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Optimizing Dynamic Structures with Bayesian Generative Search
Kernel selection for kernel-based methods is prohibitively expensive due to the NP-hard nature of discrete optimization.
Personalized Neural Architecture Search for Federated Learning
Federated Learning (FL) is a recently proposed learning paradigm for decentralized devices to collaboratively train a predictive model without exchanging private data.
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review
Machine learning plays a role in many deployed decision systems, often in ways that are difficult or impossible to understand by human stakeholders.
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