Overview
Federated Multi-Objective Learning
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In recent years, multi-objective optimization (MOO) emerges as a foundational problem underpinning many multi-agent multi-task learning applications.
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DORIS-MAE: Scientific Document Retrieval using Multi-level Aspect-based Queries
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This highlights the need for better approaches to handle complex, multifaceted queries in scientific research.
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Actor-Critic Policy Optimization in Partially Observable Multiagent Environments
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Optimization of parameterized policies for reinforcement learning (RL) is an important and challenging problem in artificial intelligence.
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