190 citations · 329 across the 14 of their papers we have counts for
4 papers · 1 filter
Meta-Learning to Cluster
Yibo Jiang, Nakul Verma
Clustering is one of the most fundamental and wide-spread techniques in exploratory data analysis. Yet, the basic approach to clustering has not really changed: a practitioner hand…
Model-Agnostic Meta-Learning using Runge-Kutta Methods
Daniel Jiwoong Im, Yibo Jiang, Nakul Verma
Meta-learning has emerged as an important framework for learning new tasks from just a few examples. The success of any meta-learning model depends on (i) its fast adaptation to ne…
Metric Learning on Manifolds
Max Aalto, Nakul Verma
Recent literature has shown that symbolic data, such as text and graphs, is often better represented by points on a curved manifold, rather than in Euclidean space. However, geomet…
Noise-tolerant fair classification
Alexandre Louis Lamy, Ziyuan Zhong, Aditya Krishna Menon +1
Fairness-aware learning involves designing algorithms that do not discriminate with respect to some sensitive feature (e.g., race or gender). Existing work on the problem operates…