On Horizontal and Vertical Separation in Hierarchical Text Classification

Hierarchy is a common and effective way of organizing data and representing their relationships at different levels of abstraction. However, hierarchical data dependencies cause difficulties in the estimation of "separable" models that can distinguish between the entities in the hierarchy. Extracting separable models of hierarchical entities requires us to take their relative position into account and to consider the different types of dependencies in the hierarchy. In this paper, we present an investigation of the effect of separability in text-based entity classification and argue that in hierarchical classification, a separation property should be established between entities not only in the same layer, but also in different layers. Our main findings are the followings. First, we analyse the importance of separability on the data representation in the task of classification and based on that, we introduce a "Strong Separation Principle" for optimizing expected effectiveness of classifiers decision based on separation property. Second, we present Hierarchical Significant Words Language Models (HSWLM) which capture all, and only, the essential features of hierarchical entities according to their relative position in the hierarchy resulting in horizontally and vertically separable models. Third, we validate our claims on real-world data and demonstrate that how HSWLM improves the accuracy of classification and how it provides transferable models over time. Although discussions in this paper focus on the classification problem, the models are applicable to any information access tasks on data that has, or can be mapped to, a hierarchical structure.Comment: Full paper (10 pages) accepted for publication in proceedings of ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR'16

The effect of low-energy ion-implantation on the electrical transport properties of Si-SiO2 MOSFETs

Using silicon MOSFETs with thin (5nm) thermally grown SiO2 gate dielectrics, we characterize the density of electrically active traps at low-temperature after 16keV phosphorus ion-implantation through the oxide. We find that, after rapid thermal annealing at 1000oC for 5 seconds, each implanted P ion contributes an additional 0.08 plus/minus 0.03 electrically active traps, whilst no increase in the number of traps is seen for comparable silicon implants. This result shows that the additional traps are ionized P donors, and not damage due to the implantation process. We also find, using the room temperature threshold voltage shift, that the electrical activation of donors at an implant density of 2x10^12 cm^-2 is ~100%.Comment: 11 pages, 10 figure

Correlation Clustering with Low-Rank Matrices

Correlation clustering is a technique for aggregating data based on qualitative information about which pairs of objects are labeled 'similar' or 'dissimilar.' Because the optimization problem is NP-hard, much of the previous literature focuses on finding approximation algorithms. In this paper we explore how to solve the correlation clustering objective exactly when the data to be clustered can be represented by a low-rank matrix. We prove in particular that correlation clustering can be solved in polynomial time when the underlying matrix is positive semidefinite with small constant rank, but that the task remains NP-hard in the presence of even one negative eigenvalue. Based on our theoretical results, we develop an algorithm for efficiently "solving" low-rank positive semidefinite correlation clustering by employing a procedure for zonotope vertex enumeration. We demonstrate the effectiveness and speed of our algorithm by using it to solve several clustering problems on both synthetic and real-world data

Use of remote sensing products in a terrestrial ecosystems verified full carbon accounting: Experiences from Russia

The paper considers the specifics, strengths and weaknesses of available remote sensing products within major steps and modules of a verified terrestrial ecosystems full carbon account (FCA) of Russia's land. The methodology used is based on system integration of all available information sources and major methods of carbon accounting using IIASA's landscape-ecosystem approach for overall designing of the account. A multi-sensor remote sensing concept is a corner stone of the methodology being substantially used for (1) georeferencing and parametrization of land cover and its change, (2) assessment of important biophysical and ecological parameters of ecosystems and landscapes, and (3) assessment of the impacts of environmental conditions on ecosystem productivity and disturbance regimes. System integration and mutual constraints of remote sensing and ground information allow for substantially decreasing uncertainty of the FCA. In the Russian case-study, the net ecosystem carbon balance of Russia for an individual year (2009) is estimated with uncertainty at 25-30% (CI 0.9), that presumably should satisfy current requirements to the FCA at the national (continental) scale

High superconducting anisotropy and weak vortex pinning in Co doped LaFeAsO

Here, we present an electrical transport study in single crystals of LaFe$_{0.92}$Co$_{0.08}$AsO ($T_c \simeq 9.1$ K) under high magnetic fields. In contrast to most of the previously reported Fe based superconductors, and despite its relatively low $T_c$, LaFe$_{1-x}$Co$_x$AsO shows a superconducting anisotropy which is comparable to those seen for instance in the cuprates or $\gamma_H = H_{c2}^{ab}/H_{c2}^{c} = m_c/m_{ab} \simeq 9$, where $m_c/m_{ab}$ is the effective mass anisotropy. Although, in the present case and as in all Fe based superconductors, $\gamma \rightarrow 1$ as $T \rightarrow 0$. Under the application of an external field, we also observe a remarkable broadening of the superconducting transition particularly for fields applied along the inter-planar direction. Both observations indicate that the low dimensionality of LaFe$_{1-x}$Co$_x$AsO is likely to lead to a more complex vortex phase-diagram when compared to the other Fe arsenides and consequently, to a pronounced dissipation associated with the movement of vortices in a possible vortex liquid phase. When compared to, for instance, F-doped compounds pertaining to same family, we obtain rather small activation energies for the motion of vortices. This suggests that the disorder introduced by doping LaFeAsO with F is more effective in pinning the vortices than alloying it with Co.Comment: 7 figures, 7 pages, Phys. Rev. B (in press