CIKM 2020 conference report

2021 ◽  
pp. 1-4
Author(s):  
Mathieu D'Aquin ◽  
Stefan Dietze
Keyword(s):  
United States ◽  
Machine Learning ◽  
Knowledge Management ◽  
Information Retrieval ◽  
Conference Report ◽  
The United States ◽  
Knowledge Based ◽  
The World ◽  
Science Conference ◽  
Information And Knowledge Management

The 29th ACM International Conference on Information and Knowledge Management (CIKM) was held online from the 19 th to the 23 rd of October 2020. CIKM is an annual computer science conference, focused on research at the intersection of information retrieval, machine learning, databases as well as semantic and knowledge-based technologies. Since it was first held in the United States in 1992, 28 conferences have been hosted in 9 countries around the world.

Conclusion

2020 ◽  
pp. 97-102
Author(s):  
Benjamin Wiggins
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Machine Learning ◽  
Risk Assessment ◽  
Big Data ◽  
The United States ◽  
Blaise Pascal ◽  
Division Problem ◽  
The World

Can risk assessment be made fair? The conclusion of Calculating Race returns to actuarial science’s foundations in probability. The roots of probability rest in a pair of problems posed to Blaise Pascal and Pierre de Fermat in the summer of 1654: “the Dice Problem” and “the Division Problem.” From their very foundation, the mathematics of probability offered the potential not only to be used to gain an advantage (as in the case of the Dice Problem), but also to divide material fairly (as in the case of the Division Problem). As the United States and the world enter an age driven by Big Data, algorithms, artificial intelligence, and machine learning and characterized by an actuarialization of everything, we must remember that risk assessment need not be put to use for individual, corporate, or government advantage but, rather, that it has always been capable of guiding how to distribute risk equitably instead.

scholarly journals Analysis of Covid-19 in the United States using Machine Learning

2020 ◽  
Vol 8 (1) ◽  
pp. 15-21
Author(s):  
James G. Koomson
Keyword(s):  
United States ◽  
Machine Learning ◽  
The United States ◽  
Global Level ◽  
Learning Models ◽  
The World ◽  
Day By Day ◽  
Machine Learning Models

The unprecedented outbreak of COVID-19 also known as the coronavirus has caused a pandemic like none ever seen before this century. Its impact has been massive on a global level. The deadly virus has commanded nations around the world to increase their efforts to fight against the spread of the virus after the stress it has put on resources. With the number of new cases increasing day by day around the world, the objective of this paper is to contribute towards the analysis of the virus by leveraging machine learning models to understand its behavior and predict future patterns in the United States (US) based on data obtained from the COVID-19 Tracking Project.

scholarly journals Combining Multi-Source Data and Machine Learning Approaches to Predict Winter Wheat Yield in the Conterminous United States

2020 ◽  
Vol 12 (8) ◽  
pp. 1232 ◽  
Author(s):  
Yumiao Wang ◽  
Zhou Zhang ◽  
Luwei Feng ◽  
Qingyun Du ◽  
Troy Runge
Keyword(s):  
United States ◽  
Machine Learning ◽  
Winter Wheat ◽  
Wheat Yield ◽  
Growing Season ◽  
The United States ◽  
Learning Approaches ◽  
Source Data ◽  
The World ◽  
Winter Wheat Yield

Winter wheat (Triticum aestivum L.) is one of the most important cereal crops, supplying essential food for the world population. Because the United States is a major producer and exporter of wheat to the world market, accurate and timely forecasting of wheat yield in the United States (U.S.) is fundamental to national crop management as well as global food security. Previous studies mainly have focused on developing empirical models using only satellite remote sensing images, while other yield determinants have not yet been adequately explored. In addition, these models are based on traditional statistical regression algorithms, while more advanced machine learning approaches have not been explored. This study used advanced machine learning algorithms to establish within-season yield prediction models for winter wheat using multi-source data to address these issues. Specifically, yield driving factors were extracted from four different data sources, including satellite images, climate data, soil maps, and historical yield records. Subsequently, two linear regression methods, including ordinary least square (OLS) and least absolute shrinkage and selection operator (LASSO), and four well-known machine learning methods, including support vector machine (SVM), random forest (RF), Adaptive Boosting (AdaBoost), and deep neural network (DNN), were applied and compared for estimating the county-level winter wheat yield in the Conterminous United States (CONUS) within the growing season. Our models were trained on data from 2008 to 2016 and evaluated on data from 2017 and 2018, with the results demonstrating that the machine learning approaches performed better than the linear regression models, with the best performance being achieved using the AdaBoost model (R2 = 0.86, RMSE = 0.51 t/ha, MAE = 0.39 t/ha). Additionally, the results showed that combining data from multiple sources outperformed single source satellite data, with the highest accuracy being obtained when the four data sources were all considered in the model development. Finally, the prediction accuracy was also evaluated against timeliness within the growing season, with reliable predictions (R2 > 0.84) being able to be achieved 2.5 months before the harvest when the multi-source data were combined.

Uber: Applying Machine Learning to Improve the Customer Pickup Experience

2019 ◽  
pp. 1-21
Author(s):  
Mohanbir Sawhney ◽  
Birju Shah ◽  
Ryan Yu ◽  
Evgeny Rubtsov ◽  
Pallavi Goodman
Keyword(s):  
United States ◽  
Machine Learning ◽  
Southeast Asia ◽  
Traffic Congestion ◽  
The United States ◽  
Gps Navigation ◽  
Product Manager ◽  
The World ◽  
Group Product

Uber had pioneered the growth and delivery of modern ridesharing services by leveraging the explosive growth of technology, GPS navigation, and smartphones. Ridesharing services had expanded across the world, growing rapidly in the United States, China, India, Europe, and Southeast Asia. Even as these services expanded and gained popularity, however, the pickup experience for drivers and riders did not always meet the expectations of either party. Pickups were complicated by traffic congestion, faulty GPS signals, and crowded pickup venues. Flawed pickups resulted in rider dissatisfaction and in lost revenues for drivers. Uber had identified the pickup experience as a top strategic priority, and a team at Uber, led by group product manager Birju Shah, was tasked with designing an automated solution to improve the pickup experience. This involved three steps. First, the team needed to analyze the pickup experience for various rider personas to identify problems at different stages in the pickup process. Next, it needed to create a model for predicting the best rider location for a pickup. The team also needed to develop a quantitative metric that would determine the quality of the pickup experience. These models and metrics would be used as inputs for a machine learning.

Sex Differences in Mass Media Preferences Across Four Asian Countries

2011 ◽  
Vol 23 (4) ◽  
pp. 186-191 ◽  
Author(s):  
Malini Ratnasingam ◽  
Lee Ellis
Keyword(s):  
United States ◽  
Sex Differences ◽  
Mass Media ◽  
The United States ◽  
Female Students ◽  
The Internet ◽  
Evolutionary Explanation ◽  
Asian Countries ◽  
The World ◽  
Media Preferences

Background. Nearly all of the research on sex differences in mass media utilization has been based on samples from the United States and a few other Western countries. Aim. The present study examines sex differences in mass media utilization in four Asian countries (Japan, Malaysia, South Korea, and Singapore). Methods. College students self-reported the frequency with which they accessed the following five mass media outlets: television dramas, televised news and documentaries, music, newspapers and magazines, and the Internet. Results. Two significant sex differences were found when participants from the four countries were considered as a whole: Women watched television dramas more than did men; and in Japan, female students listened to music more than did their male counterparts. Limitations. A wider array of mass media outlets could have been explored. Conclusions. Findings were largely consistent with results from studies conducted elsewhere in the world, particularly regarding sex differences in television drama viewing. A neurohormonal evolutionary explanation is offered for the basic findings.

Sandra Ramos Revisited

2020 ◽  
Vol 2 (4) ◽  
pp. 32-54
Author(s):  
Silvia Spitta
Keyword(s):  
United States ◽  
The United States ◽  
Ancient Greek ◽  
Graphic Arts ◽  
Left Behind ◽  
The World ◽  
The Usa ◽  
Political Choices ◽  
The Rich

Sandra Ramos (b. 1969) is one of the few artists to reflect critically on both sides of the Cuban di-lemma, fully embodying the etymological origins of the word in ancient Greek: di-, meaning twice, and lemma, denoting a form of argument involving a choice between equally unfavorable alternatives. Throughout her works she shines a light on the dilemmas faced by Cubans whether in Cuba or the United States, underlining the bad personal and political choices people face in both countries. During the hard 1990s, while still in Havana, the artist focused on the traumatic one-way journey into exile by thousands, as well as the experience of profound abandonment experienced by those who were left behind on the island. Today she lives in Miami and operates a studio there as well as one in Havana. Her initial disorientation in the USA has morphed into an acerbic representation and critique of the current administration and a deep concern with the environmental collapse we face. A buffoonlike Trumpito has joined el Bobo de Abela and Liborio in her gallery of comic characters derived from the rich Cuban graphic arts tradition where she was formed. While Cuba is now represented as a rotten cake with menacing flies hovering over it ready to pounce, a bombastic Trumpito marches across the world stage, trampling everything underfoot, a dollar sign for a face.

The Unquiet Frontier

2017 ◽  
Author(s):  
Jakub J. Grygiel ◽  
A. Wess Mitchell ◽  
Jakub J. Grygiel ◽  
A. Wess Mitchell
Keyword(s):  
United States ◽  
The United States ◽  
Great Powers ◽  
Global Order ◽  
American Power ◽  
Alliance Networks ◽  
Effective Strategies ◽  
The World ◽  
The Baltic ◽  
Critical Regions

From the Baltic to the South China Sea, newly assertive authoritarian states sense an opportunity to resurrect old empires or build new ones at America's expense. Hoping that U.S. decline is real, nations such as Russia, Iran, and China are testing Washington's resolve by targeting vulnerable allies at the frontiers of American power. This book explains why the United States needs a new grand strategy that uses strong frontier alliance networks to raise the costs of military aggression in the new century. The book describes the aggressive methods which rival nations are using to test American power in strategically critical regions throughout the world. It shows how rising and revisionist powers are putting pressure on our frontier allies—countries like Poland, Israel, and Taiwan—to gauge our leaders' commitment to upholding the American-led global order. To cope with these dangerous dynamics, nervous U.S. allies are diversifying their national-security “menu cards” by beefing up their militaries or even aligning with their aggressors. The book reveals how numerous would-be great powers use an arsenal of asymmetric techniques to probe and sift American strength across several regions simultaneously, and how rivals and allies alike are learning from America's management of increasingly interlinked global crises to hone effective strategies of their own. The book demonstrates why the United States must strengthen the international order that has provided greater benefits to the world than any in history.

Bringing the Real World of Science to Children: A Partnership of the American Museum of Natural History and the City University of New York

2008 ◽  
Vol 12 (1) ◽  
Author(s):  
Anthony G Picciano ◽  
Robert V. Steiner
Keyword(s):  
United States ◽  
New York ◽  
Natural History ◽  
Local Governments ◽  
Compulsory Education ◽  
Development Program ◽  
The United States ◽  
American Museum ◽  
The World ◽  
The City

Every child has a right to an education. In the United States, the issue is not necessarily about access to a school but access to a quality education. With strict compulsory education laws, more than 50 million students enrolled in primary and secondary schools, and billions of dollars spent annually on public and private education, American children surely have access to buildings and classrooms. However, because of a complex and competitive system of shared policymaking among national, state, and local governments, not all schools are created equal nor are equal education opportunities available for the poor, minorities, and underprivileged. One manifestation of this inequity is the lack of qualified teachers in many urban and rural schools to teach certain subjects such as science, mathematics, and technology. The purpose of this article is to describe a partnership model between two major institutions (The American Museum of Natural History and The City University of New York) and the program designed to improve the way teachers are trained and children are taught and introduced to the world of science. These two institutions have partnered on various projects over the years to expand educational opportunity especially in the teaching of science. One of the more successful projects is Seminars on Science (SoS), an online teacher education and professional development program, that connects teachers across the United States and around the world to cutting-edge research and provides them with powerful classroom resources. This article provides the institutional perspectives, the challenges and the strategies that fostered this partnership.

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