We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
— In this paper we give a theoretical model for determining the synchronization frequency that minimizes the parallel execution time of loops with uniform dependencies dynamicall...
Florina M. Ciorba, Ioannis Riakiotakis, Theodore A...
— The latency of a perception system is crucial for a robot performing interactive tasks in dynamic human environments. We present MOPED, a fast and scalable perception system fo...
Manuel Martinez, Alvaro Collet, Siddhartha S. Srin...
In this paper, we consider the problem of estimating the state of a dynamical system from distributed noisy measurements. Each agent constructs a local estimate based on its own m...
We present a methodology for the real time alignment of music signals using sequential Montecarlo inference techniques. The alignment problem is formulated as the state tracking o...