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ConsistentNon-ParametricMethodsforMaximizing Robustness
Neural Information Processing Systems
Adversarially robust classification, that has been of much recent interest, is typically formulated as follows.
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Generalization Bound and Learning Methods for Data-Driven Projections in Linear Programming
Shinsaku Sakaue, The University of Tokyo and RIKEN AIP, Tokyo, Japan, sakaue@mist.i.u-tokyo.ac.jp, "3026 Taihei Oki, Hokkaido University, Hokkaido, Japan, oki@icredd.hokudai.ac.jp
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Given training data ofn-dimensional LPs, we learn ann k projection matrix withn>k.
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Subgraph Neural Networks
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"GraphSAINT: Graph Sampling Based Inductive Learning Method".
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