This paper studies a continuous-time market where an agent, having specified an investment horizon and a targeted terminal mean return, seeks to minimize the variance of the return. The optimal portfolio of such a problem is called mean-variance efficient à la Markowitz. It is shown that, when the market coefficients are deterministic functions of time, a mean-variance efficient portfolio reali...

In an isopotential neuron with rapid response, it has been shown that the receptive fields formed by Hebbian synaptic modulation depend on the principal eigenspace of Q(0), the input autocorrelation matrix, where Qij(tau) = and xi i(t) is the input to synapse i at time t (Oja 1982). We relax the assumption of isopotentiality, introduce a time-skewed Hebb rule, and find tha...

The response time of a rule-based program is deened as the maximum number of rule rings before a xed point of the program is reached from a start state. In this paper, we present several principles which make use of two relations, potential-trigger and suppression, for deriving tight response-time bounds. While the computation of these two relations is costly in general, we show how they can be...

Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is influenced by an environmental signal, termed a reward, that directs the changes in appropriate directions. We apply a recently introduced policy learning algorithm from machine learning to networks of spiking neurons a...

Due to the wide availability of huge data collection comprising multiple sequences that evolve over time, the process of adapting the classical data-mining techniques, making them capable to work into this new context, becomes today a strong necessity. Having as a final goal the extraction of temporal rules from time series databases, we proposed in this article a methodology permitting the app...

Time series prediction is of great significance in many applications and has attracted extensive attention from the data mining community. Existing work suggests that for many problems, the shape in the current time series may correlate an upcoming shape in the same or another series. Therefore, it is a promising strategy to associate two recurring patterns as a rule’s antecedent and consequent...

The distributed evolutionary computation platform EC-Star is extended in this paper to probabilistic classifiers. This extension, called PRETSL, allows the distributed age-layered evolution of probabilistic rule sets, which in turn makes more fine-grained decisions possible. The method is tested on 20 UCI data problems, as well as a larger dataset of arterial blood pressure waveforms. The Resul...

Clarida, Galí and Gertler (CGG 2000), Orphanides and Williams (2005), Kim and Nelson (2006), and others have found time variation in the Fed’s “Taylor Rule” interest rate policy response function. CGG arbitrarily break their period into two fixedcoefficient 20-year subperiods, however, rather than letting the data tell them when and if any shift in the coefficients occurred. They also proxy the...