The document discusses several challenges in machine learning, including:
1) Determining when generative vs. discriminative learning methods are better and how to make generative methods more computationally feasible.
2) Developing methods for learning from non-vectorial data like text, images, and graphs that can work across different data types and learning algorithms.
3) Extending discriminative methods like neural networks and support vector machines to more complex problems beyond classification and regression.
4) Developing distributed learning methods that can handle distributed data while preserving privacy.
This curriculum vita summarizes the educational and professional background of Khaled Rasheed. It lists his positions including Associate Professor at the University of Georgia, education including a Ph.D from Rutgers University, research interests in artificial intelligence techniques and applications, honors and awards, grants, publications, and professional activities. The vita provides a concise overview of Rasheed's qualifications and accomplishments.
The document provides an overview and analysis of machine learning, data mining, and decision support courses available online. It categorizes the courses based on intended audience (computer science students, managers, IT professionals) and provider (universities, commercial organizations). The document also discusses the characteristics of courses within and between categories, and provides examples of specific courses. It concludes with a review of efforts to increase awareness and education around data mining and decision support through the development of seminars, workshops and distance learning activities.
Eric Siegel is a data analytics consultant who has over 20 years of experience applying predictive analytics and data mining to solve business problems. He has held leadership roles defining analytics strategies and developing predictive models for applications such as sales forecasting and customer attrition. Siegel also has experience discovering and preparing data from disparate sources, and communicating technical analytics concepts to business audiences.
UcyQNFG8C16k.docx - Preparation of Ceria Fibers Via ...butest
This document discusses applying a genetic algorithm to solve a vehicle routing problem for a bakery company in Thailand. The problem involves routing delivery vehicles from a single depot to 32 customers while meeting customer demands and vehicle capacity constraints. The document proposes a genetic algorithm using partial-mapped crossover, reciprocal exchange mutation, and roulette wheel selection. Testing shows the genetic algorithm improves total route distances by 3.74-8.15% compared to the nearest neighbor heuristic currently used by the company.
The document discusses machine learning concepts including supervised and unsupervised learning algorithms like clustering, dimensionality reduction, and classification. It also covers parallel computing strategies for machine learning like partitioning problems across systems.
States of Mind: can they be communicated and compared?Yoav Francis
This is a dialectical discussion in the question whether or not states of mind - be them perceptive, sensational or emotional, can be compared and communicated by an agent.
[This paper is in Hebrew]
The document provides biographies of several authors. It describes their educational backgrounds and areas of research expertise, which include artificial intelligence, databases, software engineering, computer science, cognitive science, and more.
The document discusses several challenges in machine learning, including:
1) Determining when generative vs. discriminative learning methods are better and how to make generative methods more computationally feasible.
2) Developing methods for learning from non-vectorial data like text, images, and graphs that can work across different data types and learning algorithms.
3) Extending discriminative methods like neural networks and support vector machines to more complex problems beyond classification and regression.
4) Developing distributed learning methods that can handle distributed data while preserving privacy.
This curriculum vita summarizes the educational and professional background of Khaled Rasheed. It lists his positions including Associate Professor at the University of Georgia, education including a Ph.D from Rutgers University, research interests in artificial intelligence techniques and applications, honors and awards, grants, publications, and professional activities. The vita provides a concise overview of Rasheed's qualifications and accomplishments.
The document provides an overview and analysis of machine learning, data mining, and decision support courses available online. It categorizes the courses based on intended audience (computer science students, managers, IT professionals) and provider (universities, commercial organizations). The document also discusses the characteristics of courses within and between categories, and provides examples of specific courses. It concludes with a review of efforts to increase awareness and education around data mining and decision support through the development of seminars, workshops and distance learning activities.
Eric Siegel is a data analytics consultant who has over 20 years of experience applying predictive analytics and data mining to solve business problems. He has held leadership roles defining analytics strategies and developing predictive models for applications such as sales forecasting and customer attrition. Siegel also has experience discovering and preparing data from disparate sources, and communicating technical analytics concepts to business audiences.
UcyQNFG8C16k.docx - Preparation of Ceria Fibers Via ...butest
This document discusses applying a genetic algorithm to solve a vehicle routing problem for a bakery company in Thailand. The problem involves routing delivery vehicles from a single depot to 32 customers while meeting customer demands and vehicle capacity constraints. The document proposes a genetic algorithm using partial-mapped crossover, reciprocal exchange mutation, and roulette wheel selection. Testing shows the genetic algorithm improves total route distances by 3.74-8.15% compared to the nearest neighbor heuristic currently used by the company.
The document discusses machine learning concepts including supervised and unsupervised learning algorithms like clustering, dimensionality reduction, and classification. It also covers parallel computing strategies for machine learning like partitioning problems across systems.
States of Mind: can they be communicated and compared?Yoav Francis
This is a dialectical discussion in the question whether or not states of mind - be them perceptive, sensational or emotional, can be compared and communicated by an agent.
[This paper is in Hebrew]
The document provides biographies of several authors. It describes their educational backgrounds and areas of research expertise, which include artificial intelligence, databases, software engineering, computer science, cognitive science, and more.
The document provides an overview of data mining and web mining techniques. It discusses how data mining uses statistical analysis, machine learning, and other techniques to extract patterns and correlations from large datasets. The document also presents results from a case study that analyzed web traffic statistics and visitor behavior on a website to gain insights on how to improve the user experience. Clustering algorithms were used to classify users and generate a web mining model. The case study demonstrated that data mining can efficiently analyze large amounts of web data and provide useful information for website optimization.
The document proposes a system to automatically select and customize educational resources from a digital library to support individual students and teachers. It will use planning methods to assemble resources into courses to achieve learning goals while considering constraints. Evaluation agents will monitor student progress and provide feedback to optimize course plans. Ontology agents will extract planning knowledge, like prerequisites and learning outcomes, from resources to construct representations for planning. The system aims to compare automatically generated plans to human-authored ones and improve over time with usage data.
What s an Event ? How Ontologies and Linguistic Semantics ...butest
This document discusses challenges for machine learning models of event extraction. It summarizes different approaches to modeling events, from simple relations to complex hierarchical decompositions. It notes challenges like associating ontologies with textual realizations, learning connectivity criteria for event relations, and developing formal frameworks that can handle the representational richness of events while remaining tractable. Clinical and biological event examples are also briefly discussed.
This document provides lesson plans for students in grades 4, 6, and 10 to learn about local history through exhibits at the Nelson County Museum of History in Oakland, Virginia. It includes three lessons focused on the 19th century tavern kitchen exhibit, the Rural Electrification exhibit, and the Hurricane Camille Room. Each lesson outlines the purpose, activities at the museum, standards addressed, and assessments. Resources like websites and books are also listed to supplement the lessons. The goal is for students to have hands-on, low-cost learning experiences about their local history through visits to the museum.
This certificate certifies that Shaun Hawkshaw successfully completed the course "X3 - Sage X3 - Application Consultant: Financials Requirements Test Out Option version 7" as of July 24, 2016. The certificate was issued by Robin DeLeone, Senior Product Manager of Learning Services.
This document provides a project report on building a descriptor-based support vector machine (SVM) for document categorization. It introduces SVMs and discusses how they were implemented for this project, including transforming data, scaling, using an RBF kernel, and training and assigning documents. The architecture of the SVM-based system is described, including training SVMs on descriptors and assigning descriptors to new documents. Experiments were conducted on a testbed using 5 descriptors, and recall, precision, and correct rate metrics were used to evaluate the results. In conclusion, the document demonstrates applying SVMs to automatically categorize documents based on their descriptors.
to download the file - School District of the Chathamsbutest
This document provides a summary of the various clubs and activities available to students at Chatham High School. It describes over 20 different clubs across many interests from academic to cultural to community service-oriented. It encourages students to get involved in extracurricular activities to have a well-rounded high school experience and provides contact information for each club's advisor.
Professor Dr. Agnar Aamodt is a professor of computer science and artificial intelligence at the Norwegian University of Science and Technology. He has over 25 years of experience in the fields of computer science and AI. He leads the Knowledge-Based Systems Group and is involved in both national and international research projects involving case-based reasoning, knowledge modeling, and decision support systems.
The document discusses the differences between machine learning (ML), statistical learning, data mining (DM), and automated learning (AL). It argues that while ML and statistical learning developed similar techniques starting in the 1960s, DM emerged in the 1990s from a merging of database research and automated learning. However, industry was much more enthusiastic about adopting DM techniques compared to AL techniques, even though many DM systems are just friendly interfaces of AL systems. The document aims to explain the key differences between DM and AL that led to DM's greater commercial success.
O documento apresenta um resumo sobre padrões de projeto. Discute classificação de padrões, exemplos de Factory Method, Decorator, Observer e Strategy. Também aborda princípios SOLID e anti-padrões.
University of Hyderabad Vacancies* *http://www.uohyd. ernet.in ...butest
The document lists job postings from various newspapers and websites in Gulf countries from February 19th to 26th, 2010. It provides links to electrical engineer, quantity surveyor, and other engineering and technical roles in Qatar, Saudi Arabia, Kuwait and UAE. The roles are from companies like Voltas Ltd. and require immediate availability.
The document provides an overview of data mining and web mining techniques. It discusses how data mining uses statistical analysis, machine learning, and other techniques to extract patterns and correlations from large datasets. The document also presents results from a case study that analyzed web traffic statistics and visitor behavior on a website to gain insights on how to improve the user experience. Clustering algorithms were used to classify users and generate a web mining model. The case study demonstrated that data mining can efficiently analyze large amounts of web data and provide useful information for website optimization.
The document proposes a system to automatically select and customize educational resources from a digital library to support individual students and teachers. It will use planning methods to assemble resources into courses to achieve learning goals while considering constraints. Evaluation agents will monitor student progress and provide feedback to optimize course plans. Ontology agents will extract planning knowledge, like prerequisites and learning outcomes, from resources to construct representations for planning. The system aims to compare automatically generated plans to human-authored ones and improve over time with usage data.
What s an Event ? How Ontologies and Linguistic Semantics ...butest
This document discusses challenges for machine learning models of event extraction. It summarizes different approaches to modeling events, from simple relations to complex hierarchical decompositions. It notes challenges like associating ontologies with textual realizations, learning connectivity criteria for event relations, and developing formal frameworks that can handle the representational richness of events while remaining tractable. Clinical and biological event examples are also briefly discussed.
This document provides lesson plans for students in grades 4, 6, and 10 to learn about local history through exhibits at the Nelson County Museum of History in Oakland, Virginia. It includes three lessons focused on the 19th century tavern kitchen exhibit, the Rural Electrification exhibit, and the Hurricane Camille Room. Each lesson outlines the purpose, activities at the museum, standards addressed, and assessments. Resources like websites and books are also listed to supplement the lessons. The goal is for students to have hands-on, low-cost learning experiences about their local history through visits to the museum.
This certificate certifies that Shaun Hawkshaw successfully completed the course "X3 - Sage X3 - Application Consultant: Financials Requirements Test Out Option version 7" as of July 24, 2016. The certificate was issued by Robin DeLeone, Senior Product Manager of Learning Services.
This document provides a project report on building a descriptor-based support vector machine (SVM) for document categorization. It introduces SVMs and discusses how they were implemented for this project, including transforming data, scaling, using an RBF kernel, and training and assigning documents. The architecture of the SVM-based system is described, including training SVMs on descriptors and assigning descriptors to new documents. Experiments were conducted on a testbed using 5 descriptors, and recall, precision, and correct rate metrics were used to evaluate the results. In conclusion, the document demonstrates applying SVMs to automatically categorize documents based on their descriptors.
to download the file - School District of the Chathamsbutest
This document provides a summary of the various clubs and activities available to students at Chatham High School. It describes over 20 different clubs across many interests from academic to cultural to community service-oriented. It encourages students to get involved in extracurricular activities to have a well-rounded high school experience and provides contact information for each club's advisor.
Professor Dr. Agnar Aamodt is a professor of computer science and artificial intelligence at the Norwegian University of Science and Technology. He has over 25 years of experience in the fields of computer science and AI. He leads the Knowledge-Based Systems Group and is involved in both national and international research projects involving case-based reasoning, knowledge modeling, and decision support systems.
The document discusses the differences between machine learning (ML), statistical learning, data mining (DM), and automated learning (AL). It argues that while ML and statistical learning developed similar techniques starting in the 1960s, DM emerged in the 1990s from a merging of database research and automated learning. However, industry was much more enthusiastic about adopting DM techniques compared to AL techniques, even though many DM systems are just friendly interfaces of AL systems. The document aims to explain the key differences between DM and AL that led to DM's greater commercial success.
O documento apresenta um resumo sobre padrões de projeto. Discute classificação de padrões, exemplos de Factory Method, Decorator, Observer e Strategy. Também aborda princípios SOLID e anti-padrões.
University of Hyderabad Vacancies* *http://www.uohyd. ernet.in ...butest
The document lists job postings from various newspapers and websites in Gulf countries from February 19th to 26th, 2010. It provides links to electrical engineer, quantity surveyor, and other engineering and technical roles in Qatar, Saudi Arabia, Kuwait and UAE. The roles are from companies like Voltas Ltd. and require immediate availability.