Results for "Anna Choromanska"

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VisualBackProp for learning using privileged information with CNNsMay 24 2018In many machine learning applications, from medical diagnostics to autonomous driving, the availability of prior knowledge can be used to improve the predictive performance of learning algorithms and incorporate `physical,' `domain knowledge,' or `common ... More
Stochastic Bound MajorizationSep 22 2013Recently a majorization method for optimizing partition functions of log-linear models was proposed alongside a novel quadratic variational upper-bound. In the batch setting, it outperformed state-of-the-art first- and second-order optimization methods ... More
LdSM: Logarithm-depth Streaming Multi-label Decision TreesMay 24 2019We consider multi-label classification where the goal is to annotate each data point with the most relevant $\textit{subset}$ of labels from an extremely large label set. Efficient annotation can be achieved with balanced tree predictors, i.e. trees with ... More
LdSM: Logarithm-depth Streaming Multi-label Decision TreesMay 24 2019Jun 03 2019We consider multi-label classification where the goal is to annotate each data point with the most relevant $\textit{subset}$ of labels from an extremely large label set. Efficient annotation can be achieved with balanced tree predictors, i.e. trees with ... More
Logarithmic Time Online Multiclass predictionJun 06 2014Nov 14 2015We study the problem of multiclass classification with an extremely large number of classes (k), with the goal of obtaining train and test time complexity logarithmic in the number of classes. We develop top-down tree construction approaches for constructing ... More
Simultaneous Learning of Trees and Representations for Extreme Classification and Density EstimationOct 14 2016Mar 02 2017We consider multi-class classification where the predictor has a hierarchical structure that allows for a very large number of labels both at train and test time. The predictive power of such models can heavily depend on the structure of the tree, and ... More
Notes on using Determinantal Point Processes for Clustering with Applications to Text ClusteringOct 26 2014In this paper, we compare three initialization schemes for the KMEANS clustering algorithm: 1) random initialization (KMEANSRAND), 2) KMEANS++, and 3) KMEANSD++. Both KMEANSRAND and KMEANS++ have a major that the value of k needs to be set by the user ... More
LSALSA: Accelerated Source Separation via Learned Sparse CodingFeb 13 2018Jun 07 2019We propose an efficient algorithm for the generalized sparse coding (SC) inference problem. The proposed framework applies to both the single dictionary setting, where each data point is represented as a sparse combination of the columns of one dictionary ... More
On the boosting ability of top-down decision tree learning algorithm for multiclass classificationMay 17 2016We analyze the performance of the top-down multiclass classification algorithm for decision tree learning called LOMtree, recently proposed in the literature Choromanska and Langford (2014) for solving efficiently classification problems with very large ... More
Deep learning with Elastic Averaging SGDDec 20 2014Oct 25 2015We study the problem of stochastic optimization for deep learning in the parallel computing environment under communication constraints. A new algorithm is proposed in this setting where the communication and coordination of work among concurrent processes ... More
LSALSA: efficient sparse coding in single and multiple dictionary settingsFeb 13 2018We propose an efficient sparse coding (SC) framework for obtaining sparse representation of data. The proposed framework is very general and applies to both the single dictionary setting, where each data point is represented as a sparse combination of ... More
Invertible Autoencoder for domain adaptationFeb 10 2018The unsupervised image-to-image translation aims at finding a mapping between the source ($A$) and target ($B$) image domains, where in many applications aligned image pairs are not available at training. This is an ill-posed learning problem since it ... More
Entropy-SGD: Biasing Gradient Descent Into Wide ValleysNov 06 2016Dec 05 2016This paper proposes a new optimization algorithm called Entropy-SGD for training deep neural networks that is motivated by the local geometry of the energy landscape at solutions found by gradient descent. Local extrema with low generalization error have ... More
Entropy-SGD: Biasing Gradient Descent Into Wide ValleysNov 06 2016This paper proposes a new optimization algorithm called Entropy-SGD for training deep neural networks that is motivated by the local geometry of the energy landscape at solutions found by gradient descent. Local extrema with low generalization error have ... More
Simultaneous Learning of Trees and Representations for Extreme Classification, with Application to Language ModelingOct 14 2016This paper addresses the problem of multi-class classification with an extremely large number of classes, where the class predictor is learned jointly with the data representation, as is the case in language modeling problems. The predictor admits a hierarchical ... More
Differentially- and non-differentially-private random decision treesOct 26 2014Feb 05 2015We consider supervised learning with random decision trees, where the tree construction is completely random. The method is popularly used and works well in practice despite the simplicity of the setting, but its statistical mechanism is not yet well-understood. ... More
Entropy-SGD: Biasing Gradient Descent Into Wide ValleysNov 06 2016Nov 13 2016This paper proposes a new optimization algorithm called Entropy-SGD for training deep neural networks that is motivated by the local geometry of the energy landscape at solutions found by gradient descent. Local extrema with low generalization error have ... More
Semistochastic Quadratic Bound MethodsSep 05 2013Feb 17 2014Partition functions arise in a variety of settings, including conditional random fields, logistic regression, and latent gaussian models. In this paper, we consider semistochastic quadratic bound (SQB) methods for maximum likelihood inference based on ... More
Skin Lesion Segmentation and Classification with Deep Learning SystemFeb 16 2019Melanoma is one of the ten most common cancers in the US. Early detection is crucial for survival, but often the cancer is diagnosed in the fatal stage. Deep learning has the potential to improve cancer detection rates, but its applicability to melanoma ... More
Adversarial Learning-Based On-Line Anomaly Monitoring for Assured AutonomyNov 12 2018The paper proposes an on-line monitoring framework for continuous real-time safety/security in learning-based control systems (specifically application to a unmanned ground vehicle). We monitor validity of mappings from sensor inputs to actuator commands, ... More
The Loss Surfaces of Multilayer NetworksNov 30 2014Jan 21 2015We study the connection between the highly non-convex loss function of a simple model of the fully-connected feed-forward neural network and the Hamiltonian of the spherical spin-glass model under the assumptions of: i) variable independence, ii) redundancy ... More
Leader Stochastic Gradient Descent for Distributed Training of Deep Learning ModelsMay 24 2019We consider distributed optimization under communication constraints for training deep learning models. We propose a new algorithm, whose parameter updates rely on two forces: a regular gradient step, and a corrective direction dictated by the currently ... More
Towards Automated Melanoma Detection with Deep Learning: Data Purification and AugmentationFeb 16 2019May 14 2019Melanoma is one of the ten most common cancers in the US. Early detection is crucial for survival, but often the cancer is diagnosed in the fatal stage. Deep learning has the potential to improve cancer detection rates, but its applicability to melanoma ... More
VisualBackProp: visualizing CNNs for autonomous drivingNov 16 2016This paper proposes a new method, that we call VisualBackProp, for visualizing which sets of pixels of the input image contribute most to the predictions made by the convolutional neural network (CNN). The method heavily hinges on exploring the intuition ... More
Explaining How a Deep Neural Network Trained with End-to-End Learning Steers a CarApr 25 2017As part of a complete software stack for autonomous driving, NVIDIA has created a neural-network-based system, known as PilotNet, which outputs steering angles given images of the road ahead. PilotNet is trained using road images paired with the steering ... More
Wasserstein Reinforcement LearningJun 11 2019We propose behavior-driven optimization via Wasserstein distances (WDs) to improve several classes of state-of-the-art reinforcement learning (RL) algorithms. We show that WD regularizers acting on appropriate policy embeddings efficiently incorporate ... More
Binary embeddings with structured hashed projectionsNov 16 2015Jul 01 2016We consider the hashing mechanism for constructing binary embeddings, that involves pseudo-random projections followed by nonlinear (sign function) mappings. The pseudo-random projection is described by a matrix, where not all entries are independent ... More
Wasserstein Reinforcement LearningJun 11 2019Jun 19 2019We propose behavior-driven optimization via Wasserstein distances (WDs) to improve several classes of state-of-the-art reinforcement learning (RL) algorithms. We show that WD regularizers acting on appropriate policy embeddings efficiently incorporate ... More
VisualBackProp: efficient visualization of CNNsNov 16 2016May 19 2017This paper proposes a new method, that we call VisualBackProp, for visualizing which sets of pixels of the input image contribute most to the predictions made by the convolutional neural network (CNN). The method heavily hinges on exploring the intuition ... More
Structured adaptive and random spinners for fast machine learning computationsOct 19 2016We consider an efficient computational framework for speeding up several machine learning algorithms with almost no loss of accuracy. The proposed framework relies on projections via structured matrices that we call Structured Spinners, which are formed ... More
A Deep Unsupervised Learning Approach Toward MTBI Identification Using Diffusion MRIFeb 08 2018Mild traumatic brain injury (mTBI) is a growing public health problem with an estimated incidence of one million people annually in US. Neurocognitive tests have been used to both assess the patient condition and to monitor the patient progress. This ... More
Structured adaptive and random spinners for fast machine learning computationsOct 19 2016Nov 26 2016We consider an efficient computational framework for speeding up several machine learning algorithms with almost no loss of accuracy. The proposed framework relies on projections via structured matrices that we call Structured Spinners, which are formed ... More
Entropy-SGD: Biasing Gradient Descent Into Wide ValleysNov 06 2016Apr 21 2017This paper proposes a new optimization algorithm called Entropy-SGD for training deep neural networks that is motivated by the local geometry of the energy landscape. Local extrema with low generalization error have a large proportion of almost-zero eigenvalues ... More
A Deep Unsupervised Learning Approach Toward MTBI Identification Using Diffusion MRIFeb 08 2018Apr 11 2018Mild traumatic brain injury is a growing public health problem with an estimated incidence of over 1.7 million people annually in US. Diagnosis is based on clinical history and symptoms, and accurate, concrete measures of injury are lacking. This work ... More
Structured adaptive and random spinners for fast machine learning computationsOct 19 2016Oct 28 2016We consider an efficient computational framework for speeding up several machine learning algorithms with almost no loss of accuracy. The proposed framework relies on projections via structured matrices that we call Structured Spinners, which are formed ... More
Beyond Backprop: Online Alternating Minimization with Auxiliary VariablesJun 24 2018Feb 01 2019We propose a novel online alternating minimization (AltMin) algorithm for training deep neural networks, provide theoretical convergence guarantees and demonstrate its advantages on several classification tasks as compared both to standard backpropagation ... More
Beyond Backprop: Online Alternating Minimization with Auxiliary VariablesJun 24 2018Jun 05 2019Despite significant recent advances in deep neural networks, training them remains a challenge due to the highly non-convex nature of the objective function. State-of-the-art methods rely on error backpropagation, which suffers from several well-known ... More
Anomalous Hall and Nernst effects in a two-dimensional electron gas with an anisotropic cubic Rashba spin-orbit interactionJun 28 2019The anomalous Hall and Nernst effects are considered theoretically within Matsubara-Green's function formalism. The effective Hamiltonian of a magnetized two-dimensional electron gas with cubic Rashba spin-orbit interaction may describe transport properties ... More
Maximally informative ensembles for SIC-POVMs in dimension 3Apr 30 2014Nov 16 2014In order to find out for which initial states of the system the uncertainty of the measurement outcomes will be minimal, one can look for the minimizers of the Shannon entropy of the measurement. In case of group covariant measurements this question becomes ... More
Strong electroweak symmetry breaking (or, if no SM Higgs, then what?)Jun 08 2012While the LHC takes on the challenge of experimentally exploring the electroweak symmetry breaking sector, it is not only interesting but also crucial to explore alternatives to the Standard Model scenario with an elementary scalar Higgs boson. The idea ... More
Detection techniques for the H.E.S.S. II telescope, data modeling of gravitational lensing and emission of blazars in HE-VHE astronomyJul 15 2013This thesis presents the study of four aspects of high energy astronomy. The first part of the thesis is dedicated to an aspect of instrument development for imaging atmospheric Cherenkov telescopes, namely the Level 2 trigger system of the High Energy ... More
Two-weight norm inequalities for potential type and maximal operators in a metric spaceMay 13 2011Dec 31 2012We characterize two-weight norm inequalities for potential type integral operators in terms of Sawyer-type testing conditions. Our result is stated in a space of homogeneous type with no additional geometric assumptions, such as group structure or non-empty ... More
Generalized channels: channels for convex subsets of the state spaceMay 10 2011Mar 12 2012Let $K$ be a convex subset of the state space of a finite dimensional $C^*$-algebra. We study the properties of channels on $K$, which are defined as affine maps from $K$ into the state space of another algebra, extending to completely positive maps on ... More
Geodesic distances on density matricesDec 17 2003We find an upper bound for geodesic distances associated to monotone Riemannian metrics on positive definite matrices and density matrices.
Extremality conditions for generalized channelsApr 12 2012A generalized channel is a completely positive map that preserves trace on a given subspace. We find conditions under which a generalized channel with respect to a positively generated subspace J is an extreme point in the set of all such generalized ... More
Current-carrying molecules: a real space pictureJun 30 2005An approach is presented to calculate characteristic current vs voltage curves for isolated molecules without explicit description of leads. The Hamiltonian for current-carrying molecules is defined by making resort to Lagrange multipliers, while the ... More
The Fokker-Planck equation for bistable potential in the optimized expansionNov 21 2001The optimized expansion is used to formulate a systematic approximation scheme to the probability distribution of a stochastic system. The first order approximation for the one-dimensional system driven by noise in an anharmonic potential is shown to ... More
A new structural approach to isoparametric hypersurfaces in spheresOct 22 2014The classification of isoparametric hypersurfaces in spheres with four or six different principal curvatures is still not complete. In this paper we develop a structural approach that may be helpful for a classification. Instead of working with the isoparametric ... More
Stellar Archaeology: New Science with Old StarsDec 06 2010The abundance patterns of metal-poor stars provide us a wealth of chemical information about various stages of cosmic chemical evolution. In particular, these stars allow us to study the formation and evolution of the elements, and the involved nucleosynthesis ... More
On Non-Gaussian Limiting Laws for the Certain Statistics of the Wigner MatricesJan 14 2012We continue investigations of our previous papers, in which there were proved central limit theorems (CLT) for linear eigenvalue statistics Tr f(M_n) and there were found the limiting probability laws for the normalised matrix elements of differential ... More
MCRG study of 12 fundamental flavors with mixed fundamental-adjoint gauge actionDec 28 2011I discuss the infrared behavior of the SU(3) gauge model with 12 fundamental fermions. Using a Monte Carlo renormalization group technique I investigate the fixed point structure in the chiral limit and show that this system has an infrared fixed point ... More
Infrared fixed point of the 12-fermion SU(3) gauge model based on 2-lattice MCRG matchingJun 27 2011I investigate an SU(3) gauge model with 12 fundamental fermions. The physically interesting region of this strongly coupled system can be influenced by an ultraviolet fixed point due to lattice artifacts. I suggest to use a gauge action with an additional ... More
Scaling properties of many-fermion systems from MCRG studiesNov 03 2009Monte Carlo renormalization group methods were designed to study the phase structure and critical behavior of statistical systems. They are well suited to determine the running coupling and to investigate the properties of fixed points of gauge-fermion ... More
Transversals in completely reducible multiary quasigroups and in multiary quasigroups of order 4Dec 06 2016An $n$-ary quasigroup $f$ of order $q$ is an $n$-ary operation over a set of cardinality $q$ such that the Cayley table of the operation is an $n$-dimensional latin hypercube of order $q$. A transversal in a quasigroup $f$ (or in the corresponding latin ... More
Rényi relative entropies and noncommutative $L_p$-spaces IIJun 30 2017We show the relation between two versions of sandwiched R\'enyi relative entropies for von Neumann algebras, introduced recently in [M. Berta et al, arXiv:1608.05317] and [A. Jen\v{c}ov\'a, arXiv:1609.08462]. It is also proved that equality in data processing ... More
Spin-structures on real Bott manifolds with Kähler structuresMar 24 2017Let M be a real Bott manifold with K\"{a}hler structure. Using Ishida characterization we give necessary and sufficient condition for the existence of the Spin-structure on M. In proof we use the technic developed in Popko, Szczepa\'{n}ski "Cohomological ... More
On the convex structure of process POVMsAug 03 2015Measurements on quantum channels are described by so-called process operator valued measures, or process POVMs. We study implementing schemes of extremal process POVMs. As it turns out, the corresponding measurement must satisfy certain extremality property, ... More
Pure spinor indications of ultraviolet finiteness in D=4 maximal supergravityJun 24 2015Aug 17 2015The ultraviolet divergences of amplitude diagrams in maximal supergravity are characterised by a first possible divergence at seven loops for the 4-point amplitude (logarithmic) and, in its absence, at eight loops. We revisit the pure spinor superfield ... More
Self-similarity of Jankins-Neumann zigguratMar 10 2015Primarily having emerged from a topological question, Jankins-Neumann ziggurat also appears in the theory of dynamical systems on the circle. It describes an answer to the following question: given the rotation numbers of two orientation-preserving circle ... More
Ultraviolet divergences in maximal supergravity from a pure spinor point of viewDec 18 2014Aug 17 2015The ultraviolet divergences of amplitude diagrams in maximal supergravity are investigated using the pure spinor superfield formalism in maximal supergravity, with maximally supersymmetric Yang-Mills theory for reference. We comment on the effects of ... More
Rigorous enclosures of rotation numbers by interval methodsSep 24 2015We apply set-valued numerical methods to compute an accurate enclosure of the rotation number. The described algorithm is supplemented with a method of proving the existence of periodic points, which is used to check the rationality of the rotation number. ... More
Almost invariance of distributions for random walks on groupsMar 04 2016Apr 28 2016We study the neighborhoods of a typical point $Z_n$ visited at $n$-th step of a random walk, determined by the condition that the transition probabilities stay close to $\mu^{*n}(Z_n)$. If such neighborhood contains a ball of radius $C \sqrt{n}$, we say ... More
Some Closed Classes of Three-Valued Logic Generated by Periodic Symmetric FunctionsApr 15 2016Closed classes of three-valued logic generated by periodic symmetric funtions that equal $1$ in tuples from $\{1,2\}^n$ and equal $0$ on the rest tuples are considered. Criteria for bases existence and finite bases existence for these classes is obtained. ... More
Comparison of quantum channels and statistical experimentsJan 24 2016Apr 24 2016For a pair of quantum channels with the same input space, we show that the possibility of approximation of one channel by post-processings of the other channel can be characterized by comparing the success probabilities for the two ensembles obtained ... More
What made discy galaxies giant?Oct 03 2017I studied giant discy galaxies with optical radii more than 30 kpc. The comparison of these systems with discy galaxies of moderate sizes revealed that they tend to have higher rotation velocities, B-band luminosities, HI masses and dark-to-luminous mass ... More
Building flat space-time from information exchange between quantum fluctuationsMar 05 2019We consider a hypothesis in which classical space-time emerges from information exchange (interactions) between quantum fluctuations in the gravity theory. In this picture, a line element would arise as a statistical average of how frequently particles ... More
Heritability estimation of diseases in case-control studiesNov 09 2016In the field of genetics, the concept of heritability refers to the proportion of variations of a biological trait or disease that can be explained by genetic factors. Quantifying the heritability of a disease is a fundamental challenge in human genetics, ... More
Supersymmetric Seesaw without Singlet Neutrinos: Neutrino Masses and Lepton-Flavour ViolationJul 01 2002Jul 08 2002We consider the supersymmetric seesaw mechanism induced by the exchange of heavy SU(2)_W triplet states, rather than `right-handed' neutrino singlets, to generate neutrino masses. We show that in this scenario the neutrino flavour structure tested at ... More
A counterpart of the Verlinde algebra for the small quantum groupJul 19 2001May 07 2002Let $\bar{Pr}$ denote the ideal spanned by the characters of projective modules in the Grothendieck ring of the category of finite dimensional modules over the small quantum group $u_l$. We show that $\bar{Pr}$ admits a description completely parallel ... More
Resolutions of p-stratifolds with isolated singularitiesNov 18 2003Recently M. Kreck introduced a class of stratified spaces called p-stratifolds [M. Kreck, Stratifolds, Preprint]. He defined and investigated resolutions of p-stratifolds analogously to resolutions of algebraic varieties. In this note we study a very ... More
Gauss diagrams of 3-manifoldsAug 06 2003We present a simple combinatorial method to encode 3-dimensional manifolds, based on their Heegaard diagrams. The notion of a Gauss diagram of a 3-manifold is introduced. We check the conditions for a Gauss diagram to represent a closed manifold and a ... More
Stochastic Volterra equations of nonscalar type in Hilbert spaceSep 01 2005Dec 02 2005In the paper stochastic Volterra equations of nonscalar type in Hilbert space are studied. The aim of the paper is to provide some results on stochastic convolution and mild solutions to those Volterra equations. The motivation of the paper comes from ... More
Average optimality for risk-sensitive control with general state spaceApr 03 2007This paper deals with discrete-time Markov control processes on a general state space. A long-run risk-sensitive average cost criterion is used as a performance measure. The one-step cost function is nonnegative and possibly unbounded. Using the vanishing ... More
B-orbits of nilpotent order 2 and link patternsMar 13 2007Sep 03 2008In this paper we describe geometry of orbits of upper triangular matrices of nilpotent order 2 under conjugation by the group of upper triangular invertible matrices in terms of link patterns. Further we apply this description to the computations of the ... More
Description of B-orbit closures of order 2 in upper-triangular matricesDec 15 2003Nov 10 2005Let n_n(C) be the algebra of strictly upper-triangular n x n matrices over the field of complex numbers and X_2 the subset of matrices of nilpotent order 2. Let B_n(C) be the group of invertible upper-triangular matrices acting on n_n(C) by conjugation. ... More
Temporal and spatial regularity of solutions to stochastic Volterra equations of convolution typeDec 06 2012In the paper regularity of solutions to stochastic Volterra equations in a separable Hilbert space is studied. Sufficient conditions for the temporal and spatial regularity of stochastic convolutions corresponding to the equations under consideration ... More
Convolution type stochastic Volterra equationsDec 28 2007The aim of this work is to present, in self-contained form, results concerning fundamental and the most important questions related to linear stochastic Volterra equations of convolution type. The paper is devoted to study the existence and some kind ... More
Maximal type inequalities for linear stochastic Volterra equationsDec 26 2004Nov 29 2005The note is devoted to estimates for convolutions appearing in some class of stochastic Volterra equations. Two maximal inequalities and exponential tail estimate are proved by the fractional method of infinite dimensional stochastic calculus. The paper ... More
Sturmian numeration systems and decompositions to palindromesOct 31 2017Nov 02 2017We extend the classical Ostrowski numeration systems, closely related to Sturmian words, by allowing a wider range of coefficients, so that possible representations of a number $n$ better reflect the structure of the associated Sturmian word. In particular, ... More
Flat connections and Wigner-Yanase-Dyson metricsJul 28 2003On the manifold of positive definite matrices, we investigate the existence of pairs of flat affine connections, dual with respect to a given monotone metric. The connections are defined either using the $\alpha$-embeddings and finding the duals with ... More
A Characterization of almost universal ternary inhomogeneous quadratic polynomials with conductor 2Jan 07 2015An integral quadratic polynomial (with positive definite quadratic part) is called almost universal if it represents all but finitely many positive integers. In this paper, we provide a characterization of almost universal ternary quadratic polynomials ... More
Fundamental Domains in Lorentzian GeometryAug 28 2003Nov 02 2004We consider discrete subgroups Gamma of the simply connected Lie group SU~(1,1), the universal cover of SU(1,1), of finite level, i.e. the subgroup intersects the centre of SU~(1,1) in a subgroup of finite index, this index is called the level of the ... More
Traces in Complex Hyperbolic Triangle GroupsFeb 10 2004Jun 21 2004We present several formulas for the traces of elements in complex hyperbolic triangle groups generated by complex reflections. The space of such groups of fixed signature is of real dimension one. We parameterise this space by a real invariant alpha of ... More
On a new transformation for generalised porous medium equations: from weak solutions to classicalOct 24 2014Nov 07 2015It is well-known that solutions for generalised porous medium equations are, in general, only H\"older continuous. In this note, we propose a new variable substitution for such equations which transforms weak solutions into classical.
Asymptotic expansions for trace functionalsDec 30 2013We obtain Taylor approximations for functionals $V\mapsto Tr(f(H_0+V))$ defined on the bounded self-adjoint operators, where $H_0$ is a self-adjoint operator with compact resolvent and $f$ is a sufficiently nice scalar function, relaxing assumptions on ... More
Generalised global supersolutions with mass control for systems with taxisJun 15 2018May 29 2019The existence of generalised global supersolutions with a control upon the total mass is established for a wide family of parabolic-parabolic chemotaxis systems and general integrable initial data in any space dimension. It is verified that as long as ... More
Investigating the critical properties of beyond-QCD theories using Monte Carlo Renormalization Group matchingJul 06 2009Monte Carlo Renormalization Group (MCRG) methods were designed to study the non-perturbative phase structure and critical behavior of statistical systems and quantum field theories. I adopt the 2-lattice matching method used extensively in the 1980's ... More
Spatial Correlation of the Topological Charge in Pure SU(3) Gauge Theory and in QCDDec 24 1999We study the spatial correlator of the topological charge density operator in pure SU(3) gauge theory and in two flavor QCD. We show that the data for distances up to about 1 fm is consistent with a vacuum consisting of individual instantons and closely ... More
Ambiguity of converting phase-averaged flux into luminosity for millisecond pulsars in gamma raysMay 16 2008Oct 15 2008We study a magnitude of possible over/underestimation of the actual gamma-ray luminosity L_{actual} of a millisecond pulsar when using so-called pseudo luminosity L_{pseudo} which is inferred from a phase-averaged flux. Both, L_{actual} and L_{pseudo} ... More
Composite or elementary? Probing the nature of the HiggsMay 23 2013I discuss consequences of electroweak symmetry breaking by strong dynamics, assuming the existence of a light composite scalar appearing as a pseudo-Goldstone boson of some global symmetry of the new strongly interacting sector. In such a scenario, the ... More
Analysis of EEG signal by Flicker Noise Spectroscopy: Identification of right/left hand movement imaginationOct 14 2014Flicker Noise Spectroscopy (FNS) has been used for the analysis of electroencephalography (EEG) signal related to the movement imagination. The analysis of sensorimotor rhythms in time-frequency maps reveals the event-related desynchronization (ERD) and ... More
Spin Topological Quantum Field TheoriesAug 17 1996Starting from the quantum group SL_q(2,C), we construct operator invariants of 3-cobordisms with spin structure, satisfying the requirements of a topological quantum field theory and refining the Reshetikhin--Turaev and Turaev--Viro models. We establish ... More
A characterization of almost universal ternary quadratic polynomials with odd prime power conductorFeb 07 2014An integral quadratic polynomial (with positive definite quadratic part) is called almost universal if it represents all but finitely many positive integers. In this paper, we introduce the conductor of a quadratic polynomial, and give an effective characterization ... More
Bayesian Analysis of the Conditional Correlation Between Stock Index Returns with Multivariate SV ModelsJul 19 2006In the paper we compare the modelling ability of discrete-time multivariate Stochastic Volatility models to describe the conditional correlations between stock index returns. We consider four trivariate SV models, which differ in the structure of the ... More
Sharp weighted bounds for fractional integral operators in a space of homogeneous typeFeb 29 2012Dec 13 2012We consider a version of M. Riesz fractional integral operator on a space of homogeneous type and show an analogue of the well-known Hardy--Littlewood--Sobolev theorem in this context. In our main result, we investigate the dependence of the operator ... More
Extremal generalized quantum measurementsJul 23 2012Jul 03 2013A measurement on a section K of the set of states of a finite dimensional C*-algebra is defined as an affine map from K to a probability simplex. Special cases of such sections are used in description of quantum networks, in particular quantum channels. ... More
Reversibility conditions for quantum operationsJul 03 2011Jun 20 2012We give a list of equivalent conditions for reversibility of the adjoint of a unital Schwarz map with respect to a set of quantum states. A large class of such conditions is given by preservation of distinguishability measures: f-divergences, L_1 -distance, ... More
The structure of strongly additive states and Markov triplets on the CAR algebraAug 05 2010We find a characterization of states satisfying equality in strong subadditivity of entropy and of Markov triplets on the CAR algebra. For even states, a more detailed structure of the density matrix is given.
Observing the r-Process Signature in the Oldest StarsDec 08 2008The abundance patterns of metal-poor stars provide us a wealth of chemical information about various stages of the chemical evolution of the Galaxy. In particular, these stars allow us to study the formation and evolution of the elements and the involved ... More
Metal-Poor StarsFeb 13 2008The abundance patterns of metal-poor stars provide us a wealth of chemical information about various stages of the chemical evolution of the Galaxy. In particular, these stars allow us to study the formation and evolution of the elements and the involved ... More