7^th International Conference on Machine Learning Optimization Data Science (LOD 2021)

June 29 – July 2, 2021, England, UK

Scope & Topics

7^th International Conference on Machine Learning Optimization Data Science (LOD 2021) has established itself as a premier multidisciplinary conference in machine learning, computational optimization, knowledge discovery and data science. It provides an international forum for presentation of original multidisciplinary research results, as well as exchange and dissemination of innovative and practical development experiences.

Topics of Interest :

• Foundations, algorithms, models and theory of data science, including big data mining.
• Machine learning and statistical methods for big data.
• Machine Learning algorithms and models. Neural Networks and Learning Systems. Convolutional neural networks.
• Unsupervised, semi-supervised, and supervised Learning.
• Knowledge Discovery. Learning Representations. Representation learning for planning and reinforcement learning.
• Metric learning and kernel learning. Sparse coding and dimensionality expansion. Hierarchical models. Learning representations of outputs or states.
• Multi-objective optimization. Optimization and Game Theory. Surrogate-assisted Optimization. Derivative-free Optimization.
• Big data Mining from heterogeneous data sources, including text, semi-structured, spatio-temporal, streaming, graph, web, and multimedia data.
• Big Data mining systems and platforms, and their efficiency, scalability, security and privacy.
• Computational optimization. Optimization for representation learning. Optimization under Uncertainty
• Optimization algorithms for Real World Applications. Optimization for Big Data. Optimization and Machine Learning.
• Implementation issues, parallelization, software platforms, hardware
• Big Data mining for modeling, visualization, personalization, and recommendation.
• Big Data mining for cyber-physical systems and complex, time-evolving networks.
• Applications in social sciences, physical sciences, engineering, life sciences, web, marketing, finance, precision medicine, health informatics, medicine and other domains.

Paper Submission

Each paper submitted will be rigorously evaluated. The evaluation will ensure high interest and expertise of reviewers. Following the tradition of LOD, we expect high-quality papers in terms of their scientific contribution, rigor, correctness, novelty, clarity, quality of presentation and reproducibility of experiments.

Important Dates