September 2013 arXiv papers — page 13

Luc Deike, Jean-Claude Bacri, Eric Falcon

We experimentally study linear and nonlinear waves on the surface of a fluid covered by an elastic sheet where both tension and flexural waves take place. An optical method is used to obtain the full space-time wave field, and the dispersion relation of waves. When the forcing is increased, a significant nonlinear shift of the dispersion relation is observed

Keyan Zahedi, Georg Martius, Nihat Ay

One of the main challenges in the field of embodied artificial intelligence is the open-ended autonomous learning of complex behaviours. Our approach is to use task-independent, information-driven intrinsic motivation(s) to support task-dependent learning. The work presented here is a preliminary step in which we investigate the predictive information (the m

Michele Cicoli

We review how axion-like particles (ALPs) naturally emerge in the low-energy effective field theory of string compactifications. We focus on the study of their mass spectrum and couplings, stressing that they depend on the mechanism used to fix the moduli. We present concrete examples where either open or closed string modes behave as QCD axions which do not

R. Armillis, G. Lazarides, C. Pallis

A simple extension of the minimal left-right symmetric supersymmetric grand unified theory model is constructed by adding two pairs of superfields. This naturally violates the partial Yukawa unification predicted by the minimal model. After including supergravity corrections, we find that this extended model naturally supports hilltop F-term hybrid inflation

Nicole Karnath, Lisa Prato, Larry Wasserman, Guillermo Torres

We report orbital parameters for two low-mass, pre-main sequence, double-lined spectroscopic binaries VSB 111 and VSB 126. These systems were originally identified as single-lined on the basis of visible-light observations. We obtained high-resolution, infrared spectra with the 10-m Keck II telescope, detected absorption lines of the secondary stars, and mea

Herbert Lange, Angela Ortega

We show that the moduli spaces of non-triple cyclic coverings of genus 2 curves and that of even spin curves of genus 2 are birationally isomorphic via the Prym map. We describe the log canonical models of the moduli space of even spin curves of genus 2 and use this to extend the above birational map.

V. P. Kochereshko, M. V. Durnev, L. Besombes, H. Mariette

The magnetic field effect on phase transitions in electrically neutral bosonic systems is much less studied than those in fermionic systems, such as superconducting or ferromagnetic phase transitions. Nevertheless, composite bosons are strongly sensitive to magnetic fields: both their internal structure and motion as whole particles may be affected. A joint

João L. Costa

We review recent results concerning the spherically symmetric Einstein-scalar field system with positive cosmological constant. We do so by comparing with the classical results of Christodoulou concerning the asymptotically flat case (vanishing cosmological constant) and by discussing some of the issues which have emerged since the publication of our main re

A. M. Souza, I. Rungger, C. D. Pemmaraju, U. Schwingenschloegl

We present a computational scheme for extracting the energy level alignment of a metal/molecule interface, based on constrained density functional theory and local exchange and correlation functionals. The method, applied here to benzene on Li(100), allows us to evaluate charge transfer energies, as well as the spatial distribution of the image charge induce

M. Z. Garaev, S. V. Konyagin

We prove that there exists an absolute constant $c>0$ such that if an arithmetic progression $\cP$ modulo a prime number $p$ does not contain zero and has the cardinality less than $cp$, then it can not be represented as a product of two subsets of cardinality greater than 1, unless $\cP=-\cP$ or $\cP=\{-2r,r,4r\}$ for some residue $r$ modulo $p$.

Necdet Serhat Aybat, Donald Goldfarb, Shiqian Ma

The problem of recovering a low-rank matrix from a set of observations corrupted with gross sparse error is known as the robust principal component analysis (RPCA) and has many applications in computer vision, image processing and web data ranking. It has been shown that under certain conditions, the solution to the NP-hard RPCA problem can be obtained by so

Eric R. Bittner, Carlos Silva

We present a fully quantum-mechanical model of the electronic dynamics of primary photoexcitations in a polymeric semiconductor heterojunction, which includes both polymer stacking and phonon relaxation. By examining the phonon-induced fluctuations in the state-to-state energy gaps and the exact golden-rule rate constants, we conclude that resonant tunnellin

Andrei Gruzinov

Emission spectrum is calculated for a weak axisymmetric pulsar. Also calculated are the observed spectrum, efficiency, and the observed efficiency. The underlying flow of electrons and positrons turns out to be curiously intricate.

Richard G. Morris, Marc Barthelemy

Recent work in the area of interdependent networks has focused on interactions between two systems of the same type. However, an important and ubiquitous class of systems are those involving monitoring and control, an example of interdependence between processes that are very different. In this Article, we introduce a framework for modelling distributed supe

Nicholas J. Wright

Using a new uniform sample of 824 solar and late-type stars with measured X-ray luminosities and rotation periods we have studied the relationship between rotation and stellar activity that is believed to be a probe of the underlying stellar dynamo. Using an unbiased subset of the sample we calculate the power law slope of the unsaturated regime of the activ

Sergey Slizovskiy, Joseph J. Betouras, Sam T. Carr, Jorge Quintanilla

We study the Fermi surface topological transition of the pocket-opening type in a two dimensional Fermi liquid. We find that the paramagnetic fluctuations in an interacting Fermi liquid typically drive the transition first order at zero temperature. We first gain insight from a calculation using second order perturbation theory in the self-energy. This is va

Nicolas Burq, Hans Christianson

We consider the damped wave equation on a manifold with imperfect geometric control. We show the sub-exponential energy decay estimate in \cite{Chr-NC-erratum} is optimal in the case of one hyperbolic periodic geodesic. We show if the equation is overdamped, then the energy decays exponentially. Finally we show if the equation is overdamped but geometric con

T. Lappi, H. Mäntysaari

We study single inclusive hadron production in proton-proton and proton-nucleus collisions in the CGC framework. The parameters in the calculation are determined solely by standard nuclear geometry and by electron-proton deep inelastic scattering data, which is fit using the running coupling BK equation. We show that it is possible to obtain a good fit of th

S. Paron, M. E. Ortega, A. Astort, M. Rubio

We are performing a systematic study of the interstellar medium around extended green objects (EGOs), likely massive young stellar objects driving outflows. EGO G35.04-0.47 is located towards a dark cloud at the northern-west edge of an HII region. Recently, H2 jets were discovered towards this source, mainly towards its southwest, where the H2 1-0 S(1) emis

H. S. Das, B. J. Medhi, S. Wolf, G. Bertrang

We present the optical imaging polarimetric observations of comet C/2009 P1(Garradd) at three different phase angles e.g., 28.2$^\circ$, 28.1$^\circ$ and 21.6$^\circ$. The observations were carried out using IUCAA Faint Object Spectrograph and Camera mounted on Cassegrain focus of the 2-m Telescope of IGO, IUCAA, Pune in R$_{comet}$, R photometric bands, on

Morgan Morancey, Vahagn Nersesyan

We consider a quantum particle in a 1D interval submitted to a potential. The evolution of this particle is controlled using an external electric field. Taking into account the so-called polarizability term in the model (quadratic with respect to the control), we prove global exact controllability in a suitable space for arbitrary potential and arbitrary dip

Claude Baesens, Robert S. MacKay

The saddle-node bifurcation on an invariant circle (SNIC) is one of the codimension-one routes to creation or destruction of a periodic orbit in a continuous-time dynamical system. It governs the transition from resting behaviour to periodic spiking in many class I neurons, for example. Here, as a first step towards theory of networks of such units the effec

Godfrey Gumbs, Andrii Iurov, Danhong Huang, Paula Fekete

A two-dimensional periodic array of scatterers has been introduced to a single layer of graphene in the presence of an external magnetic field perpendicular to the graphene layer. The eigenvalue equation for such a system has been solved numerically to display the structure of split Landau subbands as functions of both wave number and magnetic flux. The effe

Matthieu Anel, André Joyal

We prove that the category of dg-coalgebras is symmetric monoidal closed and that the category of dg-algebras is enriched, tensored, cotensored and strongly monoidal over that of coalgebras. We apply this formalism to reconstruct several known adjunctions, notably the bar-cobar adjunction.

Robert Poltis

Chameleons are a well motivated scalar field that might explain the observed late time accelerated expansion of the universe. Chameleons possess the interesting property that their mass, and hence interaction range, is dependent on the density of their environment. One very appealing feature of chameleons is the potential to test a model of dark energy in a

Jaesub Hong, Branden Allen, Jonathan Grindlay, Barbara Rodrigues

We have assembled a tiled array (220 cm2) of fine pixel (0.6 mm) imaging CZT detectors for a balloon borne wide-field hard X-ray telescope, ProtoEXIST2. ProtoEXIST2 is a prototype experiment for a next generation hard X-ray imager MIRAX-HXI on board Lattes, a spacecraft from the Agencia Espacial Brasilieira. MIRAX will survey the 5 to 200 keV sky of Galactic

Shuanhu Qi, Hans Behringer, Friederike Schmid

We develop a multiscale hybrid scheme for simulations of soft condensed matter systems, which allows one to treat the system at the particle level in selected regions of space, and at the continuum level elsewhere. It is derived systematically from an underlying particle-based model by field theoretic methods. Particles in different representation regions ca

A K Soper, K Page, A Llobet

Empirical potential structure refinement (EPSR) simulations are performed on total neutron scattering data from powder samples of polytetrafluoroethylene (PTFE) and polychlorotrifluoroethylene (PCTFE), both at 300K. For PTFE a number of Bragg peaks are visible in the scattering data and these are found to be consistent with a lattice spacing $a(=b)=5.69(1)$Å

Reinier W. Heeres, Leo P. Kouwenhoven, Valery Zwiller

Surface plasmon polaritons (plasmons) are a combination of light and a collective oscillation of the free electron plasma at metal-dielectric interfaces. This interaction allows sub-wavelength confinement of light, beyond the diffraction limit inherent to dielectric structures. The resulting electromagnetic fields are more intense and the strength of optical

Hedi Regeiba, Jean Ludwig

Motivated by the description of the C*-algebras of 5 dimensional nilpotent Lie groups as algebras of operator fields defined over their spectra, we introduce the family of C* -algebras with norm controlled dual limits and we show that the C* -algebras of the 5 dimensional nilpotents Lie groups belong to this class.

Zhidong Bai, Jiang Hu

Skorokhod's representation theorem states that if on a Polish space, there is defined a weakly convergent sequence of probability measures $μ_n\stackrel{w}\toμ_0,$ as $n\to \infty$, then there exist a probability space $(Ω, \mathscr F, P)$ and a sequence of random elements $X_n$ such that $X_n\to X$ almost surely and $X_n$ has the distribution function $

Aridaman Pandit, Rob J de Boer

Following transmission, HIV-1 evolves into a diverse population, and next generation sequencing enables us to detect variants occurring at low frequencies. Studying viral evolution at the level of whole genomes was hitherto not possible because next generation sequencing delivers relatively short reads. We here provide a proof of principle that whole HIV-1 g

Kyoungchul Kong

We review various theoretical methods for measuring dark matter properties at the Large Hadron Collider.

Hong Liu, Márk Mezei

In this paper we continue the study of renormalized entanglement entropy introduced in [1]. In particular, we investigate its behavior near an IR fixed point using holographic duality. We develop techniques which, for any static holographic geometry, enable us to extract the large radius expansion of the entanglement entropy for a spherical region. We show t

Larry Wasserman, Mladen Kolar, Alessandro Rinaldo

We consider the problem of providing nonparametric confidence guarantees for undirected graphs under weak assumptions. In particular, we do not assume sparsity, incoherence or Normality. We allow the dimension $D$ to increase with the sample size $n$. First, we prove lower bounds that show that if we want accurate inferences with low assumptions then there a

Lisa Benamati, Alessandro Sozzetti, Nuno C. Santos, David W. Latham

In this work we present a study of binary systems in a metal-poor sample of solar type stars. The stars analyzed were rejected from two planet search samples because they were found to be binaries. Using available radial velocity and Hipparcos astrometric data, we apply different methods to find, for every binary system, a possible range of solutions for the

J. Segovia, D. R. Entem, F. Fernandez, E. Hernandez

We review how quark models are able to describe the phenomenology of the charm meson sector. The spectroscopy and decays of charmonium and open charm mesons are described in a particular quark model and compared with the data and the results of other existing models in the literature. A quite reasonable global description of the heavy meson spectra is reache

Satoshi Takabe, Koji Hukushima

Typical behavior of the linear programming problem (LP) is studied as a relaxation of the minimum vertex cover problem, which is a type of the integer programming problem (IP). To deal with the LP and IP by statistical mechanics, a lattice-gas model on the Erdös-Rényi random graphs is analyzed by a replica method. It is found that the LP optimal solution is

Simone Gilardoni, Django Manglunki, Jean-Paul Burnet, Christian Carli

This report sums up in two volumes the first 50 years of operation of the CERN Proton Synchrotron. After an introduction on the genesis of the machine, and a description of its magnet and powering systems, the first volume focuses on some of the many innovations in accelerator physics and instrumentation that it has pioneered, such as transition crossing, RF

Or Zuk, Amnon Amir, Amit Zeisel, Ohad Shamir

We describe the Microbial Community Reconstruction ({\bf MCR}) Problem, which is fundamental for microbiome analysis. In this problem, the goal is to reconstruct the identity and frequency of species comprising a microbial community, using short sequence reads from Massively Parallel Sequencing (MPS) data obtained for specified genomic regions. We formulate

Alejandro Pérez Paz, Juan María García-Lastra, Troels Markussen, Kristian Sommer Thygesen

We review our recent modelling work of carbon nanotubes as potential candidates for heat dissipation in microelectronics cooling. In the first part, we analyze the impact of nanotube defects on their thermal transport properties. In the second part, we investigate the loss of thermal properties of nanotubes in presence of an interface with various substances

Marius Buliga

The chemical concrete machine is a graph rewriting system which uses only local moves (rewrites), seen as chemical reactions involving molecules which are graphs made up by 4 trivalent nodes. It is Turing complete, therefore it might be used as a model of computation in algorithmic chemistry.

Enrico Boasso

In this work it is proved that the Moore-Penrose inverse of the product of $n$-doubly commuting regular $C^*$-algebra elements obeys the so-called reverse order law. Conversely, conditions regarding the reverse order law of the Moore-Penrose inverse are given in order to characterize when $n$-regular elements doubly commute. Furthermore, applications of the

Sanjog Ray, Anuj Sharma

In management education programmes today, students face a difficult time in choosing electives as the number of electives available are many. As the range and diversity of different elective courses available for selection have increased, course recommendation systems that help students in making choices about courses have become more relevant. In this paper

Yuefeng Wu, Giles Hooker

This paper introduces a hierarchical framework to incorporate Hellinger distance methods into Bayesian analysis. We propose to modify a prior over non-parametric densities with the exponential of twice the Hellinger distance between a candidate and a parametric density. By incorporating a prior over the parameters of the second density, we arrive at a hierar

Andrew Butler, Thomas D. Humphries, Pritam Ranjan, Ronald D. Haynes

Gaussian Process (GP) models are popular statistical surrogates used for emulating computationally expensive computer simulators. The quality of a GP model fit can be assessed by a goodness of fit measure based on optimized likelihood. Finding the global maximum of the likelihood function for a GP model is typically very challenging as the likelihood surface

Eugene B. Kolomeisky

In 1952 Dyson put forward a simple and powerful argument indicating that the perturbative expansions of QED are asymptotic. His argument can be related to Chandrasekhar's limit on the mass of a star for stability against gravitational collapse. Combining these two arguments we estimate the optimal number of terms of the QED series to be 3.1(137)^{3/2}=50

S. Kaufmann, S. J. Wagner, O. Tibolla

Chandra observations of the low-energy peaked BL Lac object AP Librae revealed the clear discovery of a non-thermal X-ray jet. AP Lib is the first low energy peaked BL Lac object with an extended non-thermal X-ray jet that shows emission into the VHE range. The X-ray jet has an extension of ~15'' (~ 14 kpc). The X-ray jet morphology is similar to the

E. G. D. Cohen

Is is argued that the stretching experiments done on RNA in water can be described as a reversible process by Classical Thermodynamics.

Shiladitya Sengupta, Thomas B. Schröder, Srikanth Sastry

Dynamical quantities such as the diffusion coefficient and relaxation times for some glass-formers may depend on density and temperature through a specific combination, rather than independently, allowing the representation of data over ranges of density and temperature as a function of a single scaling variable. Such a scaling, referred to as density - temp

Swapan Rana, Preeti Parashar

In a recent article [http://dx.doi.org/10.1103/PhysRevA.87.022340, Phys. Rev. A 87, 022340 (2013)], Yan et al have studied geometric discord for a well known class of bound entangled states. Based on their calculation, they claim "It is found that there exists a nondynamic sudden change in quantum discord" for these states. In this Comment, we critic

Tuukka Hiltunen, Juha Ritala, Topi Siro, Ari harju

In double quantum dot singlet-triplet qubits, the exchange interaction is used in both quantum gate operation and the measurement of the state of the qubit. The exchange can be controlled electronically by applying gate voltage pulses. We simulate the exchange induced charge state transitions in one and two singlet-triplet qubit systems using the exact diago

Eung Jin Chun, Pankaj Sharma

CMS and ATLAS have searched for a doubly-charged boson $H^{\pm\pm}$ which may arise from type II seesaw in the 7 TeV run at the LHC by considering pair or associated production of doubly-charged bosons under the assumption of degenerate triplet scalars. In this work, we consider non-degenerate triplet components with the mass gap $ΔM \sim 1 - 40$ GeV which l

Werner Bernreuther, Christian Bogner, Oliver Dekkers

We analyze, in the antenna subtraction framework, the real radiation antenna functions for processes involving the production of a pair of heavy quarks and two gluons by an uncolored initial state at NNLO QCD. We provide explicit expressions for these functions and discuss their infrared singular behaviour. Our main results are the corresponding integrated a

J. -B. Mosset, A. Stoykov, V. Davydov, M. Hildebrandt

A thermal neutron detector based on ZnS(Ag)/6LiF scintillator, wavelength-shifting fibers (WLS) and silicon photomultipliers (SiPM) is under development at the Paul Scherrer Institute (PSI) for upgrading the POLDI instrument, a pulse-overlap diffractometer. The design of the detector is outlined, and the measurements performed on a single channel prototype a

D. García-Senz, R. M. Cabezón, A. Arcones, A. Relaño

The direct impact of white dwarfs has been suggested as a plausible channel for type Ia supernovae. In spite of their (a priori) rareness, in highly populated globular clusters and in galactic centers, where the amount of white dwarfs is considerable, the rate of violent collisions between two of them might be non-negligible. Even more, there are indications

Yury Arlinskii, Seppo Hassi

Operator-valued $Q$-functions for special pairs of nonnegative selfadjoint extensions of nonnegative not necessarily densely defined operators are defined and their analytical properties are studied. It is shown that the Kre\uın-Ovcharenko statement announced in \cite{KrO2} is valid only for $Q$-functions of densely defined symmetric operators with finite de

Marcello Meldi, Maria Vittoria Salvetti, Pierre Sagaut

A stochastic approach based on generalized Polynomial Chaos (gPC) is used to quantify the error in Large-Eddy Simulation (LES) of a spatially-evolving mixing layer flow and its sensitivity to different simulation parameters, viz. the grid stretching in the streamwise and lateral directions and the subgrid scale model constant ($C_S$). The error is evaluated

Z. Stuchlík, M. Kološ

We study motion of current-carrying string loops in the field of braneworld spherically symmetric black holes and naked singularities. The spacetime is described by the RN geometry with tidal charge b reflecting the non-local tidal effects coming from the external dimension; both positive and negative values of the spacetime parameter b are considered. We re

Sergey Fedoruk, Jerzy Lukierski

We consider the master fields for HS multiplets defined on 10-dimensional tensorial extension \tilde{\cal M} of D=4 space-time described as a coset \tilde{\cal M}={\cal M}/Sl(2;C) of 16-parameter Maxwell group {\cal M}. The tensorial coordinates provide a geometrization of the coupling to constant uniform EM fields. We describe the spinorial model in extende

Martin Hoferichter, Gilberto Colangelo, Massimiliano Procura, Peter Stoffer

Based on analyticity, unitarity, and Lorentz invariance the contribution from hadronic vacuum polarization to the anomalous magnetic moment of the muon is directly related to the cross section of e^+e^- --> hadrons. We review the main difficulties that impede such an approach for light-by-light scattering and identify the required ingredients from experiment

Chao Zhang

In this paper, we present the Bennett-type generalization bounds of the learning process for i.i.d. samples, and then show that the generalization bounds have a faster rate of convergence than the traditional results. In particular, we first develop two types of Bennett-type deviation inequality for the i.i.d. learning process: one provides the generalizatio

Peilin Zhao, Steven Hoi, Jinfeng Zhuang

Conventional learning with expert advice methods assumes a learner is always receiving the outcome (e.g., class labels) of every incoming training instance at the end of each trial. In real applications, acquiring the outcome from oracle can be costly or time consuming. In this paper, we address a new problem of active learning with expert advice, where the

Pengtao Xie, Eric P. Xing

Document clustering and topic modeling are two closely related tasks which can mutually benefit each other. Topic modeling can project documents into a topic space which facilitates effective document clustering. Cluster labels discovered by document clustering can be incorporated into topic models to extract local topics specific to each cluster and global

Satoshi Ejima, Holger Fehske

We examine the ground-state properties of the one-dimensional Edwards spinless fermion transport model by means of large-scale density-matrix renormalization-group calculations. Determining the single-particle gap and the Tomonaga-Luttinger liquid parameter ($K_ρ$) at zero temperature, we prove the existence of a metal-to-insulator quantum phase transition a

Adrian Weller, Tony S. Jebara

Finding the most likely (MAP) configuration of a Markov random field (MRF) is NP-hard in general. A promising, recent technique is to reduce the problem to finding a maximum weight stable set (MWSS) on a derived weighted graph, which if perfect, allows inference in polynomial time. We derive new results for this approach, including a general decomposition th

Luis Gustavo Vianna, Scott Sanner, Leliane Nunes de Barros

Recent advances in symbolic dynamic programming (SDP) combined with the extended algebraic decision diagram (XADD) data structure have provided exact solutions for mixed discrete and continuous (hybrid) MDPs with piecewise linear dynamics and continuous actions. Since XADD-based exact solutions may grow intractably large for many problems, we propose a bound

Deepak Venugopal, Vibhav Gogate

In this paper, we investigate combining blocking and collapsing -- two widely used strategies for improving the accuracy of Gibbs sampling -- in the context of probabilistic graphical models (PGMs). We show that combining them is not straight-forward because collapsing (or eliminating variables) introduces new dependencies in the PGM and in computation-limit

Michal Valko, Nathaniel Korda, Remi Munos, Ilias Flaounas

We tackle the problem of online reward maximisation over a large finite set of actions described by their contexts. We focus on the case when the number of actions is too big to sample all of them even once. However we assume that we have access to the similarities between actions' contexts and that the expected reward is an arbitrary linear function of

Charles Tripp, Ross D. Shachter

We seek to learn an effective policy for a Markov Decision Process (MDP) with continuous states via Q-Learning. Given a set of basis functions over state action pairs we search for a corresponding set of linear weights that minimizes the mean Bellman residual. Our algorithm uses a Kalman filter model to estimate those weights and we have developed a simpler

Yaniv Tenzer, Gal Elidan

We tackle the challenge of efficiently learning the structure of expressive multivariate real-valued densities of copula graphical models. We start by theoretically substantiating the conjecture that for many copula families the magnitude of Spearman's rank correlation coefficient is monotone in the expected contribution of an edge in network, namely the

R. K. Scott, D. G. Dritschel

We provide numerical evidence for the existence of a cascade of filament instabilities in the surface quasigeostrophic system for atmospheric and oceanic motions near a horizontal boundary. The cascade involves geometrically shrinking spatial and temporal scales and implies the singular collapse of the filament width to zero in a finite time. The numerical m

Nitish Srivastava, Ruslan R Salakhutdinov, Geoffrey E. Hinton

We introduce a Deep Boltzmann Machine model suitable for modeling and extracting latent semantic representations from a large unstructured collection of documents. We overcome the apparent difficulty of training a DBM with judicious parameter tying. This parameter tying enables an efficient pretraining algorithm and a state initialization scheme that aids in

Hossein Azari Soufiani, David C. Parkes, Lirong Xia

This paper discusses {General Random Utility Models (GRUMs)}. These are a class of parametric models that generate partial ranks over alternatives given attributes of agents and alternatives. We propose two preference elicitation scheme for GRUMs developed from principles in Bayesian experimental design, one for social choice and the other for personalized c

Ilya Shpitser, Robin J. Evans, Thomas S. Richardson, James M. Robins

Hidden variables are ubiquitous in practical data analysis, and therefore modeling marginal densities and doing inference with the resulting models is an important problem in statistics, machine learning, and causal inference. Recently, a new type of graphical model, called the nested Markov model, was developed which captures equality constraints found in m

Amar Shah, Zoubin Ghahramani

Semi-supervised clustering is the task of clustering data points into clusters where only a fraction of the points are labelled. The true number of clusters in the data is often unknown and most models require this parameter as an input. Dirichlet process mixture models are appealing as they can infer the number of clusters from the data. However, these mode

C. A. Giuppone, M. H. M. Morais, A. C. M. Correia

We test a crossing orbit stability criterion for eccentric planetary systems, based on Wisdom's criterion of first order mean motion resonance overlap (Wisdom, 1980). We show that this criterion fits the stability regions in real exoplanet systems quite well. In addition, we show that elliptical orbits can remain stable even for regions where the apocent

Eleni Sgouritsa, Dominik Janzing, Jonas Peters, Bernhard Schoelkopf

We propose a kernel method to identify finite mixtures of nonparametric product distributions. It is based on a Hilbert space embedding of the joint distribution. The rank of the constructed tensor is equal to the number of mixture components. We present an algorithm to recover the components by partitioning the data points into clusters such that the variab

Nicholas Ruozzi

A recent result has demonstrated that the Bethe partition function always lower bounds the true partition function of binary, log-supermodular graphical models. We demonstrate that these results can be extended to other interesting classes of graphical models that are not necessarily binary or log-supermodular: the ferromagnetic Potts model with a uniform ex

Novi Quadrianto, Viktoriia Sharmanska, David A. Knowles, Zoubin Ghahramani

We propose a probabilistic model to infer supervised latent variables in the Hamming space from observed data. Our model allows simultaneous inference of the number of binary latent variables, and their values. The latent variables preserve neighbourhood structure of the data in a sense that objects in the same semantic concept have similar latent values, an

Marek Petrik, Dharmashankar Subramanian, Janusz Marecki

We propose solution methods for previously-unsolved constrained MDPs in which actions can continuously modify the transition probabilities within some acceptable sets. While many methods have been proposed to solve regular MDPs with large state sets, there are few practical approaches for solving constrained MDPs with large action sets. In particular, we sho

Patrice Perny, Paul Weng, Judy Goldsmith, Josiah Hanna

This paper is devoted to fair optimization in Multiobjective Markov Decision Processes (MOMDPs). A MOMDP is an extension of the MDP model for planning under uncertainty while trying to optimize several reward functions simultaneously. This applies to multiagent problems when rewards define individual utility functions, or in multicriteria problems when rewar

Michael Pacer, Joseph Williams, Xi Chen, Tania Lombrozo

We evaluate four computational models of explanation in Bayesian networks by comparing model predictions to human judgments. In two experiments, we present human participants with causal structures for which the models make divergent predictions and either solicit the best explanation for an observed event (Experiment 1) or have participants rate provided ex

Sigal Oren, Michael Schapira, Moshe Tennenholtz

We introduce the class of pay or play games, which captures scenarios in which each decision maker is faced with a choice between two actions: one with a fixed payoff and an- other with a payoff dependent on others' selected actions. This is, arguably, the simplest setting that models selection among certain and uncertain outcomes in a multi-agent system

Shuzi Niu, Yanyan Lan, Jiafeng Guo, Xueqi Cheng

This paper addresses the problem of rank aggregation, which aims to find a consensus ranking among multiple ranking inputs. Traditional rank aggregation methods are deterministic, and can be categorized into explicit and implicit methods depending on whether rank information is explicitly or implicitly utilized. Surprisingly, experimental results on real dat

Teppo Niinimaki, Mikko Koivisto

Consider a collection of weighted subsets of a ground set N. Given a query subset Q of N, how fast can one (1) find the weighted sum over all subsets of Q, and (2) sample a subset of Q proportionally to the weights? We present a tree-based greedy heuristic, Treedy, that for a given positive tolerance d answers such counting and sampling queries to within a g

Kiyohito Nagano, Yoshinobu Kawahara

A number of discrete and continuous optimization problems in machine learning are related to convex minimization problems under submodular constraints. In this paper, we deal with a submodular function with a directed graph structure, and we show that a wide range of convex optimization problems under submodular constraints can be solved much more efficientl

Joris Mooij, Tom Heskes

We propose a method for learning cyclic causal models from a combination of observational and interventional equilibrium data. Novel aspects of the proposed method are its ability to work with continuous data (without assuming linearity) and to deal with feedback loops. Within the context of biochemical reactions, we also propose a novel way of modeling inte

Elad Mezuman, Daniel Tarlow, Amir Globerson, Yair Weiss

Graphical models with High Order Potentials (HOPs) have received considerable interest in recent years. While there are a variety of approaches to inference in these models, nearly all of them amount to solving a linear program (LP) relaxation with unary consistency constraints between the HOP and the individual variables. In many cases, the resulting relaxa

Ofer Meshi, Elad Eban, Gal Elidan, Amir Globerson

Structured prediction is a powerful framework for coping with joint prediction of interacting outputs. A central difficulty in using this framework is that often the correct label dependence structure is unknown. At the same time, we would like to avoid an overly complex structure that will lead to intractable prediction. In this work we address the challeng

James McInerney, Alex Rogers, Nicholas R. Jennings

In many developing countries, half the population lives in rural locations, where access to essentials such as school materials, mosquito nets, and medical supplies is restricted. We propose an alternative method of distribution (to standard road delivery) in which the existing mobility habits of a local population are leveraged to deliver aid, which raises

Denis D. Maua, Cassio Polpo de Campos, Alessio Benavoli, Alessandro Antonucci

Credal networks are graph-based statistical models whose parameters take values in a set, instead of being sharply specified as in traditional statistical models (e.g., Bayesian networks). The computational complexity of inferences on such models depends on the irrelevance/independence concept adopted. In this paper, we study inferential complexity under the

Brandon Malone, Changhe Yuan

Exact algorithms for learning Bayesian networks guarantee to find provably optimal networks. However, they may fail in difficult learning tasks due to limited time or memory. In this research we adapt several anytime heuristic search-based algorithms to learn Bayesian networks. These algorithms find high-quality solutions quickly, and continually improve the

Marc Maier, Katerina Marazopoulou, David Arbour, David Jensen

The PC algorithm learns maximally oriented causal Bayesian networks. However, there is no equivalent complete algorithm for learning the structure of relational models, a more expressive generalization of Bayesian networks. Recent developments in the theory and representation of relational models support lifted reasoning about conditional independence. This

Sanghack Lee, Vasant Honavar

We introduce z-transportability, the problem of estimating the causal effect of a set of variables X on another set of variables Y in a target domain from experiments on any subset of controllable variables Z where Z is an arbitrary subset of observable variables V in a source domain. z-Transportability generalizes z-identifiability, the problem of estimatin

Akshat Kumar, Daniel Sheldon, Biplav Srivastava

Diffusion processes in networks are increasingly used to model the spread of information and social influence. In several applications in computational sustainability such as the spread of wildlife, infectious diseases and traffic mobility pattern, the observed data often consists of only aggregate information. In this work, we present new models that genera

Oluwasanmi Koyejo, Joydeep Ghosh

We present a novel approach for constrained Bayesian inference. Unlike current methods, our approach does not require convexity of the constraint set. We reduce the constrained variational inference to a parametric optimization over the feasible set of densities and propose a general recipe for such problems. We apply the proposed constrained Bayesian infere

Arindam Khaled, Eric A. Hansen, Changhe Yuan

A limited-memory influence diagram (LIMID) generalizes a traditional influence diagram by relaxing the assumptions of regularity and no-forgetting, allowing a wider range of decision problems to be modeled. Algorithms for solving traditional influence diagrams are not easily generalized to solve LIMIDs, however, and only recently have exact algorithms for so

Jean Honorio, Tommi S. Jaakkola

We propose maximum likelihood estimation for learning Gaussian graphical models with a Gaussian (ell_2^2) prior on the parameters. This is in contrast to the commonly used Laplace (ell_1) prior for encouraging sparseness. We show that our optimization problem leads to a Riccati matrix equation, which has a closed form solution. We propose an efficient algori

Antti Hyttinen, Patrik O. Hoyer, Frederick Eberhardt, Matti Jarvisalo

We present a very general approach to learning the structure of causal models based on d-separation constraints, obtained from any given set of overlapping passive observational or experimental data sets. The procedure allows for both directed cycles (feedback loops) and the presence of latent variables. Our approach is based on a logical representation of c