1.1k citations · 5.4k across the 59 of their papers we have counts for
4 papers · 1 filter
Revisiting minimum description length complexity in overparameterized models
Raaz Dwivedi, Chandan Singh, Bin Yu +1
Complexity is a fundamental concept underlying statistical learning theory that aims to inform generalization performance. Parameter count, while successful in low-dimensional sett…
Instability, Computational Efficiency and Statistical Accuracy
Nhat Ho, Koulik Khamaru, Raaz Dwivedi +3
Many statistical estimators are defined as the fixed point of a data-dependent operator, with estimators based on minimizing a cost function being an important special case. The li…
Interpretations are useful: penalizing explanations to align neural networks with prior knowledge
Laura Rieger, Chandan Singh, W. James Murdoch +1
For an explanation of a deep learning model to be effective, it must provide both insight into a model and suggest a corresponding action in order to achieve some objective. Too of…
Hierarchical interpretations for neural network predictions
Chandan Singh, W. James Murdoch, Bin Yu
Deep neural networks (DNNs) have achieved impressive predictive performance due to their ability to learn complex, non-linear relationships between variables. However, the inabilit…