7th International Conference on Machine Learning Techniques (MLTEC 2026)

Memo

7th International Conference on Machine Learning Techniques (MLTEC 2026) December 19 ~ 20, 2026, Sydney, Australia https://mltec.org Scope 7th International Conference on Machine Learning Techniques (MLTEC 2026) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Machine Learning Techniques. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Machine Learning Techniques. Topics of interest  Advanced ML Systems, MLOps and Deployment Adversarial Robustness and Secure ML AI‑Hardware Co‑Design Auto ML and Hyperparameter Optimization Causal Machine Learning Climate Modeling and Environmental ML Computer Vision and Visual Learning Continual and Lifelong Learning Data Mining and Knowledge Discovery Diffusion Models for Non‑Vision Modalities Edge ML, TinyML and On‑Device Learning Embodied AI and Interactive Learning Evaluation, Benchmarking and Safety of Foundation Models Explainable and Interpretable ML Fairness, Accountability and Responsible ML Federated and Distributed Learning Fine‑Tuning, Alignment and Adaptation of Foundation Models Foundation Models: Architectures, Training and Adaptation Fraud Detection and Risk Modeling Generative AI: Diffusion, GANs and Autoregressive Models Graph Foundation Models Graph Machine Learning and GNNs Knowledge Graphs and Reasoning LLM Agents and Autonomous Decision‑Making LLM‑Based Software Engineering Machine Learning Applications Machine Learning for NLP Machine Translation Meta‑Learning and Few‑Shot Learning ML for Biology and Protein Modeling ML for Chemistry and Drug Discovery ML for Code and Program Synthesis ML for Cybersecurity and Threat Detection ML for Healthcare, Finance, Robotics and Science ML‑Accelerated Compilers Model‑Based RL and Generative Simulation Multi‑Agent Reinforcement Learning Multimodal Learning and Fusion Multimodal LLMs (Vision‑Language‑Audio) Neural Networks and Deep Learning Neuro‑Symbolic Learning Planning‑Enabled and Memory‑Augmented Agents Privacy‑Preserving ML and Differential Privacy Quantum Machine Learning Recommender Systems Reinforcement Learning and RLHF Representation Learning Responsible Foundation Models: Fairness, Safety and Governance Scalable FM Training, Distributed Compute and ML Infrastructure Scalable ML and Distributed Training Self‑Supervised and Contrastive Learning Sustainable AI Systems Temporal Transformers and Sequence Modeling Time‑Series Foundation Models Tool‑Using AI Systems Transfer Learning and Domain Adaptation Ubiquitous and Pervasive ML Vision‑Language‑Action Models (VLAMs) World Models and Predictive Simulation Learning XML, Databases and Structured Data Learning   Paper Submission Authors are invited to submit papers through the conference Submission System by August 22, 2026 . Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed). Selected papers from MLTEC 2026, after further revisions, will be published in the special issues of the following journals International Journal of Artificial Intelligence & Applications (IJAIA) Machine Learning and Applications: An International Journal (MLAIJ) International Journal of Ubiquitous Computing (IJU) Advances in Vision Computing: An International Journal (AVC) Important Dates Submission Deadline : August 22, 2026 Authors Notification : October 10, 2026 Registration & Camera-Ready Paper Due : October 17, 2026 Contact Us Here’s where you can reach us : This email address is being protected from spambots. You need JavaScript enabled to view it. or This email address is being protected from spambots. You need JavaScript enabled to view it.