Algorithms
How good is your classifier? Revisiting the role of evaluation metrics in machine learning
With the increasing integration of machine learning into real systems, it is crucial that trained models are optimized to reflect real-world tradeoffs. Increasing interest in proper evaluation has led to a wide variety of metrics…
Fast Approximation of Empirical Entropy via Subsampling
The promotional video for the KDD 2019 paper: Fast Approximation of Empirical Entropy via Subsampling by Chi Wang and Bailu Ding.
InterpretML
InterpretML is an open-source python package for training interpretable models and explaining blackbox systems. Historically, the most intelligible models were not very accurate, and the most accurate models were not intelligible. Microsoft Research has developed…
Accelerated Bregman Proximal Gradient Methods (accbpg)
A Python package of accelerated first-order algorithms for solving relatively-smooth convex optimization problems. It implements all algorithms described in our recent paper on accelerated Bregman proximal gradient methods, including the baseline algorithms for comparison. It…