Efficient Parallel Translating Embedding For Knowledge Graphs

Knowledge graph embedding aims to embed entities and relations of knowledge graphs into low-dimensional vector spaces. Translating embedding methods regard relations as the translation from head entities to tail entities, which achieve the state-of-the-art results among knowledge graph embedding methods. However, a major limitation of these methods is the time consuming training process, which may take several days or even weeks for large knowledge graphs, and result in great difficulty in practical applications. In this paper, we propose an efficient parallel framework for translating embedding methods, called ParTrans-X, which enables the methods to be paralleled without locks by utilizing the distinguished structures of knowledge graphs. Experiments on two datasets with three typical translating embedding methods, i.e., TransE [3], TransH [17], and a more efficient variant TransE- AdaGrad [10] validate that ParTrans-X can speed up the training process by more than an order of magnitude.Comment: WI 2017: 460-46

The Computational Power of Optimization in Online Learning

We consider the fundamental problem of prediction with expert advice where the experts are "optimizable": there is a black-box optimization oracle that can be used to compute, in constant time, the leading expert in retrospect at any point in time. In this setting, we give a novel online algorithm that attains vanishing regret with respect to $N$ experts in total $\widetilde{O}(\sqrt{N})$ computation time. We also give a lower bound showing that this running time cannot be improved (up to log factors) in the oracle model, thereby exhibiting a quadratic speedup as compared to the standard, oracle-free setting where the required time for vanishing regret is $\widetilde{\Theta}(N)$. These results demonstrate an exponential gap between the power of optimization in online learning and its power in statistical learning: in the latter, an optimization oracle---i.e., an efficient empirical risk minimizer---allows to learn a finite hypothesis class of size $N$ in time $O(\log{N})$. We also study the implications of our results to learning in repeated zero-sum games, in a setting where the players have access to oracles that compute, in constant time, their best-response to any mixed strategy of their opponent. We show that the runtime required for approximating the minimax value of the game in this setting is $\widetilde{\Theta}(\sqrt{N})$, yielding again a quadratic improvement upon the oracle-free setting, where $\widetilde{\Theta}(N)$ is known to be tight

Combined local-density and dynamical mean field theory calculations for the compressed lanthanides Ce, Pr, and Nd

This paper reports calculations for compressed Ce (4f^1), Pr (4f^2), and Nd (4f^3) using a combination of the local-density approximation (LDA) and dynamical mean field theory (DMFT), or LDA+DMFT. The 4f moment, spectra, and the total energy among other properties are examined as functions of volume and atomic number for an assumed face-centered cubic (fcc) structure.Comment: 15 pages, 9 figure

Low-frequency incommensurate magnetic response in strongly correlated systems

It is shown that in the t-J model of Cu-O planes at low frequencies the dynamic spin structure factor is peaked at incommensurate wave vectors (1/2+-delta,1/2)$, (1/2,1/2+-delta). The incommensurability is connected with the momentum dependencies of the magnon frequency and damping near the antiferromagnetic wave vector. The behavior of the incommensurate peaks is similar to that observed in La_{2-x}(Ba,Sr)_xCuO_{4+y} and YBa_2Cu_3O_{7-y}: for hole concentrations 0.02<x<=0.12 we find that delta is nearly proportional to x, while for x>0.12 it tends to saturation. The incommensurability disappears with increasing temperature. Generally the incommensurate magnetic response is not accompanied by an inhomogeneity of the carrier density.Comment: 4 pages, 4 figure

Doping-dependent study of the periodic Anderson model in three dimensions

We study a simple model for $f$-electron systems, the three-dimensional periodic Anderson model, in which localized $f$ states hybridize with neighboring $d$ states. The $f$ states have a strong on-site repulsion which suppresses the double occupancy and can lead to the formation of a Mott-Hubbard insulator. When the hybridization between the $f$ and $d$ states increases, the effects of these strong electron correlations gradually diminish, giving rise to interesting phenomena on the way. We use the exact quantum Monte-Carlo, approximate diagrammatic fluctuation-exchange approximation, and mean-field Hartree-Fock methods to calculate the local moment, entropy, antiferromagnetic structure factor, singlet-correlator, and internal energy as a function of the $f-d$ hybridization for various dopings. Finally, we discuss the relevance of this work to the volume-collapse phenomenon experimentally observed in f-electron systems.Comment: 12 pages, 8 figure

Strongly Correlated Electrons on a Silicon Surface: Theory of a Mott Insulator

We demonstrate theoretically that the electronic ground state of the potassium-covered Si(111)-B surface is a Mott insulator, explicitly contradicting band theory but in good agreement with recent experiments. We determine the physical structure by standard density-functional methods, and obtain the electronic ground state by exact diagonalization of a many-body Hamiltonian. The many-body conductivity reveals a Brinkman-Rice metal-insulator transition at a critical interaction strength; the calculated interaction strength is well above this critical value.Comment: 4 pages; 4 figures included in text; Revte

Pairing, Charge, and Spin Correlations in the Three-Band Hubbard Model

Using the Constrained Path Monte Carlo (CPMC) method, we simulated the two-dimensional, three-band Hubbard model to study pairing, charge, and spin correlations as a function of electron and hole doping and the Coulomb repulsion $V_{pd}$ between charges on neighboring Cu and O lattice sites. As a function of distance, both the $d_{x^2 - y^2}$-wave and extended s-wave pairing correlations decayed quickly. In the charge-transfer regime, increasing $V_{pd}$ decreased the long-range part of the correlation functions in both channels, while in the mixed-valent regime, it increased the long-range part of the s-wave behavior but decreased that of the d-wave behavior. Still the d-wave behavior dominated. At a given doping, increasing $V_{pd}$ increased the spin-spin correlations in the charge-transfer regime but decreased them in the mixed-valent regime. Also increasing $V_{pd}$ suppressed the charge-charge correlations between neighboring Cu and O sites. Electron and hole doping away from half-filling was accompanied by a rapid suppression of anti-ferromagnetic correlations.Comment: Revtex, 8 pages with 15 figure

Dynamical Mean-Field Theory and Its Applications to Real Materials

Dynamical mean-field theory (DMFT) is a non-perturbative technique for the investigation of correlated electron systems. Its combination with the local density approximation (LDA) has recently led to a material-specific computational scheme for the ab initio investigation of correlated electron materials. The set-up of this approach and its application to materials such as (Sr,Ca)VO_3, V_2O_3, and Cerium is discussed. The calculated spectra are compared with the spectroscopically measured electronic excitation spectra. The surprising similarity between the spectra of the single-impurity Anderson model and of correlated bulk materials is also addressed.Comment: 20 pages, 9 figures, invited paper for the JPSJ Special Issue "Kondo Effect - 40 Years after the Discovery"; final version, references adde