2026 International Conference on Algorithms, Deep Learning, and Pattern Recognition

Algorithm Design and Analysis Approximation and Random Algorithms Combinatorial Optimization Algorithms Graph Theory and Network Algorithms Dynamic Programming and Greedy Strategies Parallel and Distributed Algorithms High-Performance Numerical Algorithms Fundamentals of Quantum Algorithms Evolutionary and Genetic Algorithms Ant Colony and Particle Swarm Optimization Deep Neural Network Architecture Convolutional Neural Network (CNN) Recurrent Neural Network (RNN) Transformer and Attention Mechanism Self-supervised Learning Methods Small Sample and Zero Sample Learning Contrastive Learning and Representation Learning Generative Adversarial Network (GAN) Diffusion Models and Generative AI Lightweight and Efficient Models Model Compression and Acceleration Neural Network Pruning and Quantization Knowledge Distillation Technology Interpretability and Visualization Robustness and Adversarial Defense Deep Learning Optimization Theory Loss Function and Regularization Multi-task and Transfer Learning Meta-Learning and Adaptive Learning Fundamentals of Pattern Recognition Image Classification and Recognition Object Detection and Instance Segmentation Semantic and Panoramic Segmentation Face and Biometric Recognition Behavior and Action Recognition Speech and Audio Pattern Analysis Text and Cross-Modal Pattern Understanding Multimodal Fusion Methods Graph Neural Network (GNN) Spatio-Temporal Data Modeling Anomaly Detection and Outlier Analysis Clustering and Dimensionality Reduction Techniques Feature Selection and Extraction Bayesian and Probabilistic Graphical Models Support Vector Machine and Traditional Classifiers Sequence Pattern Mining Reinforcement Learning and Decision Modeling Federated Learning and Privacy Protection Deep Learning Hardware Deployment Algorithm and Model Benchmark Evaluation