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Found 5 papers, 1 papers with code
Distributionally Robust Imitation Learning
We consider the imitation learning problem of learning a policy in a Markov Decision Process (MDP) setting where the reward function is not given, but demonstrations from experts are available.
Consistent Robust Adversarial Prediction for General Multiclass Classification
We propose a robust adversarial prediction framework for general multiclass classification.
Distributionally Robust Graphical Models
Our approach enjoys both the flexibility of incorporating customized loss metrics into its design as well as the statistical guarantee of Fisher consistency.
Adversarial Surrogate Losses for Ordinal Regression
Ordinal regression seeks class label predictions when the penalty incurred for mistakes increases according to an ordering over the labels.
Decomposition-Invariant Conditional Gradient for General Polytopes with Line Search
Frank-Wolfe (FW) algorithms with linear convergence rates have recently achieved great efficiency in many applications.
