The OS* Algorithm: a Joint Approach to Exact Optimization and Sampling

Most current sampling algorithms for high-dimensional distributions are based on MCMC techniques and are approximate in the sense that they are valid only asymptotically. Rejection sampling, on the other hand, produces valid samples, but is unrealistically slow in high-dimension spaces. The OS* algorithm that we propose is a unified approach to exact optimization and sampling, based on incremental refinements of a functional upper bound, which combines ideas of adaptive rejection sampling and of A* optimization search. We show that the choice of the refinement can be done in a way that ensures tractability in high-dimension spaces, and we present first experiments in two different settings: inference in high-order HMMs and in large discrete graphical models.Comment: 21 page

Climatic and edaphic classification at a continental scale (1:5,000,000) for cassava in South America

The different environments (combinations of climatic and edaphic conditions) in which cassava is grown in South America are classified, and the most probable differences between one agroecozone and the next based on environmental factors affecting the cassava plant are presented. A hierarchical approach is used for soil and climate classifications. Specific maps for climates, soils, and a combination of climate-soil homologues for cassava in South America are presented as well as a map of cassava distribution. (CIAT

A note on the distribution of cassava amongst different climate and soil types in South America

The distribution of cassava among different climate and soil types in South America, based on the adopted hierachical classification of soil and climate conditions for cassava, is briefly discussed. Both soil and climate components of the classification have been used to produce a map of environmental homologues for the crop. By subdividing cassava-growing areas on the basis of a simple climatic and edaphic classification, it is apparent that the ecosystems of CIAT`s cassava program cover some important climate-soil homologues; if the system is to be continuously used, a more systematic approach towards soils is required and there are some important semiarid and highland areas that are not currently covered. It is recognized that the cassava program cannot work specifically for all the different classes identified, but the knowledge of their existence and relative importance can help the process of deciding where to work and how many different ecosystems to work for. The organization of data in a microregion framework is seen as a longer-term solution to climatic and edaphic classification problems that arise in the cassava program`s research and planning. (CIAT

The management and memory of fascist monumental art in postwar and contemporary Italy: the case of Luigi Montanarini's apotheosis of fascism

In postwar Germany, the Allies and the German authorities moved quickly and systematically to destroy or physically remove all traces of Nazi art. No such process occurred in postwar Italy. This meant that hundreds of ideologically inspired statues, mosaics, murals and other artefacts survived into the republican period. This article uses Luigi Montanarini’s mural, the Apotheosis of Fascism, as a case study to examine the management, meaning and memory of fascist monumental art (and, more broadly, fascist monumental architecture) in postwar and contemporary Italy. To date, memory studies of fascism have largely overlooked the artistic and architectural legacies of the dictatorship. This article helps to address this historiographical lacuna and speaks to current debates and controversies in Italy surrounding the meaning and significance of historic fascism

Robotics for Distance learning: A Case Study from a UK Masters Programme

The MSc Intelligent Systems (IS) and the MSc Intelligent Systems and Robotics (ISR) programmes at De Montfort University are Masters level courses that are delivered both on-site and by distance learning. The courses have been running successfully on-site for eight years and are now in the fifth year with a distance learning mode. Delivering material at a distance, especially where there is technical and practical content, presents a challenge and in this paper we focus on some of the techniques adopted to overcome the particular challenges encountered in the delivery of Robotics modules

Quantum Algorithm for the Collision Problem

In this note, we give a quantum algorithm that finds collisions in arbitrary r-to-one functions after only O((N/r)^(1/3)) expected evaluations of the function. Assuming the function is given by a black box, this is more efficient than the best possible classical algorithm, even allowing probabilism. We also give a similar algorithm for finding claws in pairs of functions. Furthermore, we exhibit a space-time tradeoff for our technique. Our approach uses Grover's quantum searching algorithm in a novel way.Comment: 8 pages, LaTeX2