Scalarization is a general technique that can be deployed in any
multiob...
Model overconfidence and poor calibration are common in machine learning...
We study dynamic algorithms robust to adaptive input generated from sour...
We consider the problem of minimizing the number of matrix-vector querie...
Meta-learning hyperparameter optimization (HPO) algorithms from prior
ex...
Can deep learning solve multiple tasks simultaneously, even when they ar...
Large neural network models have been successful in learning functions o...
The tremendous success of deep neural networks has motivated the need to...
Many convex problems in machine learning and computer science share the ...
We consider the phylogenetic tree reconstruction problem with insertions...