Online Estimation via Offline Estimation: An Information-Theoretic Framework Dylan J. Foster
The classical theory of statistical estimation aims to estimate a parameter of interest under data generated from a fixed design ("offline estimation"), while the contemporary theory of online learning provides algorithms for estimation under adaptively
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Neural Networks with Cheap Differential Operators
Tian Qi Chen, David K. Duvenaud
Neural Information Processing Systems http://nips.cc/
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Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions
Sara Magliacane, Thijs van Ommen, Tom Claassen, Stephan Bongers, Philip Versteeg, Joris M. Mooij
Neural Information Processing Systems http://nips.cc/
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Improved Sample Complexity for Multiclass PAC Learning
We aim to understand the optimal P AC sample complexity in multiclass learning.
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