1,721,095 research outputs found
Smooth numbers are orthogonal to nilsequences
Full text linkThe aim of this paper is to study distributional properties of integers without large or small prime factors. Define an integer to be [y′, y]-smooth if all of its prime factors belong to the interval [y′, y]. We identify suitable weights g[y′,y](n) for the characteristic function of [y′, y]-smooth numbers that allow us to establish strong asymptotic results on their distribution in short arithmetic progressions. Building on these equidistribution properties, we show that (a W-tricked version of) the function g[y′,y](n) − 1 is orthogonal to nilsequences. Our results apply in the almost optimal range (log N)K N1/√log9N asymptotic results on the frequency with which an arbitrary finite complexity system of shifted linear forms ψj (n)+aj ∈ ℤ[n1, …, ns ], 1 ⩽ j ⩽ r, simultaneously takes [y′, y]-smooth values as the ni vary over integers below N.ER
Stabilization of Stochastic Iterative Methods for Singular and Nearly Singular Linear Systems
Full text linkWe consider linear systems of equations, Ax = b, with an emphasis on the case where A is singular. Under certain conditions, necessary as well as sufficient, linear deterministic iterative methods generate sequences {x[subscript k]} that converge to a solution as long as there exists at least one solution. This convergence property can be impaired when these methods are implemented with stochastic simulation, as is often done in important classes of large-scale problems. We introduce additional conditions and novel algorithmic stabilization schemes under which {x[subscript k]} converges to a solution when A is singular and may also be used with substantial benefit when A is nearly singular.United States. Air Force (Grant GA9550-10-1-0412)Los Alamos National Laboratory. Information Science and Technology Institute (Grant 67870-001-08
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Model-Misspecified Offline Reinforcement Learning
No full textWe study offline reinforcement learning (RL) with linear function approximation, a common technique often employed to lift the dependence on the size of the state space. A great volume of existing literature has studied this problem under the realizability assumption, i.e., the underlying transition/value function is indeed a linear function of given features. However, such an assumption rarely holds in practice. In sharp contrast, classic learning theory in supervised learning provides agnostic generalization bound that holds regardless of whether the given function approximation is realizable or not.
In an attempt to theoretically understand the learnability question when the model is outside of the linear realm, we propose a variant of the standard Least Square Value Iteration (LSVI) algorithm and theoretically prove its efficiency. Specifically, we examine the case where the transition model of the MDP is close to having a low rank decomposition but not exactly linear. In contrast to existing works that measure model misspecification by the point-wise error, our result scales only with the expected error under the offline data distribution, a significantly weaker notion that can be much smaller than the point-wise error. Provided with a bound on this population error, we establish a data-dependent upper bound on the suboptimality of Constrained-LSVI for approximately linear MDPs. The upper bound is further accompanied by a lower bound discussion which provides some insight on the information-theoretic limits of the learning process
The Israeli Kibbutz: A Simulation and Analysis on the Optimality of Privatization versus Degrees of Central Planning
No full textThe purpose of this project is to create and evaluate the total utility generated by the individual members of a kibbutz and how this utility compares to similar environments in which individuals are given all or no control over their allocation of resources. Because the kibbutz is mostly studied through a qualitative lens, I create simulated utility curves used to mirror the decision making process of rational individuals within the kibbutz. I begin with a very simplistic and straightforward model intended to mimic social welfare generated from full privatization and full central control. I then elaborate onto this model by introducing finer tuning elements. Following this I vary the level of privatization to further mimic that of a kibbutz and study the subsequent effects. Overall, I found that the introduction of a central planner reduces the overall utility of the society when looking at a single period of time. However, in the long run having a central planner increases the overall utility of the community. In addition, I find that varying the level of privatization in a community affects the utility generated but not the growth. Finally, there is evidence to suggest that the increase in utility of privatized goods is correlated with the variability of the good
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
A Product Generation Algorithm for Revenue and Consumer Rating Optimization
No full textConsumer-facing companies seek to develop brand loyalty and increase their market share by providing the best priced and highest quality products. Some industries have started using consumer review data to power recommendation algorithms that direct consumers toward existing products they may enjoy. In this
thesis, we expand upon this idea by developing a process that uses consumer preferences to come up with ideas for new products to create. This thesis outlines the
idea for a product generation algorithm that identifies important product features
for different consumer groups and generates proposals for products that will have
a high rating and generate high sales
Multi-State Markov Chain Modeling of Health Insurance Claims and Cost Prediction
No full textHealth care costs have increased significantly in the past few decades due to a cost-per-
service incentive structure, which compensates physicians for quantity, not quality, of
treatments. Accordingly, predicting health insurance costs of multi-visit conditions
with accuracy is a problem of wide-reaching importance for insurance companies. This
thesis focuses on modeling health insurance claims of episodic, recurring health prob-
lems as Markov Chains, estimating cycle length and cost, and then pricing associated
health insurance premiums and setting forth a framework for the risk-management
of a health insurance portfolio. The cost and cycle-length estimations modeled in
this thesis affords health insurance companies a way to compare physician treatment
effectiveness and cost effectiveness, to inform them of which physicians to cover
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