Non-Gaussian buoyancy statistics in fingering convection

We examine the statistics of active scalar fluctuations in high-Rayleigh number fingering convection with high-resolution three-dimensional numerical experiments. The one-point distribution of buoyancy fluctuations is found to present significantly non-Gaussian tails. A modified theory based on an original approach by Yakhot (1989) is used to model the active scalar distributions as a function of the conditional expectation values of scalar dissipation and fluxes in the flow. Simple models for these two quantities highlight the role of blob-like coherent structures for scalar statistics in fingering convection

Models of Firm Dynamics and the Hazard Rate of Exits: Reconciling Theory and Evidence using Hazard Regression Models

This paper considers empirical work relating to models of firm dynamics. We show that a hazard regression model for firm exits, with a modification to accommodate age-varying covariate effects, provides an empirical framework accommodating many of the features of interest in studies on firm dynamics. Modelling implications of some of the popular theoretical models are considered and a set of empirical procedures for verifying testable implications of the theoretical models are proposed. The proposed hazard regression models can accommodate negative effects of initial size that go to zero with age (active learning model), negative initial size effects that fall with age but stay permanently negative (passive learning model), conditional and unconditional hazard rates that decrease with age at higher ages, and adverse effects of macroeconomic shocks that decrease with age of the firm. The methods are illustrated using data on quoted UK firms. Consistent with the active learning model, the effect of initial size is significantly negative for a young firm and falls to zero with age. The hazard function conditional on size, other firm- and industry-level characteristics, and macroeconomic conditions decreases with age only at higher ages, but shows the weaker property of Increasing Mean Residual Life over its entire life-duration. Instability in exchange rates affects survival of very young firms strongly, and the effect decreases to insignificant levels for older firms.Firm exit, Learning, Firm Dynamics, Non-proportional hazards, Hazard regression models

Who Spoke What? A Latent Variable Framework for the Joint Decoding of Multiple Speakers and their Keywords

In this paper, we present a latent variable (LV) framework to identify all the speakers and their keywords given a multi-speaker mixture signal. We introduce two separate LVs to denote active speakers and the keywords uttered. The dependency of a spoken keyword on the speaker is modeled through a conditional probability mass function. The distribution of the mixture signal is expressed in terms of the LV mass functions and speaker-specific-keyword models. The proposed framework admits stochastic models, representing the probability density function of the observation vectors given that a particular speaker uttered a specific keyword, as speaker-specific-keyword models. The LV mass functions are estimated in a Maximum Likelihood framework using the Expectation Maximization (EM) algorithm. The active speakers and their keywords are detected as modes of the joint distribution of the two LVs. In mixture signals, containing two speakers uttering the keywords simultaneously, the proposed framework achieves an accuracy of 82% for detecting both the speakers and their respective keywords, using Student's-t mixture models as speaker-specific-keyword models.Comment: 6 pages, 2 figures Submitted to : IEEE Signal Processing Letter

Robust Interactive Learning

In this paper we propose and study a generalization of the standard active-learning model where a more general type of query, class conditional query, is allowed. Such queries have been quite useful in applications, but have been lacking theoretical understanding. In this work, we characterize the power of such queries under two well-known noise models. We give nearly tight upper and lower bounds on the number of queries needed to learn both for the general agnostic setting and for the bounded noise model. We further show that our methods can be made adaptive to the (unknown) noise rate, with only negligible loss in query complexity

A direct semantic characterization of RELFUN

This paper attempts a direct semantic formalization of first-order relational-functional languages (the characteristic RELFUN subset) in terms of a generalized model concept. Function-defining conditional equations (or, footed clauses) and active call-by-value expressions (in clause premises) are integrated into first-order theories. Herbrand models are accommodated to relational-functional programs by not only containing ground atoms but also ground molecules, i.e. specific function applications paired with values. Extending SLD-resolution toward innermost conditional narrowing of relational-functional clauses, SLV-resolution is introduced, which, e.g., flattens active expressions. The Tp-operator is generalized analogously, e.g. by unnesting ground-clause premises. Soundness and completeness proofs for SLV-resolution naturally extend the corresponding results in logic programming