Binding of transcription factors to DNA is one of the keystones of gene regulation. The
existence of statistical dependencies between binding site positions is widely accepted …

Fisher kernels provide a commonly used vectorial representation of structured objects. The
paper presents a technique that exploits label information to improve the object …

Traditional techniques for measuring similarities between time series are based on
handcrafted similarity measures, whereas more recent learning-based approaches cannot …

While video-based activity analysis and recognition has received much attention, existing
body of work mostly deals with single object/person case. Coordinated multi-object activities …

In this paper, we propose a novel sparse representation based framework for classifying
complicated human gestures captured as multi-variate time series (MTS). The novel feature …

Annotating class labels of a large number of time-series data is generally an expensive task.
We propose novel semi-supervised learning algorithms that can improve the classification …

From the streets of London to subway stations in New York City, hundreds of thousands of
surveillance cameras ubiquitously collect hundreds of thousands of videos, often running …

We consider the problem of predicting a sequence of real-valued multivariate states that are
correlated by some unknown dynamics, from a given measurement sequence. Although …

While video-based activity analysis and recognition has received much attention, a large
body of existing work deals with activities of a single subject. Modeling and recognition of …

We address the feature selection problem for hidden Markov models (HMMs) in sequence
classification. Temporal correlation in sequences often causes difficulty in applying feature …