This paper deals with the task of detection of a given keyword in continuous speech. We build upon a previously proposed algorithm where a modified Viterbi search algorithm is used to detect keywords, without requiring any explicit garbage or filler models. In this work, the concept of durational entropy is used to further discard a large fraction of false alarm errors. Durational entropy is de...

Some problems occurring in Expert Systems can be resolved by employing a causal (Bayesian) network and methodologies exist for this purpose. These require data in a specific form and make assumptions about the independence relationships involved. Methodologies using Maximum Entropy (ME) are free from these conditions and have the potential to be used in a wider context including systems consist...

We present a bouquet of continuity bounds for quantum entropies, falling broadly into two classes: First, a tight analysis of the Alicki-Fannes continuity bounds for the conditional von Neumann entropy, reaching almost the best possible form that depends only on the system dimension and the trace distance of the states. Almost the same proof can be used to derive similar continuity bounds for t...

In this paper, we propose a Robust Discriminant Analysis based on maximum entropy (MaxEnt) criterion (MaxEnt-RDA), which is derived from a nonparametric estimate of Renyi’s quadratic entropy. MaxEnt-RDA uses entropy as both objective and constraints; thus the structural information of classes is preserved while information loss is minimized. It is a natural extension of LDA from Gaussian assump...

It is well-known that maximum entropy distributions, subject to appropriate moment constraints, arise in physics and mathematics. In an attempt to find a physical reason for the appearance of maximum entropy distributions, the following theorem is offered. The conditional distribution of X, given the empirical observation (1 /n)X:, ,/I ( X,) = (Y, where X, , X2, . are independent identically di...

Many CSPs can be effectively represented and efficiently solved using matrix models, in which the matrices may have symmetry between their rows and/or columns. Eliminating all such symmetry can be very costly as there are in general exponentially many symmetries. Cost-effective methods have been proposed to break much of the symmetry, if not all. In this paper, we continue with this line of res...

We review research on the ̄uency heuristic as a basis for the subjective experience of familiarity. Then, we explore the links between the construct of ̄uency and the automatic versus consciously controlled memory processes that are estimated using the process dissociation procedure, and the phenomenological experiences studied using ``Remember'' and ``Know'' judgements. Although the ̄uency tha...

We introduce an entropy-like proximal algorithm for the problem of minimizing a closed proper convex function subject to symmetric cone constraints. The algorithm is based on a distance-like function that is an extension of the Kullback-Leiber relative entropy to the setting of symmetric cones. Like the proximal algorithms for convex programming with nonnegative orthant cone constraints, we sho...

We use the method of Maximum (relative) Entropy to process information in the form of observed data and moment constraints. The generic “canonical” form of the posterior distribution for the problem of simultaneous updating with data and moments is obtained. We discuss the general problem of non-commuting constraints, when they should be processed sequentially and when simultaneously. As an ill...

We present a novel derivation of the constraints required to obtain the underlying principles of statistical mechanics using a maximum entropy framework. We derive the mean value constraints by use of the central limit theorem and the scaling properties of Lagrange multipliers. We then arrive at the same result using a quantum free field theory and the Ward identities. The work provides a princ...