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We describe a new adaptive multiwindow Gabor expansion, which dynamically adapts the windows to the signal's features in time-frequency space. The adaptation is based on local time-frequency sparsity criteria, and also yields as by-product an expansion of the signal into layers corresponding to different windows. As an illustration, we show that simply using two different windows with different sizes leads to decompositions of audio signals into transient and tonal layers. We also discuss potential applications to transient detection and denoising.

While full-sibling group reconstruction from microsatellite data is a well-studied problem, reconstruction of half-sibling groups is much less studied, theoretically challenging, and computationally demanding. In this paper, we present a formulation of the half-sibling reconstruction problem and prove its APX-hardness. We also present exact solutions for this formulation and develop heuristics. Using biological and synthetic datasets we present experimental results and compare them with the leading alternative software COLONY. We show that our results are competitive and allow half-sibling group reconstruction in the presence of polygamy, which is prevalent in nature.

In this context, a model is an algorithm or a procedure that applies to data resulting in a functional relation $\tau$ between “input space” ${𝒳}$ and “output space” ${𝒴}$. In this short paper, we will delineate objective criteria which help to disambiguate and rate models’ credibility. We will define pertinent concepts and will voice an opinion on the matter of good versus bad versus so–so models.

In this context, a model is an algorithm or a procedure that applies to data resulting in a functional relation τ between “input space” $\mathcal{X}$ and “output space” $\mathcal{Y}$. In this short paper, we will delineate objective criteria which help to disambiguate and rate models’ credibility. We will define pertinent concepts and will voice an opinion on the matter of good versus bad versus so–so models.

Modern science has been thoroughly influenced by the centuries-old Simplicity Principle, also known as Ockham’s Razor. This principle is usually formulated as “entities must not be multiplied without necessity”. The main problem with this formulation is that the necessity or redundancy of an entity (e.g. a concept, hypothesis, law, rule, an explanatory element) cannot always be compellingly demonstrated. This means that, certainly within an empiristic, positivistic or materialistic worldview, the use of Ockham’s Razor easily tends towards unjustified reductionism. However, ontologically or epistemologically, the Simplicity Principle can no longer be justified. The Simplicity Principle does not provide a sufficient argument to reject “entities” as irrelevant or superfluous. Moreover, a reductionistic conception of science cannot contribute to tackling issues concerning ultimate values, meanings of life, metaphysics, aesthetics, religion and several aspects of practical life, such as counselling, morals, politics and jurisdiction. Therefore, this article proposes an alternative principle that I have called the Chatton–Ockham Strategy, which is an integration of Chatton’s anti-Razor and Ockham’s Razor and deals with the complexity–simplicity polarity.