Software pipelining and unfolding are commonly used techniques to increase parallelism for DSP applications. However, these techniques expand the code size of the application sign...
Bin Xiao, Zili Shao, Chantana Chantrapornchai, Edw...
Main stream approaches in distributed artificial intelligence (DAI) are essentially logic-based. Little has been reported to explore probabilistic approach in DAI. On the other han...
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Abstract. Loops are an important source of optimization. In this paper, we address such optimizations for those cases when loops contain kernels mapped on reconfigurable fabric. We...
Ozana Silvia Dragomir, Elena Moscu Panainte, Koen ...
Distributed learning is a problem of fundamental interest in machine learning and cognitive science. In this paper, we present asynchronous distributed learning algorithms for two...