Efficient Bayesian Inference for Learning in the Ising Linear Perceptron and Signal Detection in CDMA

Efficient new Bayesian inference technique is employed for studying critical properties of the Ising linear perceptron and for signal detection in Code Division Multiple Access (CDMA). The approach is based on a recently introduced message passing technique for densely connected systems. Here we study both critical and non-critical regimes. Results obtained in the non-critical regime give rise to a highly efficient signal detection algorithm in the context of CDMA; while in the critical regime one observes a first order transition line that ends in a continuous phase transition point. Finite size effects are also studied.Comment: 11 pages, 3 figure

Decarbonization of Urban areas: Thermal and Electrical grid integration

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Learning in ultrametric committee machines

The problem of learning by examples in ultrametric committee machines (UCMs) is studied within the framework of statistical mechanics. Using the replica formalism we calculate the average generalization error in UCMs with L hidden layers and for a large enough number of units. In most of the regimes studied we find that the generalization error, as a function of the number of examples presented, develops a discontinuous drop at a critical value of the load parameter. We also find that when L>1 a number of teacher networks with the same number of hidden layers and different overlaps induce learning processes with the same critical points

Anisotropic opinion dynamics with an adaptive social rule

We consider an anisotropic opinion formation process where the set of rules B, that dictates what is the socially acceptable position, changes following the average voters' opinion. As in the case of a constant B, conservative (agreement with B) and liberal (agreement with neighbors) voters' attitudes are still represented by stable fixed points in the phase space of the system but with the difference that the conservative fixed point is stable for all possible values of the intervoter interaction. It has been also observed that, when the model is applied to sufficiently large populations, the time needed to consolidate a position in agreement with B is finite. We observed that there is also a range of values of the interaction where the two stable points coexist, opening the door for the modeling of bistability related phenomena, such as stochastic resonance and hysteresis

Anisotropic opinion dynamics

We consider the process of opinion formation in a society of interacting agents, where there is a set B of socially accepted rules. In this scenario, we observed that agents, represented by simple feed-forward, adaptive neural networks, may have a conservative attitude (mostly in agreement with B) or liberal attitude (mostly in agreement with neighboring agents) depending on how much their opinions are influenced by their peers. The topology of the network representing the interaction of the society's members is determined by a graph, where the agents' properties are defined over the vertexes and the interagent interactions are defined over the bonds. The adaptability of the agents allows us to model the formation of opinions as an online learning process, where agents learn continuously as new information becomes available to the whole society (online learning). Through the application of statistical mechanics techniques we deduced a set of differential equations describing the dynamics of the system. We observed that by slowly varying the average peer influence in such a way that the agents attitude changes from conservative to liberal and back, the average social opinion develops a hysteresis cycle. Such hysteretic behavior disappears when the variance of the social influence distribution is large enough. In all the cases studied, the change from conservative to liberal behavior is characterized by the emergence of conservative clusters, i.e., a closed knitted set of society members that follow a leader who agrees with the social status quo when the rule B is challenged

Storage capacity of ultrametric committee machines

The problem of computing the storage capacity of a feed-forward network, with L hidden layers, N inputs, and K units in the first hidden layer, is analyzed using techniques from statistical mechanics. We found that the storage capacity strongly depends on the network architecture αc ∼ (log K)1-1/2L and that the number of units K limits the number of possible hidden layers L through the relationship 2L - 1 < 2log K

Phase changes in 38 atom Lennard-Jones clusters. II: A parallel tempering study of equilibrium and dynamic properties in the molecular dynamics and microcanonical

We study the 38-atom Lennard-Jones cluster with parallel tempering Monte Carlo methods in the microcanonical and molecular dynamics ensembles. A new Monte Carlo algorithm is presented that samples rigorously the molecular dynamics ensemble for a system at constant total energy, linear and angular momenta. By combining the parallel tempering technique with molecular dynamics methods, we develop a hybrid method to overcome quasi-ergodicity and to extract both equilibrium and dynamical properties from Monte Carlo and molecular dynamics simulations. Several thermodynamic, structural and dynamical properties are investigated for LJ$_{38}$, including the caloric curve, the diffusion constant and the largest Lyapunov exponent. The importance of insuring ergodicity in molecular dynamics simulations is illustrated by comparing the results of ergodic simulations with earlier molecular dynamics simulations.Comment: Journal of Chemical Physics, accepte

Rebellions and Impeachments in a Neural Network Society

Basede on a study of the modern presidencial democracies in South America, we present a statistical mechanics exploration of the collective, coordinated action of political actors in the legislative chamber that may result on the impeachment of the executive. By representing the legislative political actors with neurla networks, we observed that the larger the effective number of presidential-agenda items are treated, the smaller the chances for a cross-party dialogue, which, if combined with a decrement in the president's public approval rating, could trigger an impeachment process.Comment: 23 pages and 7 figure

Dealing with the tensions between innovation and internationalization in SMEs: A dynamic capability view

Previous literature disagrees on the fact that innovation and internationalization are decisions with a complementary effect on the performance of small and medium enterprises (SMEs) performance. We reconcile the contrasting views on this topic by using a dynamic capability perspective. We show that the simultaneous involvement in research and development (R&D) and export activities positively impacts SMEs’ profitability when such firms collaborate with universities and research centers, or when their international experience involves a diverse set of geographical markets. The magnitude of these moderations is different for low and high performers, thereby showing the lack of a “one best way” to successfully achieve complementarity between R&D and internationalization decisions