TY - JOUR
AB - The performance of several common approximations for the exchange-correlation kernel within time-dependent density-functional theory is tested for elementary excitations in the homogeneous electron gas. Although the adiabatic local-density approximation gives a reasonably good account of the plasmon dispersion, systematic errors are pointed out and traced to the neglect of the wave-vector dependence. Kernels optimized for atoms are found to perform poorly in extended systems due to an incorrect behavior in the long-wavelength limit, leading to quantitative deviations that significantly exceed the experimental error bars for the plasmon dispersion in the alkali metals.
AU - Tatarczyk, Krzysztof
AU - Schindlmayr, Arno
AU - Scheffler, Matthias
ID - 18615
IS - 23
JF - Physical Review B
SN - 0163-1829
TI - Exchange-correlation kernels for excited states in solids
VL - 63
ER -
TY - CONF
AU - Berenbrink, Petra
AU - Brinkmann, André
AU - Scheideler, Christian
ID - 2141
T2 - PDP
TI - SIMLAB-A Simulation Environment for Storage Area Networks
ER -
TY - JOUR
AB - In this paper, it is shown that a correlation criterion is the appropriate criterion for bottom-up clustering to obtain broad phonetic class regression trees for maximum likelihood linear regression (MLLR)-based speaker adaptation. The correlation structure among speech units is estimated on the speaker-independent training data. In adaptation experiments the tree outperformed a regression tree obtained from clustering according to closeness in acoustic space and achieved results comparable with those of a manually designed broad phonetic class tree
AU - Haeb-Umbach, Reinhold
ID - 11778
IS - 3
JF - IEEE Transactions on Speech and Audio Processing
KW - acoustic space
KW - adaptation experiments
KW - automatic generation
KW - bottom-up clustering
KW - broad phonetic class regression trees
KW - correlation criterion
KW - correlation methods
KW - maximum likelihood estimation
KW - maximum likelihood linear regression based speaker adaptation
KW - MLLR adaptation
KW - pattern clustering
KW - phonetic regression class trees
KW - speaker-independent training data
KW - speech recognition
KW - speech units
KW - statistical analysis
KW - trees (mathematics)
TI - Automatic generation of phonetic regression class trees for MLLR adaptation
VL - 9
ER -
TY - CONF
AU - Kolman, Petr
AU - Scheideler, Christian
ID - 2142
T2 - SPAA
TI - Simple on-line algorithms for the maximum disjoint paths problem
ER -
TY - JOUR
AB - We derive a class of computationally inexpensive linear dimension reduction criteria by introducing a weighted variant of the well-known K-class Fisher criterion associated with linear discriminant analysis (LDA). It can be seen that LDA weights contributions of individual class pairs according to the Euclidean distance of the respective class means. We generalize upon LDA by introducing a different weighting function
AU - Loog, M.
AU - Duin, R.P.W.
AU - Haeb-Umbach, Reinhold
ID - 11870
IS - 7
JF - IEEE Transactions on Pattern Analysis and Machine Intelligence
KW - approximate pairwise accuracy
KW - Bayes error
KW - Bayes methods
KW - error statistics
KW - Euclidean distance
KW - Fisher criterion
KW - linear dimension reduction
KW - linear discriminant analysis
KW - pattern classification
KW - statistical analysis
KW - statistical pattern classification
KW - weighting function
TI - Multiclass linear dimension reduction by weighted pairwise Fisher criteria
VL - 23
ER -
TY - JOUR
AB - There is increasing interest in many-body perturbation theory as a practical tool for the calculation of ground-state properties. As a consequence, unambiguous sum rules such as the conservation of particle number under the influence of the Coulomb interaction have acquired an importance that did not exist for calculations of excited-state properties. In this paper we obtain a rigorous, simple relation whose fulfilment guarantees particle-number conservation in a given diagrammatic self-energy approximation. Hedin’s G0W0 approximation does not satisfy this relation and hence violates the particle-number sum rule. Very precise calculations for the homogeneous electron gas and a model inhomogeneous electron system allow the extent of the nonconservation to be estimated.
AU - Schindlmayr, Arno
AU - García-González, Pablo
AU - Godby, Rex William
ID - 18612
IS - 23
JF - Physical Review B
SN - 0163-1829
TI - Diagrammatic self-energy approximations and the total particle number
VL - 64
ER -
TY - CONF
AB - The traditional way to find a linear solution to the feature extraction problem is based on the maximization of the class-between scatter over the class-within scatter (Fisher mapping). For the multi-class problem this is, however, sub-optimal due to class conjunctions, even for the simple situation of normal distributed classes with identical covariance matrices. We propose a novel, equally fast method, based on nonlinear PCA. Although still sub-optimal, it may avoid the class conjunction. The proposed method is experimentally compared with Fisher mapping and with a neural network based approach to nonlinear PCA. It appears to outperform both methods, the first one even in a dramatic way.
AU - Duin, Robert P.W.
AU - Loog, Marco
AU - Haeb-Umbach, Reinhold
ID - 11758
T2 - International Conference on Pattern Recognition (ICPR 2000)
TI - Multi-class Linear Feature Extraction by Nonlinear PCA
ER -
TY - CONF
AU - Berenbrink, Petra
AU - Brinkmann, André
AU - Scheideler, Christian
ID - 2146
T2 - PDPTA
TI - Distributed Path Selection for Storage Networks
ER -
TY - CONF
AU - Czumaj, Artur
AU - Scheideler, Christian
ID - 2211
T2 - 32nd ACM Symposium on Theory of Computing
TI - A New Algorithmic Approach to the General Lovász Local Lemma with Applications to Scheduling and Satisfiability Problems
ER -
TY - CONF
AU - Czumaj, Artur
AU - Scheideler, Christian
ID - 2147
T2 - SODA
TI - Coloring non-uniform hypergraphs: a new algorithmic approach to the general Lovász local lemma
ER -