On the universality of low-energy string model

The low-energy (bosonic "heterotic") string theory is interpreted as a universal limit of the Kaluza-Klein reduction when the dimension of an internal space goes to infinity. We show that such an approach is helpful in obtaining classical solutions of the string model. As a particular application, we obtain new exact static solutions for the two-dimensional effective string model. They turn out to be in agreement with the generalized no-hair conjecture, in complete analogy with the four and higher dimensional Einstein theory of gravity.Comment: 11 pages, LATEX, no figure

Real-Time Seamless Single Shot 6D Object Pose Prediction

We propose a single-shot approach for simultaneously detecting an object in an RGB image and predicting its 6D pose without requiring multiple stages or having to examine multiple hypotheses. Unlike a recently proposed single-shot technique for this task (Kehl et al., ICCV'17) that only predicts an approximate 6D pose that must then be refined, ours is accurate enough not to require additional post-processing. As a result, it is much faster - 50 fps on a Titan X (Pascal) GPU - and more suitable for real-time processing. The key component of our method is a new CNN architecture inspired by the YOLO network design that directly predicts the 2D image locations of the projected vertices of the object's 3D bounding box. The object's 6D pose is then estimated using a PnP algorithm. For single object and multiple object pose estimation on the LINEMOD and OCCLUSION datasets, our approach substantially outperforms other recent CNN-based approaches when they are all used without post-processing. During post-processing, a pose refinement step can be used to boost the accuracy of the existing methods, but at 10 fps or less, they are much slower than our method.Comment: CVPR 201

Regret Bounds for Reinforcement Learning with Policy Advice

In some reinforcement learning problems an agent may be provided with a set of input policies, perhaps learned from prior experience or provided by advisors. We present a reinforcement learning with policy advice (RLPA) algorithm which leverages this input set and learns to use the best policy in the set for the reinforcement learning task at hand. We prove that RLPA has a sub-linear regret of \tilde O(\sqrt{T}) relative to the best input policy, and that both this regret and its computational complexity are independent of the size of the state and action space. Our empirical simulations support our theoretical analysis. This suggests RLPA may offer significant advantages in large domains where some prior good policies are provided

Conserved Charges of Higher D Kerr-AdS Spacetimes

We compute the energy and angular momenta of recent D-dimensional Kerr-AdS solutions to cosmological Einstein gravity, as well as of the BTZ metric, using our invariant charge definitions.Comment: 11 pages, references added, equation correcte

A note on the Deser-Tekin charges

Perturbed equations for an arbitrary metric theory of gravity in $D$ dimensions are constructed in the vacuum of this theory. The nonlinear part together with matter fields are a source for the linear part and are treated as a total energy-momentum tensor. A generalized family of conserved currents expressed through divergences of anti-symmetrical tensor densities (superpotentials) linear in perturbations is constructed. The new family generalizes the Deser and Tekin currents and superpotentials in quadratic curvature gravity theories generating Killing charges in dS and AdS vacua. As an example, the mass of the $D$-dimensional Schwarzschild black hole in an effective AdS spacetime (a solution in the Einstein-Gauss-Bonnet theory) is examined.Comment: LATEX, 7 pages, no figure

Shortcuts to Spherically Symmetric Solutions: A Cautionary Note

Spherically symmetric solutions of generic gravitational models are optimally, and legitimately, obtained by expressing the action in terms of the two surviving metric components. This shortcut is not to be overdone, however: a one-function ansatz invalidates it, as illustrated by the incorrect solutions of [1].Comment: 2 pages. Amplified derivation, accepted for publication in Class Quant Gra

Finite-Dimensional Calculus

We discuss topics related to finite-dimensional calculus in the context of finite-dimensional quantum mechanics. The truncated Heisenberg-Weyl algebra is called a TAA algebra after Tekin, Aydin, and Arik who formulated it in terms of orthofermions. It is shown how to use a matrix approach to implement analytic representations of the Heisenberg-Weyl algebra in univariate and multivariate settings. We provide examples for the univariate case. Krawtchouk polynomials are presented in detail, including a review of Krawtchouk polynomials that illustrates some curious properties of the Heisenberg-Weyl algebra, as well as presenting an approach to computing Krawtchouk expansions. From a mathematical perspective, we are providing indications as to how to implement in finite terms Rota's "finite operator calculus".Comment: 26 pages. Added material on Krawtchouk polynomials. Additional references include

Gambler's Ruin Bandit Problem

In this paper, we propose a new multi-armed bandit problem called the Gambler's Ruin Bandit Problem (GRBP). In the GRBP, the learner proceeds in a sequence of rounds, where each round is a Markov Decision Process (MDP) with two actions (arms): a continuation action that moves the learner randomly over the state space around the current state; and a terminal action that moves the learner directly into one of the two terminal states (goal and dead-end state). The current round ends when a terminal state is reached, and the learner incurs a positive reward only when the goal state is reached. The objective of the learner is to maximize its long-term reward (expected number of times the goal state is reached), without having any prior knowledge on the state transition probabilities. We first prove a result on the form of the optimal policy for the GRBP. Then, we define the regret of the learner with respect to an omnipotent oracle, which acts optimally in each round, and prove that it increases logarithmically over rounds. We also identify a condition under which the learner's regret is bounded. A potential application of the GRBP is optimal medical treatment assignment, in which the continuation action corresponds to a conservative treatment and the terminal action corresponds to a risky treatment such as surgery. © 2016 IEEE

Adult Education in Turkey: Stylized Facts, Determinants and Further Issues

We provide a novel set of stylized facts on individuals engaging in adult education using the Adult Education Survey (AES) conducted by TurkStat for the first time. This way we provide the first evidence on the determinants of participation in adult education in a developing country, Turkey. Our results indicate that old, uneducated, workingwomen with uneducated fathers and with young children in the household are less likely to take part in adult education activities in Turkey. However, young, educated, workingmen living in rural areas are more likely to participate in adult education. We also find that past performance of the sector of employment, significantly and positively affects the odds for adult education. Finally, we repeated our analysis for different fields of adult education. Our results suggest that characteristics of men and women who take courses in the most popular fields of education vary

Adult Education in Turkey: Stylized Facts, Determinants and Further Issues

We provide a novel set of stylized facts on individuals engaging in adult education using the Adult Education Survey (AES) conducted by TurkStat for the first time. This way we provide the first evidence on the determinants of participation in adult education in a developing country, Turkey. Our results indicate that old, uneducated, workingwomen with uneducated fathers and with young children in the household are less likely to take part in adult education activities in Turkey. However, young, educated, workingmen living in rural areas are more likely to participate in adult education. We also find that past performance of the sector of employment, significantly and positively affects the odds for adult education. Finally, we repeated our analysis for different fields of adult education. Our results suggest that characteristics of men and women who take courses in the most popular fields of education vary