The Learnable Evolution Model (LEM) involves alternating periods of optimization and learning, performa extremely well on a range of problems, a specialises in achieveing good resu...
Given a data matrix, the problem of finding dense/uniform sub-blocks in the matrix is becoming important in several applications. The problem is inherently combinatorial since th...
—In graph-based learning models, entities are often represented as vertices in an undirected graph with weighted edges describing the relationships between entities. In many real...
—Recent advances in DNA sequencing techniques have led to an unprecedented accumulation and availability of molecular sequence data that needs to be analyzed. This data explosion...
In many data-centric applications, it is desirable to use OWL as an expressive schema language with which one expresses constraints that must be satisfied by instance data. Howeve...