We derive an optimal learning rule in the sense of mutual information maximization for a spiking neuron model. Under the assumption of small fluctuations of the input, we find a s...
We propose a quasi-greedy algorithm for approximating the classical uncapacitated 2-level facility location problem (2-LFLP). Our algorithm, unlike the standard greedy algorithm, ...
We present a connectionist architecture that can learn a model of the relations between perceptions and actions and use this model for behavior planning. State representations are...
In this paper, we present a stochastic language model for Japanese using dependency. The prediction unit in thismodel isallattributeof "bunsetsu". This isrepresented by ...
This paper discusses the efficiency of various batching methods for estimating performance parameters from steady-state simulation output, e.g., the steadystate mean. Our primary ...