
Hypernetwork.- Learning to Resolve Conflicts in Multi-Task
Learning.- Neighborhood-oriented Decentralized Learning Communication in
Multi-Agent System.- NN-Denoising: A Low-Noise Distantly Supervised
Document-Level Relation Extraction Scheme using Natural Language Inference
and Negative Sampling.- pFedLHNs: Personalized Federated Learning via Local
Hypernetworks.- Prototype Contrastive Learning for Personalized Federated
Learning.- PTSTEP: Prompt Tuning for Semantic Typing of Event
Processes.- SR-IDS: A Novel Network Intrusion Detection System Based on
Self-taught Learning and Representation Learning.- Task-Aware Adversarial
Feature Perturbation for Cross-Domain Few-Shot Learning.- Ternary Data,
Triangle Decoding, Three Tasks, a Multitask Learning Speech Translation Model.