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A Survey of Decomposition-Based Evolutionary Multi-Objective Optimization: Part II -- A Data Science Perspective
This paper presents the second part of the two-part survey series on decomposition-based evolutionary multi-objective optimization where we mainly focus on discussing the literature related to multi-objective evolutionary algorithms based on decomposition (MOEA/D).
Towards the Inferrence of Structural Similarity of Combinatorial Landscapes
However, due to the black-box nature of combinatorial optimization, it is far from trivial to infer such similarity in real-world scenarios.
On the Hyperparameter Landscapes of Machine Learning Algorithms
Despite the recent success in a plethora of hyperparameter optimization (HPO) methods for machine learning (ML) models, the intricate interplay between model hyperparameters (HPs) and predictive losses (a. k. a fitness), which is a key prerequisite for understanding HPO, remain notably underexplored in our community.
Detecting Violations of Differential Privacy for Quantum Algorithms
Quantum algorithms for solving a wide range of practical problems have been proposed in the last ten years, such as data search and analysis, product recommendation, and credit scoring.
Unlocking the Secrets of Software Configuration Landscapes-Ruggedness, Accessibility, Escapability, and Transferability
Modern software systems are often highly configurable to tailor varied requirements from diverse stakeholders.
MAssistant: A Personal Knowledge Assistant for MOOC Learners
Massive Open Online Courses (MOOCs) have developed rapidly and attracted large number of learners.
