4 citations · 4 across the 3 of their papers we have counts for
4 papers
A scaled Bregman theorem with applications
Richard Nock, Aditya Krishna Menon, Cheng Soon Ong
Bregman divergences play a central role in the design and analysis of a range of machine learning algorithms. This paper explores the use of Bregman divergences to establish reduct…
Learning from Binary Labels with Instance-Dependent Corruption
Aditya Krishna Menon, Brendan van Rooyen, Nagarajan Natarajan
Suppose we have a sample of instances paired with binary labels corrupted by arbitrary instance- and label-dependent noise. With sufficiently many such samples, can we optimally cl…
Learning with Symmetric Label Noise: The Importance of Being Unhinged
Brendan van Rooyen, Aditya Krishna Menon, Robert C. Williamson
Convex potential minimisation is the de facto approach to binary classification. However, Long and Servedio [2010] proved that under symmetric label noise (SLN), minimisation of an…
Textual Features for Programming by Example
Aditya Krishna Menon, Omer Tamuz, Sumit Gulwani +2
In Programming by Example, a system attempts to infer a program from input and output examples, generally by searching for a composition of certain base functions. Performing a nai…