石野_Towards Responsible Decision and Control via Implicit Networks (2)_watermark.pdf

1、RLChina 2023Towards Responsible Decision and Control via Implicit Networks石 野助理教授，研究员，博导2023-11-25ShanghaiTechResponsible AI LabDecision and Control in Real WorldsRoboticsFinanceHealth-careAutonomous DrivingSmart GridChargingAgent负责任AI安全高效隐私Explicit ModelsExplicit ModelsTraditional deep learning mod

2、elsExplicitly construct the relationship between input and outputComputeAn explicit layer is a differentiable parametric function.Deep neural networks are typically constructed by composing many explicit layers,then training end-to-end via backpropagation.Problems in Explicit ModelsUnreliableMemory-

3、InefficientExplicit ModelsTraditional deep learning modelsExplicitly construct the relationship between input and outputComputeImplicit ModelsExplicit ModelsTraditional deep learning modelsExplicitly construct the relationship between input and outputComputeImplicit ModelsImplicitly define the relat

4、ionship between input and outputThe relationship may be given by the optimization problems,equations,etc.Need to give the implicit gradient flowFind solution ofGradient FlowImplicit Gradient FlowImplicit networks1.Powerful representations:represent complex operations such asintegrating differential

5、equations,solving optimization problems,etc.2.Memory efficiency:no need to backpropagate through intermediatecomponents,via implicit function theorem.3.Simplicity:Ease and elegance of designing architectures.Implicit NetworksDeep Equilibrium Model21 Chen R T Q,Rubanova Y,Bettencourt J,et al.Neural o

6、rdinary differential equationsJ.Advances in neural information processing systems,2018,31.2 Bai S,Kolter J Z,Koltun V.Deep equilibrium modelsJ.Advances in Neural Information Processing Systems,2019,32.3 Amos B,Kolter J Z.Optnet:Differentiable optimization as a layer in neural networksC/International