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Found 4 papers, 1 papers with code
Test-time Detection and Repair of Adversarial Samples via Masked Autoencoder
Test-time defenses solve these issues but most existing test-time defenses require adapting the model weights, therefore they do not work on frozen models and complicate model memory management.
The First AI4TSP Competition: Learning to Solve Stochastic Routing Problems
Overall, by organizing this competition we have introduced routing problems as an interesting problem setting for AI researchers.
Learning How to Optimize Black-Box Functions With Extreme Limits on the Number of Function Evaluations
We tune this method for black box optimization and then evaluate on classical black box optimization benchmarks.
Cost-sensitive Hierarchical Clustering for Dynamic Classifier Selection
We introduce some additions to the original CSHC method for the special case of choosing a classification algorithm and evaluate their impact on performance.
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