CFP
The goal of ICAML is to provide a broad platform to the key areas in machine learning along with emphasizing various application sectors. It aims to bring together researchers, practitioners and scholars from both academia and industry to share their knowledge, exchange ideas and establish new collaborations.
The following topics arebeing included, but not limited to:
Artificial Intelligence, Deep Learning, Cognitive Computing, Image Analysis, Text Analytics, Speech Recognition, Natural Language Processing, Cyber and Cloud Security, Industry 4.0, Internet of Things, Manufacturing and retail Sector: Operational Issues & Challenges, Financial Analytics, Revenue Management, Health Sector Services, Marketing Operations & Efficiency Measures, Public Systems operations management, Systems Studies, Coastal-zone Management: best practices & operational issues, Applications of Mathematical & Statistical Models, Power generation and grids, Smart buildings and cities, Industrial optimization, Agriculture, forestry and other land use, Disaster management and relief, Ecosystems and natural resources, Extreme weather events, Data and voice communication, etc.
| I. Core Machine Learning Techniques | II. Manufacturing |
(1) Decision Tree (2) Neural networks (3) Bayesian methods (4) Linear discriminant and support vector machines (5) Instance based learning (6) Inductive logic programming (7) Model selection and error estimation (8) Unsupervised learning (9) Online, active and reinforcement learning (10) Computational and statistical learning theory | (1) Process optimization (2) Demand forecasting (3) Modeling of predictive purchase behavior (4) Predictive monitoring of maintenance requirement (5) Monitoring warranty expenses and liability (6) Predictive analytics for telematics |
| III. Retail | IV. Energy and Utilities |
(1) Recommender engines (2) Market segmentation (3) Cross-channel marketing (4) Predicting Customer ROI (5) Forecasting lifetime value (6) Inventory planning using predictive analytics | (1) Power Usage analytics (2) Carbon emission and trading (3) Energy demand forecasting (4) Customer-specific pricing (5) Smart grid management (6) Energy optimization |
| V. Travel and Hospitality | VI. Healthcare and Life Sciences |
(1) Dynamic pricing (2) Aircraft scheduling (3) Social media analytics (4) Analysis of consumer feedback (5) Resolution of consumer complaints (6) Identification of traffic patterns (7) Congestion management | (1) Alerts and diagnostics from real-time patient data (2) Disease identification and risk stratification (3) Patient triangle optimization (4) Proactive health management (5) Healthcare provider sentiment analysis |
| Ⅶ. Financial Services | |
(1) Regulatory risk analytics (2) Management of sales and marketing campaigns (3) Evaluation of credit worthiness |