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Iterative Feature Matching: Toward Provable Domain Generalization with Logarithmic Environments
To obtain useful guarantees, it is necessary to study data models that encode structure reflective of settings of interest.
A Statistical Framework for Low-bitwidth Training of Deep Neural Networks
For training ResNet-50 on ImageNet, our 5-bit block Householder quantizer achieves only 0.5% validation accuracy loss relative to QA T, comparable to the existing INT8 baseline.
Convolutional Generation of Textured 3D Meshes
This heavily restricts the degree of control over generated objects as well as the possible applications of such models.
LearningOptimalPredictiveChecklists
Checklists are simple decision aids that are often used to promote safety and reliability in clinical applications. In this paper, we present a method to learn checklists for clinical decision support. We represent predictive checklists as discrete linear classifiers with binary features and unit weights.
