Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...
This paper describes the mathematical underpinning used to analyse two dimensional movements with time using Fourier Analysis techniques. Interpreting the complex harmonic compone...
We present a new method for classification with structured
latent variables. Our model is formulated using the
max-margin formalism in the discriminative learning literature.
We...
Recognition of a protein’s fold provides valuable information about its function. While many sequence-based homology prediction methods exist, an important challenge remains: tw...
Images constitute data that lives in a very high dimensional space, typically of the order of hundred thousand dimensions. Drawing inferences from data of such high dimensions soon...