152 citations · 227 across the 4 of their papers we have counts for
5 papers · 1 filter
Data Shapley Valuation for Efficient Batch Active Learning
Amirata Ghorbani, James Zou, Andre Esteva
Annotating the right set of data amongst all available data points is a key challenge in many machine learning applications. Batch active learning is a popular approach to address…
Neuron Shapley: Discovering the Responsible Neurons
Amirata Ghorbani, James Zou
We develop Neuron Shapley as a new framework to quantify the contribution of individual neurons to the prediction and performance of a deep network. By accounting for interactions…
Data Shapley: Equitable Valuation of Data for Machine Learning
Amirata Ghorbani, James Zou
As data becomes the fuel driving technological and economic growth, a fundamental challenge is how to quantify the value of data in algorithmic predictions and decisions. For examp…
Towards Automatic Concept-based Explanations
Amirata Ghorbani, James Wexler, James Zou +1
Interpretability has become an important topic of research as more machine learning (ML) models are deployed and widely used to make important decisions. Most of the current explan…
Knockoffs for the mass: new feature importance statistics with false discovery guarantees
Jaime Roquero Gimenez, Amirata Ghorbani, James Zou
An important problem in machine learning and statistics is to identify features that causally affect the outcome. This is often impossible to do from purely observational data, and…