Learning Timbre Analogies from Unlabelled Data by Multivariate Tree Regression

This is the Author's Original Manuscript of an article whose final and definitive form, the Version of Record, has been published in the Journal of New Music Research, November 2011, copyright Taylor & Francis. The published article is available online at http://www.tandfonline.com/10.1080/09298215.2011.596938

Rank-based model selection for multiple ions quantum tomography

The statistical analysis of measurement data has become a key component of many quantum engineering experiments. As standard full state tomography becomes unfeasible for large dimensional quantum systems, one needs to exploit prior information and the "sparsity" properties of the experimental state in order to reduce the dimensionality of the estimation problem. In this paper we propose model selection as a general principle for finding the simplest, or most parsimonious explanation of the data, by fitting different models and choosing the estimator with the best trade-off between likelihood fit and model complexity. We apply two well established model selection methods -- the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) -- to models consising of states of fixed rank and datasets such as are currently produced in multiple ions experiments. We test the performance of AIC and BIC on randomly chosen low rank states of 4 ions, and study the dependence of the selected rank with the number of measurement repetitions for one ion states. We then apply the methods to real data from a 4 ions experiment aimed at creating a Smolin state of rank 4. The two methods indicate that the optimal model for describing the data lies between ranks 6 and 9, and the Pearson $\chi^{2}$ test is applied to validate this conclusion. Additionally we find that the mean square error of the maximum likelihood estimator for pure states is close to that of the optimal over all possible measurements.Comment: 24 pages, 6 figures, 3 table

Combining Qualitative Research Perspectives and Methods for Critical Social Purposes The Neoliberal U.S. Childhood Public Policy Behemoth

This article discusses the broad-based use of bricolage to examine the neoliberal childhood policy discourses and forms of implementation that are currently practiced in the United States. Diverse, traditionally marginalized understandings such as Black feminist thought, Chicana feminism, and feminist analysis of capitalist patriarchy are combined with a Deleuze/Guattarian critique of capitalism and qualitative methods of situational analyses. We do this to identify childhood assemblages within the childhood public policy behemoth in the United States and compare these assemblages to capitalism more broadly, including how neoliberal practices are facilitated

The recent intellectual structure of geography

An active learning project in an introductory graduate course used multidimensional scaling of the name index in Geography in America at the Dawn of the 21st Century, by Gary Gaile and Cort Willmott, to reveal some features of the discipline\u27s recent intellectual structure relevant to the relationship between human and physical geography. Previous analyses, dating to the 1980s, used citation indices or Association of American Geographers spe- cialty-group rosters to conclude that either the regional or the methods and environmental subdisciplines bridge human and physical geography. The name index has advantages over those databases, and its analysis reveals that the minimal connectivity that occurs between human and physical geography has recently operated more through environmental than through either methods or regional subdisciplines

Critical Qualitative Methodologies Reconceptualizations and Emergent Construction

Critical qualitative scholarship offers humble grounds and many unforeseen possibilities to seek and promote justice, critical global engagement, and diverse epistemologies. This dialogical and interactive paper is based on a panel session at the International Congress of Qualitative Inquiry that highlighted diverse areas of critical qualitative inquiry, namely justice, difference, ethics, and equity. Authors in this paper share their critical qualitative research practices and provide examples of how justice can be addressed through research foci, methods, theories, and ethical practices.publishedVersio

A comprehensive re-analysis of the Golden Spike data: Towards a benchmark for differential expression methods

<p>Abstract</p> <p>Background</p> <p>The Golden Spike data set has been used to validate a number of methods for summarizing Affymetrix data sets, sometimes with seemingly contradictory results. Much less use has been made of this data set to evaluate differential expression methods. It has been suggested that this data set should not be used for method comparison due to a number of inherent flaws.</p> <p>Results</p> <p>We have used this data set in a comparison of methods which is far more extensive than any previous study. We outline six stages in the analysis pipeline where decisions need to be made, and show how the results of these decisions can lead to the apparently contradictory results previously found. We also show that, while flawed, this data set is still a useful tool for method comparison, particularly for identifying combinations of summarization and differential expression methods that are unlikely to perform well on real data sets. We describe a new benchmark, AffyDEComp, that can be used for such a comparison.</p> <p>Conclusion</p> <p>We conclude with recommendations for preferred Affymetrix analysis tools, and for the development of future spike-in data sets.</p

Skunk River Review September 1989, vol 1 no 1

https://openspace.dmacc.edu/skunkriver/1004/thumbnail.jp

Empirical Bayes models for multiple probe type microarrays at the probe level

<p>Abstract</p> <p>Background</p> <p>When analyzing microarray data a primary objective is often to find differentially expressed genes. With empirical Bayes and penalized t-tests the sample variances are adjusted towards a global estimate, producing more stable results compared to ordinary t-tests. However, for Affymetrix type data a clear dependency between variability and intensity-level generally exists, even for logged intensities, most clearly for data at the probe level but also for probe-set summarizes such as the MAS5 expression index. As a consequence, adjustment towards a global estimate results in an intensity-level dependent false positive rate.</p> <p>Results</p> <p>We propose two new methods for finding differentially expressed genes, Probe level Locally moderated Weighted median-t (PLW) and Locally Moderated Weighted-t (LMW). Both methods use an empirical Bayes model taking the dependency between variability and intensity-level into account. A global covariance matrix is also used allowing for differing variances between arrays as well as array-to-array correlations. PLW is specially designed for Affymetrix type arrays (or other multiple-probe arrays). Instead of making inference on probe-set summaries, comparisons are made separately for each perfect-match probe and are then summarized into one score for the probe-set.</p> <p>Conclusion</p> <p>The proposed methods are compared to 14 existing methods using five spike-in data sets. For RMA and GCRMA processed data, PLW has the most accurate ranking of regulated genes in four out of the five data sets, and LMW consistently performs better than all examined moderated t-tests when used on RMA, GCRMA, and MAS5 expression indexes.</p

Permutationally invariant state reconstruction

Feasible tomography schemes for large particle numbers must possess, besides an appropriate data acquisition protocol, also an efficient way to reconstruct the density operator from the observed finite data set. Since state reconstruction typically requires the solution of a non-linear large-scale optimization problem, this is a major challenge in the design of scalable tomography schemes. Here we present an efficient state reconstruction scheme for permutationally invariant quantum state tomography. It works for all common state-of-the-art reconstruction principles, including, in particular, maximum likelihood and least squares methods, which are the preferred choices in today's experiments. This high efficiency is achieved by greatly reducing the dimensionality of the problem employing a particular representation of permutationally invariant states known from spin coupling combined with convex optimization, which has clear advantages regarding speed, control and accuracy in comparison to commonly employed numerical routines. First prototype implementations easily allow reconstruction of a state of 20 qubits in a few minutes on a standard computer.Comment: 25 pages, 4 figues, 2 table

Measurement of Energy Correlators inside Jets and Determination of the Strong Coupling Formula Presented

Energy correlators that describe energy-weighted distances between two or three particles in a hadronic jet are measured using an event sample of $\sqrt{s}$=13 TeV proton-proton collisions collected by the CMS experiment and corresponding to an integrated luminosity of 36.3 fb$^{−1}$. The measured distributions are consistent with the trends in the simulation that reveal two key features of the strong interaction: confinement and asymptotic freedom. By comparing the ratio of the measured three- and two-particle energy correlator distributions with theoretical calculations that resum collinear emissions at approximate next-to-next-to-leading-logarithmic accuracy matched to a next-to-leading-order calculation, the strong coupling is determined at the Z boson mass: α$_S$ (m$_Z$)=0.1229 $\frac{0.0040}{-0.0050}$ , the most precise α$_S$m$_Z$ value obtained using jet substructure observable