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Applications of the Multi-Constraint Most Probable Explanation Problem
Probabilistic models are often used in practice to represent and reason about uncertainty. A key reasoning task over them is finding the most probable assignment to all the unobserved variables given observations. This ...
AI Inspired Algorithms for Several Combinatorial Optimization Problems in Data Science
Combinatorial optimization is a class of problems that consists of finding an optimal solution from a finite set of feasible solutions. Many important problems in Data Science can be viewed as combinatorial optimization ...
Framework for Mapping Convolutional Neural Networks on FPGAs
Artificial Intelligence (AI) applications are on the rise. Recent advances in machine learning and deep learning have created various applications for medicine/healthcare, financial markets, security, entertainment, and ...
Validation and Interpretable Model Explanations for Synthesized Data in Healthcare
Recent advances in artificial intelligence (AI) based solutions for healthcare problems have led to the increased demands for quality accessible patient data and the functional understanding of the remarkable outcomes of ...