Scope & Topics

by admin last modified Jan 12, 2019 11:44 AM
The 3rd International Conference on Applied Cognitive Computing (ACC'19)
ll researchers, authors and scientists are respectfully encouraged to contribute to the conference with submissions of their novel research papers having unpublished and original research with theoretical, mathematical, empirical and experimental work in the following arears of applied cognitive computing and are cordially invited for presentation at the conference. 

    • Novel Computationally Intelligent algorithms
    • Bio Inspired Cognitive Algorithms
    • Improving Cognition in machine learning systems
    • Modeling Human Brain processing systems
    • Multimodal learning systems
    • Autonomous learning systems
    • Reinforced learning
    • Cognitive evolution
    • Concept Drift and Evolution
    • Cognitive inferential systems
    • Cognitive improvement in deep learning networks
    • Hebbian Learning Systems
    • Advancements in Neural Networks
    • Fuzzy Engineering
    • Multiscale Learning systems
    • Fractal based learning and decision support systems
    • Application of chaos Engineering in machine intelligence
    • Dynamical learning systems
    • Application of Information Theory in Machine Intelligence
    • Application of linear and nonlinear optimization theory in machine intelligence
    • New algorithms for Predictive Analytics and Applied Data Science
    • Self-Adaptive and Self Organizing Systems
    • Manifold and Metric learning
    • Cognitive Modeling, Visualization and Analytics of Big Data
    • Application of Graph Theoretic approaches in dimensionality reduction and machine intelligence
    • Information and Knowledge retrieval and searching algorithms
    • Big data knowledge mining
    • Mathematical modeling of Big Data and Artificial Intelligence
    • Cognitive Signal Processing
    • Rough Set Theory
    • Knowledge Representation and Classification Systems
    • Agent Based Modeling in Machine Learning Systems
    • Information Processing and Decision Making Systems
    • Natural Language Processing
    • Big Data Fusion and Information Retrieval
    • Time and Space Analysis in Machine Learning
    • New application of classical stochastic and statistical analysis for big data machine learning
    • Bayesian modeling applications
    • Hierarchical learning systems
    • Cognition in Genetic and Evolutionary algorithms for learning and decision making
    • Nature inspired cognitive computing algorithms
    • Heuristic Analysis
    • Cognitive Feature Extraction
    • Extraction of latent semantics from big data
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