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Omar Montasser 2019/06/10 15:06

Half-baked problems

This is an experiment where volunteers spend (at most) 5 minutes describing a research problem and plan of attack.

The goal is to exhibit a tiny seed (carrot?) from which a research collaboration can grow.

Omar Montasser - Problems on Robust Learnability:

  • For one-hidden layer neural networks with threshold/ReLU activations, are there gaps between proper/improper robust learning algorithms in terms of sample complexity?
  • Given some robustness criterion (i.e. a threat model), can we efficiently robustly PAC learn linear classifiers in the realizable setting?
  • Empirical/Theoretical analysis of boosting/bagging/smoothing procedures in the robust learning setting, going beyond robust empirical risk minimization.
half-baked_problems.txt · Last modified: 2019/06/10 15:16 by omontasser