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Parameter Disparities Dissection for Backdoor Defense in Heterogeneous Federated Learning Wenke Huang 1, Mang Y e
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Existing backdoor defense methods typically require either homogeneous assumption, validation datasets, or client optimization conflicts.
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Newton Informed Neural Operator for Solving Nonlinear Partial Differential Equations
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These methods can be broadly categorized into two types: function learning and operator learning approaches. In function learning, the goal is to directly learn the solution.
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Imitation learning (IL) aims to mimic the behavior of an expert in a sequential decision making task by learning from demonstrations, and has been widely applied
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Full experimental details are provided in Appendix C.
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