270 citations · 669 across the 40 of their papers we have counts for
5 papers · 1 filter
A Formal Framework to Characterize Interpretability of Procedures
Amit Dhurandhar, Vijay Iyengar, Ronny Luss +1
We provide a novel notion of what it means to be interpretable, looking past the usual association with human understanding. Our key insight is that interpretability is not an abso…
Efficient Data Representation by Selecting Prototypes with Importance Weights
Karthik S. Gurumoorthy, Amit Dhurandhar, Guillermo Cecchi +1
Prototypical examples that best summarizes and compactly represents an underlying complex data distribution communicate meaningful insights to humans in domains where simple explan…
TIP: Typifying the Interpretability of Procedures
Amit Dhurandhar, Vijay Iyengar, Ronny Luss +1
We provide a novel notion of what it means to be interpretable, looking past the usual association with human understanding. Our key insight is that interpretability is not an abso…
Learning with Changing Features
Amit Dhurandhar, Steve Hanneke, Liu Yang
In this paper we study the setting where features are added or change interpretation over time, which has applications in multiple domains such as retail, manufacturing, finance. I…
Uncovering Group Level Insights with Accordant Clustering
Amit Dhurandhar, Margareta Ackerman, Xiang Wang
Clustering is a widely-used data mining tool, which aims to discover partitions of similar items in data. We introduce a new clustering paradigm, \emph{accordant clustering}, which…