Dec 22, 2011 · Abstract:We consider the problem of classification using similarity/distance functions over data. Specifically, we propose a framework for ...

We consider the problem of classification using similarity/distance functions over data. Specifically, we propose a framework for defining the goodness of a.

We consider the problem of classification using similarity/distance functions over data. Specifically, we propose a framework for defining the goodness of a.

In this paper we present a machine-learning algorithm that computes a small set of accurate and interpretable rules. The decisions of these rules can be ...

What is a good similarity function ? ▷ Suitability of a similarity function to a given classification problem. > Points with same label should be more similar ...

A framework for defining the goodness of a (dis)similarity function with respect to a given learning task and proposed algorithms that have guaranteed ...

Nov 3, 2011 · The above procedure essentially creates a data-driven, problem specific embedding of the domain X into a Euclidean space. P. Kar and P. Jain ( ...

In this paper we address the problem of general supervised learning where data can only be accessed through an (indefinite) similarity function between data ...

Jan 21, 2021 · Bibliographic details on Similarity-based Learning via Data Driven Embeddings.

Oct 31, 2023 · In this article, we will show how to tackle this problem using embedding layers and dot products in a neural network model.