Energy-based temporal neural networks for imputing missing values

Imputing missing values in high dimensional time series is a difficult problem. There have been some approaches to the problem [11,8] where neural architectures were trained as probabilistic models of the data. However, we argue that this approach is not optimal. We propose to view temporal neural networks with latent variables as energy-based models and train them for missing value recovery directly. In this paper we introduce two energy-based models. The first model is based on a one dimensional convolution and the second model utilizes a recurrent neural network. We demonstrate how ideas from the energy-based learning framework can be used to train these models to recover missing values. The models are evaluated on a motion capture dataset

Comparing Probabilistic Models for Melodic Sequences

Modelling the real world complexity of music is a challenge for machine learning. We address the task of modeling melodic sequences from the same music genre. We perform a comparative analysis of two probabilistic models; a Dirichlet Variable Length Markov Model (Dirichlet-VMM) and a Time Convolutional Restricted Boltzmann Machine (TC-RBM). We show that the TC-RBM learns descriptive music features, such as underlying chords and typical melody transitions and dynamics. We assess the models for future prediction and compare their performance to a VMM, which is the current state of the art in melody generation. We show that both models perform significantly better than the VMM, with the Dirichlet-VMM marginally outperforming the TC-RBM. Finally, we evaluate the short order statistics of the models, using the Kullback-Leibler divergence between test sequences and model samples, and show that our proposed methods match the statistics of the music genre significantly better than the VMM.Comment: in Proceedings of the ECML-PKDD 2011. Lecture Notes in Computer Science, vol. 6913, pp. 289-304. Springer (2011

Economics of grain-fallow rotations in Saskatchewan

Non-Peer Reviewe

Renormalization Group Analysis of \rho-Meson Properties at Finite Density

We calculate the density dependence of the $\rho$-meson mass and coupling constant($g_{\rho NN}$) for $\rho$-nucleon-nucleon vertex at one loop using the lagrangian where the $\rho$-meson is included as a dynamical gauge boson of a hidden local symmetry. From the condition that thermodynamic potential should not depend on the arbitrary energy scale, renormalization scale, one can construct a renormalization group equation for the thermodynamic potential and argue that the various renormalization group coefficients are functions of the density or temperature. We calculate the $\beta$-function for $\rho$-nucleon-nucleon coupling constant ($g_{\rho NN}$) and $\gamma$-function for $\rho$-meson mass ($\gamma_{m_\rho}$). We found that the $\rho$-meson mass and the coupling constant for $g_{\rho NN}$ drop as density increases in the low energy limit.Comment: 24 pages, 10 figures, revised versio

A multi-category decision support framework for the Tennessee Eastman problem

The paper investigates the feasibility of developing a classification framework, based on support vector machines, with the correct properties to act as a decision support system for an industrial process plant, such as the Tennessee Eastman process. The system would provide support to the technicians who monitor plants by signalling the occurrence of abnormal plant measurements marking the onset of a fault condition. To be practical such a system must meet strict standards, in terms of low detection latency, a very low rate of false positive detection and high classification accuracy. Experiments were conducted on examples generated by a simulation of the Tennessee Eastman process and these were preprocessed and classified using a support vector machine. Experiments also considered the efficacy of preprocessing observations using Fisher Discriminant Analysis and a strategy for combining the decisions from a bank of classifiers to improve accuracy when dealing with multiple fault categories

Asymmetric Adjustment In The Effects Of Monetary Policy On Output: Evidence In The USA And Canada Using A Cointegration Analysis

Using a set of cointegration and error correction models with Threshold Autoregressive (TAR) or Momentum Threshold Autoregressive (MTAR) asymmetric adjustment, we investigate whether the effects of monetary policy on output in the USA and Canada are asymmetric or not. Forty years of quarterly data on output, money supply, price of oil and interest rate for the USA and Canada obtained from the International Monetary Funds International Financial Statistics CD-ROM were used for the different tests. Empirical results show that the effects of monetary policy on output are asymmetric in both countries. Furthermore, the impulse response functions indicate that the results are consistent with a dynamic asymmetry in the behavior of money supply movements in both countries

Nitrogen quadrupole coupling constants for HCN and H2CN +: Explanation of the absence of fine structure in the microwave spectrum of interstellar H2CN+

Nitrogen 14 quadrupole coupling constants for H2CN+ and HCN are predicted via ab initio self-consistent-field and configuration interaction theory. Effects of electron correlation, basis set completeness, and geometrical structure on the predicted electric field gradients are analyzed. The quadrupole coupling constant obtained for H2CN+ is one order of magnitude less than in HCN, providing an explanation for the experimental fact that the fine structure of the microwave spectrum of H 2CN+ has not been resolved. This research also allows a reliable prediction of the nuclear quadrupole moment of 14N, namely Q(14N)=2.00×10-26 cm2. © 1986 American Institute of Physics.Fil:Scuseria, G.E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina

Kaon Condensation in ``Nuclear Star" Matter

The critical density for kaon condensation in ``nuclear star" matter is computed up to two-loop order {\it in medium} (corresponding to next-to-next-to-leading order in chiral perturbation theory in free space) with a heavy-baryon effective chiral Lagrangian whose parameters are determined from $KN$ scattering and kaonic atom data. To the order considered, the kaon self-energy has highly non-linear density dependence in dense matter. We find that the four-Fermi interaction terms in the chiral Lagrangian play an important role in triggering condensation, predicting for ``natural" values of the four-Fermi interactions a rather low critical density, $\rho_c < 4 \rho_0$.Comment: 12 pages and 2 figures(LaTeX), SNUTP-94-28. The fig. 3 is replaced, with some changes in the text but the conclusion is not affected by these change

Wavefunction topology of two-dimensional time-reversal symmetric superconductors

We discuss the topology of the wavefunctions of two-dimensional time-reversal symmetric superconductors. We consider (a) the planar state, (b) a system with broken up-down reflection symmetry, and (c) a system with general spin-orbit interaction. We show explicitly how the relative sign of the order parameter on the two Fermi surfaces affects this topology, and clarify the meaning of the $Z_2$ classification for these topological states.Comment: only the Introduction has been modified from v