Carnegie Mellon University

About: Carnegie Mellon University is a education organization based out in Pittsburgh, Pennsylvania, United States. It is known for research contribution in the topics: Population & Robot. The organization has 36317 authors who have published 104359 publications receiving 5975734 citations. The organization is also known as: CMU & Carnegie Mellon.

Correlation Clustering

Abstract: We consider the following clustering problem: we have a complete graph on n vertices (items), where each edge (u, v) is labeled either + or − depending on whether u and v have been deemed to be similar or different. The goal is to produce a partition of the vertices (a clustering) that agrees as much as possible with the edge labels. That is, we want a clustering that maximizes the number of + edges within clusters, plus the number of − edges between clusters (equivalently, minimizes the number of disagreements: the number of − edges inside clusters plus the number of + edges between clusters). This formulation is motivated from a document clustering problem in which one has a pairwise similarity function f learned from past data, and the goal is to partition the current set of documents in a way that correlates with f as much as possibles it can also be viewed as a kind of “agnostic learning” problem. An interesting feature of this clustering formulation is that one does not need to specify the number of clusters k as a separate parameter, as in measures such as k-median or min-sum or min-max clustering. Instead, in our formulation, the optimal number of clusters could be any value between 1 and n, depending on the edge labels. We look at approximation algorithms for both minimizing disagreements and for maximizing agreements. For minimizing disagreements, we give a constant factor approximation. For maximizing agreements we give a PTAS, building on ideas of Goldreich, Goldwasser, and Ron (1998) and de la Veg (1996). We also show how to extend some of these results to graphs with edge labels in [−1, +1], and give some results for the case of random noise.

3D bioprinting of collagen to rebuild components of the human heart

Abstract: Collagen is the primary component of the extracellular matrix in the human body. It has proved challenging to fabricate collagen scaffolds capable of replicating the structure and function of tissues and organs. We present a method to 3D-bioprint collagen using freeform reversible embedding of suspended hydrogels (FRESH) to engineer components of the human heart at various scales, from capillaries to the full organ. Control of pH-driven gelation provides 20-micrometer filament resolution, a porous microstructure that enables rapid cellular infiltration and microvascularization, and mechanical strength for fabrication and perfusion of multiscale vasculature and tri-leaflet valves. We found that FRESH 3D-bioprinted hearts accurately reproduce patient-specific anatomical structure as determined by micro-computed tomography. Cardiac ventricles printed with human cardiomyocytes showed synchronized contractions, directional action potential propagation, and wall thickening up to 14% during peak systole.

Side-Jump Mechanism for the Hall Effect of Ferromagnets

Abstract: The center of mass of a wave packet undergoes a discontinuous and finite sideways displacement on scattering by a central potential, in the presence of spin-orbit interaction. This is the main Hall-effect mechanism (${\ensuremath{\rho}}_{H}\ensuremath{\propto}{\ensuremath{\rho}}^{2}$) for Fe, Ni, and their alloys above 100 K, while asymmetric scattering dominates below 100 K. Displacement $\ensuremath{\Delta}y$ per actual collision is calculated by partial waves. In the case of Born expansion, the leading term of $\ensuremath{\Delta}y or \frac{{\ensuremath{\rho}}_{H}}{{\ensuremath{\rho}}^{2}}$ is of zero order in the scattering potential. The magnitude is predicted correctly ($\ensuremath{\Delta}y\ensuremath{\approx}{10}^{\ensuremath{-}10}\ensuremath{-}{10}^{\ensuremath{-}11}$ m) when using the effective spin-orbit Hamiltonian derived by Fivaz from spin-orbit interband mixing. The calculation of ${\ensuremath{\rho}}_{H}$ is extended to arbitrary ${\ensuremath{\omega}}_{c}\ensuremath{\tau}$ for compensated and un-compensated metals. Other nonclassical physical mechanisms proposed by Karplus and Luttinger and by Doniach and by Fivaz are spurious for the dc Hall effect.

Epidemic spreading in real networks: an eigenvalue viewpoint

Abstract: How will a virus propagate in a real network? Does an epidemic threshold exist for a finite graph? How long does it take to disinfect a network given particular values of infection rate and virus death rate? We answer the first question by providing equations that accurately model virus propagation in any network including real and synthesized network graphs. We propose a general epidemic threshold condition that applies to arbitrary graphs: we prove that, under reasonable approximations, the epidemic threshold for a network is closely related to the largest eigenvalue of its adjacency matrix. Finally, for the last question, we show that infections tend to zero exponentially below the epidemic threshold. We show that our epidemic threshold model subsumes many known thresholds for special-case graphs (e.g., Erdos-Renyi, BA power-law, homogeneous); we show that the threshold tends to zero for infinite power-law graphs. We show that our threshold condition holds for arbitrary graphs.

Skill Acquisition: Compilation of Weak-Method Problem Solutions.

Abstract: : Cognitive skills are encoded by a set of productions, which are organized according to a hierarchical goal structure. People solve problems in new domains by applying weak problem-solving procedures to declarative knowledge they have about this domain. From these initial problem solutions, production rules are compiled which are specific to that domain and that use of the knowledge. Numerous experimental results follow from this conception of skill organization and skill acquisition. These experiments include predictions about transfer among skills, differential improvement on problem types, effects of working memory limitations, and applications to instruction. The theory implies that all variety of skill acquisition, including that typically regarded as inductive, conforms to this characterization. Keywords: Artificial intelligence; Cognitive science; Skill acquisition; Production system; LISP.