We present techniques for rendering and animation of realistic scenes by analyzing and training on short video sequences. This work extends the new paradigm for computer animation...
In this paper we use genetic programming for changing the representation of the input data for machine learners. In particular, the topic of interest here is feature construction i...
In this paper, we propose a method for simultaneous human full-body pose tracking and activity recognition from time-of-flight (ToF) camera images. Simple and sparse depth cues ar...
Loren Arthur Schwarz, Diana Mateus, Victor Castane...
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
Learning in many multi-agent settings is inherently repeated play. This calls into question the naive application of single play Nash equilibria in multi-agent learning and sugges...