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Abstract: This work studies black-box adversarial attacks against deep neural networks, where the attacker only has access to the query feedback from the target model. The current state-of-the-art ...

Mission: Deliver a modern database that seamlessly integrates traditional RDBMS capabilities with cutting-edge features like vector search, temporal queries, adaptive compression, and comprehensive ...

Abstract: With limited labeled samples, few-shot classification poses a challenge to standard deep models and has attracted a surge of concern. Metric learning based approaches stand out for the ...