Search Results for author:
Found 6 papers, 3 papers with code
Finite Sample Confidence Regions for Linear Regression Parameters Using Arbitrary Predictors
We explore a novel methodology for constructing confidence regions for parameters of linear models, using predictions from any arbitrary predictor.
Expecting The Unexpected: Towards Broad Out-Of-Distribution Detection
Our findings reveal that while these methods excel in detecting unknown classes, their performance is inconsistent when encountering other types of distribution shifts.
No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths
Understanding the optimization dynamics of neural networks is necessary for closing the gap between theory and practice.
Towards Out-of-Distribution Adversarial Robustness
Compared to existing methods, we obtain similar or superior worst-case adversarial robustness on attacks seen during training.
A Study of Condition Numbers for First-Order Optimization
Since smoothness and strong convexity are not continuous, we propose a comprehensive study of existing alternative metrics which we prove to be continuous.
InsectUp: Crowdsourcing Insect Observations to Assess Demographic Shifts and Improve Classification
Insects play such a crucial role in ecosystems that a shift in demography of just a few species can have devastating consequences at environmental, social and economic levels.
