An Efficient Bandit Algorithm for Realtime Multivariate Optimization

Optimization is commonly employed to determine the content of web pages, such as to maximize conversions on landing pages or click-through rates on search engine result pages. Often the layout of these pages can be decoupled into several separate decisions. For example, the composition of a landing page may involve deciding which image to show, which wording to use, what color background to display, etc. Such optimization is a combinatorial problem over an exponentially large decision space. Randomized experiments do not scale well to this setting, and therefore, in practice, one is typically limited to optimizing a single aspect of a web page at a time. This represents a missed opportunity in both the speed of experimentation and the exploitation of possible interactions between layout decisions. Here we focus on multivariate optimization of interactive web pages. We formulate an approach where the possible interactions between different components of the page are modeled explicitly. We apply bandit methodology to explore the layout space efficiently and use hill-climbing to select optimal content in realtime. Our algorithm also extends to contextualization and personalization of layout selection. Simulation results show the suitability of our approach to large decision spaces with strong interactions between content. We further apply our algorithm to optimize a message that promotes adoption of an Amazon service. After only a single week of online optimization, we saw a 21% conversion increase compared to the median layout. Our technique is currently being deployed to optimize content across several locations at Amazon.com.Comment: KDD'17 Audience Appreciation Awar

Clinical Outcomes in Men and Women following Total Knee Arthroplasty with a High-Flex Knee: No Clinical Effect of Gender

While it is generally recognized that anatomical differences exist between the male and female knee, the literature generally refutes the clinical need for gender-specific total knee prostheses. It has been found that standard, unisex knees perform as well, or better, in women than men. Recently, high-flex knees have become available that mechanically accommodate increased flexion yet no studies have directly compared the outcomes of these devices in men and women to see if gender-based differences exist. We retrospectively compared the performance of the high-flex Vanguard knee (Biomet, Warsaw, IN) in 716 male and 1,069 female knees. Kaplan-Meier survivorship was 98.5% at 5.6–5.7 years for both genders. After 2 years, mean improvements in Knee Society Knee and Function scores for men and women (50.9 versus 46.3; 26.5 versus 23.1) and corresponding SF-12 Mental and Physical scores (0.2 versus 2.2; 13.7 versus 12.2) were similar with differences not clinically relevant. Postoperative motion gains as a function of preoperative motion level were virtually identical in men and women. This further confirms the suitability of unisex total knee prostheses for both men and women

Parametrização do modelo CANEGRO para as cultivares brasileiras de cana-de-açúcar.

O objetivo do presente trabalho foi a parametrização do modelo CANEGRO para a as cultivares brasileiras IAC 91-1099 e SP 89 1115.Trabalho apresentado na V Mostra de Trabalhos de Estagiários e Bolsistas, Campinas, out. 2009

Análise de sensibilidade local do modelo Canegro/DSSAT.

O objetivo deste trabalho é a determinação dos parâmetros que causam variações no CANEGRO, através da análise de sensibilidade, e a sua segregação pela avaliação de quanto sensível é cada parâmetro no modelo estudado. A análise de sensibilidade foi realizada com a cultivar brasileira de cana-de-açúcar SP 89-1115. Foram utilizados dados meteorológicos de temperatura máxima e mínima, precipitação e radiação solar global da estação meteorológica situada na Escola Superior de Agricultura "Luiz de Queiroz" (ESALQ), da Universidade de São Paulo (USP) em Piracicaba, SP, Brasil, a 22° 42' 30'' Sul e 47° 38' 00'' Oeste, com altitude de 546 metros

Predicting invasive breast cancer versus DCIS in different age groups.

BackgroundIncreasing focus on potentially unnecessary diagnosis and treatment of certain breast cancers prompted our investigation of whether clinical and mammographic features predictive of invasive breast cancer versus ductal carcinoma in situ (DCIS) differ by age.MethodsWe analyzed 1,475 malignant breast biopsies, 1,063 invasive and 412 DCIS, from 35,871 prospectively collected consecutive diagnostic mammograms interpreted at University of California, San Francisco between 1/6/1997 and 6/29/2007. We constructed three logistic regression models to predict the probability of invasive cancer versus DCIS for the following groups: women ≥ 65 (older group), women 50-64 (middle age group), and women < 50 (younger group). We identified significant predictors and measured the performance in all models using area under the receiver operating characteristic curve (AUC).ResultsThe models for older and the middle age groups performed significantly better than the model for younger group (AUC = 0.848 vs, 0.778; p = 0.049 and AUC = 0.851 vs, 0.778; p = 0.022, respectively). Palpability and principal mammographic finding were significant predictors in distinguishing invasive from DCIS in all age groups. Family history of breast cancer, mass shape and mass margins were significant positive predictors of invasive cancer in the older group whereas calcification distribution was a negative predictor of invasive cancer (i.e. predicted DCIS). In the middle age group--mass margins, and in the younger group--mass size were positive predictors of invasive cancer.ConclusionsClinical and mammographic finding features predict invasive breast cancer versus DCIS better in older women than younger women. Specific predictive variables differ based on age

Dynamic model of fracture

We study the failure properties of heterogeneous materials within the framework of the fiber bundle model subject to the global load-sharing rule in which the load failing elements is shared equally among all surviving elements. We develop a simulation technique by using the Langevin equation in order to investigate some characteristics of our model. It is found that the behavior of time to failure tf decreases with an exponential law and the avalanche size distribution present a power law.We study the failure properties of heterogeneous materials within the framework of the fiber bundle model subject to the global load-sharing rule in which the load failing elements is shared equally among all surviving elements. We develop a simulation technique by using the Langevin equation in order to investigate some characteristics of our model. It is found that the behavior of time to failure tf decreases with an exponential law and the avalanche size distribution present a power law