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

Algorithm

Approximation and Random Algorithms

Combinatorial Optimization Algorithms

Parallel and Distributed Algorithms

High-Performance Numerical Algorithms

Evolutionary and Genetic Algorithms

Algorithm and Model Benchmark Evaluation

Graph Theory and Network Algorithms

Convolutional Neural Network (CNN)

Recurrent Neural Network (RNN)

Generative Adversarial Network (GAN)

Neural Network Pruning and Quantization

Graph Neural Network (GNN)

Algorithm Design and Analysis

Ant Colony and Particle Swarm Optimization

Fundamentals of Quantum Algorithms

Multimodal Fusion Methods

Deep Learning

Self-supervised Learning Methods

Small Sample and Zero Sample Learning

Contrastive Learning and Representation Learning

Deep Learning Optimization Theory

Multi-task and Transfer Learning

Meta-Learning and Adaptive Learning

Reinforcement Learning and Decision Modeling

Federated Learning and Privacy Protection

Deep Learning Hardware Deployment

Dynamic Programming and Greedy Strategies

Transformer and Attention Mechanism

Interpretability and Visualization

Robustness and Adversarial Defense

Loss Function and Regularization

Object Detection and Instance Segmentation

Semantic and Panoramic Segmentation

Anomaly Detection and Outlier Analysis

Clustering and Dimensionality Reduction Techniques

Feature Selection and Extraction

Support Vector Machine and Traditional Classifiers

Deep Neural Network Architecture

Pattern Recognition

Lightweight and Efficient Models

Model Compression and Acceleration

Knowledge Distillation Technology

Fundamentals of Pattern Recognition

Image Classification and Recognition

Face and Biometric Recognition

Behavior and Action Recognition

Speech and Audio Pattern Analysis

Text and Cross-Modal Pattern Understanding

Spatio-Temporal Data Modeling

Bayesian and Probabilistic Graphical Models

Sequence Pattern Mining

Diffusion Models and Generative AI