A Block Minorization--Maximization Algorithm for Heteroscedastic Regression

The computation of the maximum likelihood (ML) estimator for heteroscedastic regression models is considered. The traditional Newton algorithms for the problem require matrix multiplications and inversions, which are bottlenecks in modern Big Data contexts. A new Big Data-appropriate minorization--maximization (MM) algorithm is considered for the computation of the ML estimator. The MM algorithm is proved to generate monotonically increasing sequences of likelihood values and to be convergent to a stationary point of the log-likelihood function. A distributed and parallel implementation of the MM algorithm is presented and the MM algorithm is shown to have differing time complexity to the Newton algorithm. Simulation studies demonstrate that the MM algorithm improves upon the computation time of the Newton algorithm in some practical scenarios where the number of observations is large

A Universal Approximation Theorem for Mixture of Experts Models

The mixture of experts (MoE) model is a popular neural network architecture for nonlinear regression and classification. The class of MoE mean functions is known to be uniformly convergent to any unknown target function, assuming that the target function is from Sobolev space that is sufficiently differentiable and that the domain of estimation is a compact unit hypercube. We provide an alternative result, which shows that the class of MoE mean functions is dense in the class of all continuous functions over arbitrary compact domains of estimation. Our result can be viewed as a universal approximation theorem for MoE models

A study of the kinematics and binary-induced shaping of the planetary nebula HaTr 4

We present the first detailed spatio-kinematical analysis and modelling of the planetary nebula HaTr 4, one of few known to contain a post-common-envelope central star system. Common envelope evolution is believed to play an important role in the shaping of planetary nebulae, but the exact nature of this role is yet to be understood. High spatial- and spectral- resolution spectroscopy of the [OIII]5007 nebular line obtained with VLT-UVES are presented alongside deep narrowband Ha+[NII]6584 imagery obtained using EMMI-NTT, and together the two are used to derive the three-dimensional morphology of HaTr 4. The nebula is found to display an extended ovoid morphology with an enhanced equatorial region consistent with a toroidal waist - a feature believed to be typical amongst planetary nebulae with post-common-envelope central stars. The nebular symmetry axis is found to lie perpendicular to the orbital plane of the central binary, concordant with the idea that the formation and evolution of HaTr 4 has been strongly influenced by its central binary.Comment: 9 pages, 5 figures, accepted for publication in MNRA

A Buffer Stocks Model for Stabilizing Price of Staple Food with Considering the Expectation of Non Speculative Wholesaler

This paper is a study of price stabilization in the staple food distribution system. All stakeholders experience market risks due to some possibility causes of price volatility. Many models of price stabilization had been developed by employing several approaches such as floor-ceiling prices, buffer funds, export or import taxes, and subsidies. In the previous researches, the models were expanded to increase the purchasing price for producer and decrease the selling price for consumer. Therefore, the policy can influence the losses for non-speculative wholesaler that is reflected by the descending of selling quantity and ascending of the stocks. The objective of this model is not only to keep the expectation of both producer and consumer, but also to protect non-speculative wholesaler from the undesirable result of the stabilization policy. A nonlinear programming model was addressed to determine the instruments of intervention program. Moreover, the result shows that the wholesaler behavior affects the intervention costs. Index Terms Buffer stocks, Price stabilization, Nonlinear programming, Wholesaler behavior

Implementation of a Deutsch-like quantum algorithm utilizing entanglement at the two-qubit level, on an NMR quantum information processor

We describe the experimental implementation of a recently proposed quantum algorithm involving quantum entanglement at the level of two qubits using NMR. The algorithm solves a generalisation of the Deutsch problem and distinguishes between even and odd functions using fewer function calls than is possible classically. The manipulation of entangled states of the two qubits is essential here, unlike the Deutsch-Jozsa algorithm and the Grover's search algorithm for two bits.Comment: 4 pages, two eps figure

Quantum search without entanglement

Entanglement of quantum variables is usually thought to be a prerequisite for obtaining quantum speed-ups of information processing tasks such as searching databases. This paper presents methods for quantum search that give a speed-up over classical methods, but that do not require entanglement. These methods rely instead on interference to provide a speed-up. Search without entanglement comes at a cost: although they outperform analogous classical devices, the quantum devices that perform the search are not universal quantum computers and require exponentially greater overhead than a quantum computer that operates using entanglement. Quantum search without entanglement is compared to classical search using waves.Comment: 9 pages, TeX, submitted to Physical Review Letter

Proof Relevant Corecursive Resolution

Resolution lies at the foundation of both logic programming and type class context reduction in functional languages. Terminating derivations by resolution have well-defined inductive meaning, whereas some non-terminating derivations can be understood coinductively. Cycle detection is a popular method to capture a small subset of such derivations. We show that in fact cycle detection is a restricted form of coinductive proof, in which the atomic formula forming the cycle plays the role of coinductive hypothesis. This paper introduces a heuristic method for obtaining richer coinductive hypotheses in the form of Horn formulas. Our approach subsumes cycle detection and gives coinductive meaning to a larger class of derivations. For this purpose we extend resolution with Horn formula resolvents and corecursive evidence generation. We illustrate our method on non-terminating type class resolution problems.Comment: 23 pages, with appendices in FLOPS 201

Universal simulation of Hamiltonian dynamics for qudits

What interactions are sufficient to simulate arbitrary quantum dynamics in a composite quantum system? Dodd et al. (quant-ph/0106064) provided a partial solution to this problem in the form of an efficient algorithm to simulate any desired two-body Hamiltonian evolution using any fixed two-body entangling N-qubit Hamiltonian, and local unitaries. We extend this result to the case where the component systems have D dimensions. As a consequence we explain how universal quantum computation can be performed with any fixed two-body entangling N-qudit Hamiltonian, and local unitaries.Comment: 13 pages, an error in the "Pauli-Euclid-Gottesman Lemma" fixed, main results unchange