Efficient Semidefinite Spectral Clustering via Lagrange Duality

We propose an efficient approach to semidefinite spectral clustering (SSC), which addresses the Frobenius normalization with the positive semidefinite (p.s.d.) constraint for spectral clustering. Compared with the original Frobenius norm approximation based algorithm, the proposed algorithm can more accurately find the closest doubly stochastic approximation to the affinity matrix by considering the p.s.d. constraint. In this paper, SSC is formulated as a semidefinite programming (SDP) problem. In order to solve the high computational complexity of SDP, we present a dual algorithm based on the Lagrange dual formalization. Two versions of the proposed algorithm are proffered: one with less memory usage and the other with faster convergence rate. The proposed algorithm has much lower time complexity than that of the standard interior-point based SDP solvers. Experimental results on both UCI data sets and real-world image data sets demonstrate that 1) compared with the state-of-the-art spectral clustering methods, the proposed algorithm achieves better clustering performance; and 2) our algorithm is much more efficient and can solve larger-scale SSC problems than those standard interior-point SDP solvers.Comment: 13 page

Multi-stage Multi-recursive-input Fully Convolutional Networks for Neuronal Boundary Detection

In the field of connectomics, neuroscientists seek to identify cortical connectivity comprehensively. Neuronal boundary detection from the Electron Microscopy (EM) images is often done to assist the automatic reconstruction of neuronal circuit. But the segmentation of EM images is a challenging problem, as it requires the detector to be able to detect both filament-like thin and blob-like thick membrane, while suppressing the ambiguous intracellular structure. In this paper, we propose multi-stage multi-recursive-input fully convolutional networks to address this problem. The multiple recursive inputs for one stage, i.e., the multiple side outputs with different receptive field sizes learned from the lower stage, provide multi-scale contextual boundary information for the consecutive learning. This design is biologically-plausible, as it likes a human visual system to compare different possible segmentation solutions to address the ambiguous boundary issue. Our multi-stage networks are trained end-to-end. It achieves promising results on two public available EM segmentation datasets, the mouse piriform cortex dataset and the ISBI 2012 EM dataset.Comment: Accepted by ICCV201

Bosonization of quantum sine-Gordon field with a boundary

Boundary operators and boundary ground states in sine-Gordon model with a fixed boundary condition are studied using bosonization and q-deformed oscillators.We also obtain the form-factors of this model.Comment: Latex 25page

Person Re-identification with Correspondence Structure Learning

This paper addresses the problem of handling spatial misalignments due to camera-view changes or human-pose variations in person re-identification. We first introduce a boosting-based approach to learn a correspondence structure which indicates the patch-wise matching probabilities between images from a target camera pair. The learned correspondence structure can not only capture the spatial correspondence pattern between cameras but also handle the viewpoint or human-pose variation in individual images. We further introduce a global-based matching process. It integrates a global matching constraint over the learned correspondence structure to exclude cross-view misalignments during the image patch matching process, hence achieving a more reliable matching score between images. Experimental results on various datasets demonstrate the effectiveness of our approach

Perturbative corrections to B→DB \to D form factors in QCD

We compute perturbative QCD corrections to $B \to D$ form factors at leading power in $\Lambda/m_b$, at large hadronic recoil, from the light-cone sum rules (LCSR) with $B$-meson distribution amplitudes in HQET. QCD factorization for the vacuum-to-$B$-meson correlation function with an interpolating current for the $D$-meson is demonstrated explicitly at one loop with the power counting scheme $m_c \sim {\cal O} \left (\sqrt{\Lambda \, m_b} \right )$. The jet functions encoding information of the hard-collinear dynamics in the above-mentioned correlation function are complicated by the appearance of an additional hard-collinear scale $m_c$, compared to the counterparts entering the factorization formula of the vacuum-to-$B$-meson correction function for the construction of $B \to \pi$ from factors. Inspecting the next-to-leading-logarithmic sum rules for the form factors of $B \to D \ell \nu$ indicates that perturbative corrections to the hard-collinear functions are more profound than that for the hard functions, with the default theory inputs, in the physical kinematic region. We further compute the subleading power correction induced by the three-particle quark-gluon distribution amplitudes of the $B$-meson at tree level employing the background gluon field approach. The LCSR predictions for the semileptonic $B \to D \ell \nu$ form factors are then extrapolated to the entire kinematic region with the $z$-series parametrization. Phenomenological implications of our determinations for the form factors $f_{BD}^{+, 0}(q^2)$ are explored by investigating the (differential) branching fractions and the $R(D)$ ratio of $B \to D \ell \nu$ and by determining the CKM matrix element $|V_{cb}|$ from the total decay rate of $B \to D \mu \nu_{\mu}$.Comment: 49 pages, 8 figures, version accepted for publication in JHE

QCD calculations of B→π,KB \to \pi, K form factors with higher-twist corrections

We update QCD calculations of $B \to \pi, K$ form factors at large hadronic recoil by including the subleading-power corrections from the higher-twist $B$-meson light-cone distribution amplitudes (LCDAs) up to the twist-six accuracy and the strange-quark mass effects at leading-power in $\Lambda/m_b$ from the twist-two $B$-meson LCDA $\phi_B^{+}(\omega, \mu)$. The higher-twist corrections from both the two-particle and three-particle $B$-meson LCDAs are computed from the light-cone QCD sum rules (LCSR) at tree level. In particular, we construct the local duality model for the twist-five and -six $B$-meson LCDAs, in agreement with the corresponding asymptotic behaviours at small quark and gluon momenta, employing the QCD sum rules in heavy quark effective theory at leading order in $\alpha_s$. The strange quark mass effects in semileptonic $B \to K$ form factors yield the leading-power contribution in the heavy quark expansion, consistent with the power-counting analysis in soft-collinear effective theory, and they are also computed from the LCSR approach due to the appearance of the rapidity singularities. We further explore the phenomenological aspects of the semileptonic $B \to \pi \ell \nu$ decays and the rare exclusive processes $B \to K \nu \nu$, including the determination of the CKM matrix element $|V_{ub}|$, the normalized differential $q^2$ distributions and precision observables defined by the ratios of branching fractions for the above-mentioned two channels in the same intervals of $q^2$.Comment: 36 pages, 9 figure