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About 10,000 papers for “Distributed learning”

Distributed learning

David I. Lewis, Donna M. Johnson · 2024

While the definition of distributed learning can be varied, probably the most recognised is the combination of asynchronous and synchronous activities, digital and in-person content delivery, as well as independent and collaborative learning experiences. While many biomedical science courses are rooted in the traditional face-to-face formatting, particularly given the vital lab-based element, the pandemic has afforded an opportunity to expand the use of distributed learning approaches. Students can work through teaching and learning activities at their own pace and as many times as needed in order to get to grips fully with a topic. Integration of virtual learning environment elements such as learning modules can also be used to guide students through a topic and a range of activities can be embedded to promote interactivity. Such approaches can again add value to face-to-face sessions, allowing synchronous sessions to be focused on areas of particular difficulty and applications of knowledge.

Cited by 0

Distributed Robust Learning

Yerrapragada, Akhil · KTH Publication Database DiVA (KTH Royal Institute of Technology) · 2021

Accuracy obtained when training deep learning models with large amounts of data is high, however, training a model with such huge amounts of data on a single node is not feasible due to various reasons. For example, it might not be possible to fit the entire data set in the memory of a single node, training times can significantly increase since the dataset is huge. To avoid these problems decentralized training is devised. In decentralized training, using the technique of Data parallelism, multiple nodes/workers make a local copy of the model and train it using a partition of the dataset. Each of these locally trained models are aggregated at some point to obtain the final trained model. Architectures such as Parameter server, All-reduce and Gossip use their own network topology to implement decentralized training. However, there is a vulnerability in this decentralized setting, any of the worker nodes may behave arbitrarily and fail. This type of failure is called byzantine failure. Here, arbitrary means any of the worker nodes may send incorrect parameters to others, which may lead to inaccuracy of the global model or failure of the entire system sometimes. To tolerate such arbitrary failures, aggregation rules were devised and are tested using Parameter server architecture. In this thesis we analyse the fault tolerance of Ring all-reduce architecture to byzantine gradients using various aggregation rules such as Krum, Brute and Bulyan. We will also inject adversaries during the model training to observe, which of the aforementioned aggregation rules provide better resilience to byzantine gradients.

Cited by 0Open access

Distributed dictionary learning

Amir Daneshmand, Gesualdo Scutari, Francisco Facchinei · 2016

The paper studies distributed Dictionary Learning (DL) problems where the learning task is distributed over a multi-agent network with time-varying (nonsymmetric) connectivity. This formulation is relevant, for instance, in Big Data scenarios where massive amounts of data are collected/stored in different spatial locations and it is unfeasible to aggregate and/or process all data in a fusion center, due to resource limitations, communication overhead or privacy considerations. We develop a general distributed algorithmic framework for the (nonconvex) DL problem and establish its asymptotic convergence. The new method hinges on Successive Convex Approximation (SCA) techniques coupled with i) a gradient tracking mechanism instrumental to locally estimate the missing global information; and ii) a consensus step, as a mechanism to distribute the computations among the agents. To the best of our knowledge, this is the first distributed algorithm with provable convergence for the DL problem and, more in general, bi-convex optimization problems over (time-varying) directed graphs.

Cited by 13

Distributed Learning Ecosystems

Daniel Otto, Gianna Scharnberg, Michael Kerres et al. · 2023

This open-access book is based on the observation that learning ecosystems are increasingly established in higher education institutions.

Cited by 5Open access

Advanced Distributed Learning

Stephen K. Curda, L. K. Curda · Quarterly review of distance education · 2003

In “Professional Education: The Key to Transformation,” Shelton (2001) pointed out the importance of education in the joint military environment and discussed how technology is transforming today's military education system. Specifically, he gave an example of the Joint Forces Staff College's (JFSC) initiative of developing an interactive CD-ROM, Joint Force Employment Course (JFEC), for training Joint Task Force commanders and their staff on joint doctrine. He also mentioned the initiative under way to develop the JFEC as an online course that will be available through distributive learning centers in 2003. An important key warning Shelton addressed with the emergence of technology-enhanced education was the “need of developing the doctrine to use them.”Too often in an education system, when a new methodology, technique, curriculum or tool arrives, everyone gets on the bandwagon thinking this new “thing” is the answer to one or more educational problems. Similarly, we are in danger of being enticed into distance education, specifically Advanced Distributed Learning (ADL) in the U.S. military, initiatives without correctly implementing “appropriate” practices. Currently, many of those joining the ADL “game” are practicing just as they would in resident courses without regard for the unique qualities of ADL and different practices that need to be employed. Though the use of ADL methodologies has been increasing in recent years, especially among a growing number of higher education organizations, corporations, and the military, these methods are still in their infancy and are progressing slowly toward becoming widely applied, well-understood, pedagogical tools. Consequently, recognized standards for ADL practices have not yet fully evolved nor have their capabilities and limitations as educational tools been clearly established. Therefore, if we move expeditiously, military educational institutions have an opportunity to play a constructive role in refining and shaping these new educational technologies for the benefit of its own programs, the Department of Defense (DoD) educational institutions and the educational system as a whole. In addition, assuming such a constructive role in the evolution of educationally sound ADL practices could become an important ingredient in achieving a distinctive and compelling character for the military in this century.This article takes a brief look at past military distance education practices and then focuses on discussion of the DoD's initiative in Advanced Distributed Learning. Finally, it will outline some of the potential problems we believe should be addressed in the near future and possible solutions towards the goal of implementing a successful ADL system for military educational organizations. Specifically, this paper will recommend a paradigm shift for military education institutions practicing ADL.Throughout the paper, we will be using the terms advanced distributed learning and distance education. Therefore, it is critical to define them from the perspective of the DoD so all readers will be familiar with and define the terms in a consistent manner. We want to be consistent with the way the DoD defines the two terms and therefore both definitions are adapted from the DoD Strategic Plan for ADL.Traditionally, distributed learning within a military setting focused on distance learning in the form of paper-based correspondence courses. Since the end of World War II, most military personnel were encouraged to further their military education, especially if they wanted to be upwardly mobile. Some were fortunate enough to attend the resident portion of the course while most were relegated to taking the course via correspondence. Correspondence courses often lack the same “quality” of residence courses and have a reputation for not being very interesting nor motivating. Although some individuals learned from correspondence courses, dropout rates are high when compared with students attending the resident military courses. The greater success rates for resident courses are due to several factors. First, the student-student and instructor-student interaction encountered within the residence courses made the learning experience more enjoyable, motivating, and authentic. Second, students in residence courses had the opportunity to focus their time and energy on learning the content and completing assignments (often in collaboration with fellow classmates) without family and military demands.Traditional correspondence courses were paper-based only and have since slowly transitioned to CD-ROM. With this change in delivery medium the terminology changed from “correspondence courses” to “distance education.” However, the terminology change brought few, if any, pedagogical changes. Initially, the CD-ROM course simply provided the same text material via a different medium. Gradually, some changes were evident in sporadic examples, PowerPoint slides, and additional graphics to enhance learning. The change of media did little to address problems of dropout rate and motivation given they did little to address the factors noted above that contribute to the success of resident courses. Regardless of the challenges of providing high-quality and motivating distance education for military personnel, the demand for this type of training and education continued to increase as the number of personnel desiring training and education increased and the costs of travel and time off the job increased for resident courses.One of the common concerns expressed by commanders is the challenge of having to send their service members away from their units to satisfy education and training requirements. The accelerating pace of technological change in weapons systems advancement further complicates this challenge. These concerns, and the ever-growing complexity of modern weapon systems, demand that the military re-engineer their education and training systems to take advantage of information-age technologies (DoD Strategic Plan for ADL, 1999). Such technologies must allow for just-in-time education and training so that personnel can “attend” and remain with their unit. They must also overcome the well-documented disadvantages of correspondence courses. The advances of technology and communications quickly suggested alternatives to the paper-based and CD-ROM correspondence courses. Such alternatives included implementation of a wide variety of delivery media that had the potential for providing more interactive and engaging distance instruction than was previously possible for distance education. This new consideration for leveraging all forms of communication and technology to provide high quality education and training in resident and distance courses was the beginning of Advanced Distributed Learning (ADL) initiatives.In recent years, distance education courses, most often in the form of video-teleconferencing and online courses, have exploded throughout business sectors, educational sectors and in the military. Improved access to the Internet has allowed for new tools and methods for practicing distance education. There are approximately 7,000 Internet Service Providers (ISP) in the U.S. and over 10,000 ISPs across 120 countries. As of September 2002, there were more than 182 million people estimated to be online in North America. There are over 605 million Internet users worldwide, and that number continues to grow (Scope Communications Group). Other advancements, including increased bandwidth, satellite and wireless technologies, and portable and handheld computers, among others, have continued the push to bring distance education into mainstream education.The client demand for implementing these new tools and methods is also prevalent. In educational institutions, the demographics of students are changing rapidly. More than 40 percent are “nontraditional” students with the need for flexible scheduling and coursework that will move them ahead in the workplace and fit their busy family life. Business, industry, and military personnel are in constant need of retraining. The majority of workers are likely using some form of information technology in their jobs. Oblinger and Rush (1997) estimated that every employee will need training equivalent to 30 credit hours every 7 years.Traditionally, business, industry, and military organizations sent their personnel to training during the regular work week and sacrificed time lost on the job for well-trained personnel. Costs for personnel training such as this have doubled in the past 15 years as travel expenses increase and employee time has become even more valuable. Distance education technologies have allowed business and industry to cut training costs by saving travel and lodging costs for location specific training. In addition, time lost on the job is reduced because employees now do not have a travel day on each side of the training schedule. Additional possible benefits of online education include personnel choosing to further their education while they maintain full-time jobs and remain at home. The National Center for Education Statistics (2002) reported that 7.6 percent of all undergraduates and 10 percent of all graduate students enrolled in distance education courses in 1999-2000. The International Data Corporation predicted that 2.2 million college students will enroll in online courses this year.More specific to the military, the Secretary of Defense's Training Technology Vision was established to ensure access to high quality education and training materials that can be tailored to individual learner needs and can be made available whenever and wherever it is required (Sherman, 2000). To achieve this vision, anytime-anywhere learning must be distributed, just-in-time and on-demand, and enabled with resourced development and exploitation of learning technologies. The strategic shift from learning solely in the central classroom to learning in the unit where and when required—while maintaining quality—can ensure higher readiness and improve the mission availability of personnel. The indicators of success for the Advanced Distributed Learning investment will be measurable, in terms of improved unit cohesion, increased availability for operations, and heightened operational readiness stemming from unit management of learning assets throughout the DoD.Because of the importance of distributed learning in this vision, the Department of Defense and the White House Office of Science and Technology Policy (OSTP) launched the Advanced Distributed Learning (ADL) initiative in 1997. The ADL Initiative is a collaborative effort to expedite production of learning materials and tools that are reusable, can run on a broad range of hardware platforms, and can be accessed and modified over a communications network. The ADL vision is to utilize the power of the Internet and other virtual or private wide-area networks to deliver high-quality instruction. ADL brings together intelligent tutors, distributed subject matter experts, real-time in-depth learning management, and a diverse array of support tools to ensure a responsive, high-quality “learner-centric” system. This ADL initiative does not exclude any existing delivery method. In some cases, this initiative may expand and complement legacy delivery systems (DoD Strategic Plan for ADL, 1999).The DoD Strategic Plan for ADL suggests this ADL initiative requires re-engineering the learning paradigm from a “classroom-centric” model to an increasingly “learner-centric” model, and re-engineering the learning business process from a “factory model” to a more network-centric “information-age model” that incorporates anytime-anywhere learning. The purpose is not to replace the entire classroom model of training and education within the Department of There will be a for such instruction. The is to provide for the of as instruction as possible while maintaining the standards for and quality of instruction (DoD Strategic Plan for ADL, DoD ADL initiative a of the readiness of the Joint Vision environment ADL by high operational and personnel for the complexity of future systems and operations, and the availability and the of education and training systems for the entire The ADL is also for learning for personnel, as as for through high for military being in DoD (DoD Strategic Plan for ADL, to the DoD Plan it is that the availability of and in military distance education courses will increase over the In the same in the DoD that distance education may classroom time by as as 30 increase by as as travel and costs by and development costs by to Distance education has the potential for given that military provide education and training to over students a through the military education and training centers of Defense 2000). military educational institutions such as the War and the importance of distance education and now have of distance education or to students do not have the opportunity to attend the resident The DoD to provide high-quality education and the to DoD personnel and at are that ADL initiatives will the way for high-quality military education and service have ADL initiatives and are in of implementing ADL are a from the Department of Defense Plan and other DoD ADL initiative the military education and training system as a to include management, and of the entire system across the of service and including resident as as distance courses. is focused on providing standards and for everyone to towards the goal of so common content can be by Although the of the ADL initiative is from the above it can be that most of service are on the distance education of This focus is given the it for military education and training in the future and the in higher education, business, and However, such distance education must be to not the same as distance education in the of learning and must be now more than if distance education are to be distance education practices can be from learned in higher education and business while are still is with and industry to provide the most technologies for military personnel to be and of distance education. With the emergence of new the DoD ADL initiative from learning solely in the central classroom or from others, to learning in a interactive do we use the ADL initiatives by the training vision to provide access to the quality education and training that can be tailored to individual whenever and wherever it is without to the same as correspondence courses of the the recent technology many military organizations have the focus of their distance education toward of instruction and technology instruction. Such has the potential to learning and learning that in more and of education and training because of their to provide and communication among students and with The is not likely to be without a paradigm shift in military to and courses. Such a paradigm shift for course and and the most and to achieve learning and on the job and are likely to include a of different media and different of interaction as by the of the learning This paradigm shift will take a effort to move from the with correspondence and classroom courses to an Advanced Distributed Learning focused in needs and media and learner motivation play key in the and delivery some focus has toward and delivery of online education and many military distance education courses are for via given to many students as a just as paper-based correspondence courses were in the paper-based content is and to a CD-ROM delivery by a with from a subject matter However, are when and developing the instruction. In most higher education institutions and have that a to development has more potential for quality distance education courses. of at one one one one and one or more subject matter by a higher education institutions have that and are critical of motivation and as correspondence course students motivation and in it is likely the students using these correspondence courses to will some of the same problems if more distance education practices are not (2001) suggests key of a education system that any should when the and development of such a system. These are critical of the delivery medium and are for the for the development of a successful ADL system. of these is and for use within the of implementation of an ADL system requires consideration of all the above ADL has been by the DoD with technology and and standards that ensure the goal of the ADL initiatives is service are also taking on their own initiatives to or and develop their own learning management system. and distance courses are to more communication technologies to enhance the learning As as these initiatives are to the of ADL and distance education, it will not be enough for success to be a focus on the technological and management and the pedagogical or support Such in the system will to The of ADL are to the way institutions distance education. military institutions, such a system will a shift in The way of practicing distance education in the military to higher dropout rates and towards courses 2000). The new paradigm must address pedagogical such as and the role of the in distance education. must address to and of courses to ensure and learning. it must the support students and need to be education must learning that time and by providing educational to the needs of all students through the development and delivery of by media to students as and courses across requires more than just existing materials to an that can be a CD-ROM and sent to the education should not be simply way of providing for military education Distance education additional in to and future educational technologies and methodologies will and support staff to develop for distance instruction that of and of learning. 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Cited by 0Open access

Distributed learning automata.

Mansour Esmaeilpour (632453), Vahideh Naderifar (632454), Zarina Shukur (632455) · Figshare · 2015

Cited by 0Open access

Spatially Distributed Learning

Liván García Lache, Lino Alberto Rodríguez Coayahuitl, Antonio González · Lecture notes in computer science · 2025

Cited by 0

Distributed Dictionary Learning

Amir Daneshmand, Scutari Gesualdo, Francisco Facchinei · arXiv (Cornell University) · 2016

The paper studies distributed Dictionary Learning (DL) problems where the learning task is distributed over a multi-agent network with time-varying (nonsymmetric) connectivity. This formulation is relevant, for instance, in big-data scenarios where massive amounts of data are collected/stored in different spatial locations and it is unfeasible to aggregate and/or process all the data in a fusion center, due to resource limitations, communication overhead or privacy considerations. We develop a general distributed algorithmic framework for the (nonconvex) DL problem and establish its asymptotic convergence. The new method hinges on Successive Convex Approximation (SCA) techniques coupled with i) a gradient tracking mechanism instrumental to locally estimate the missing global information; and ii) a consensus step, as a mechanism to distribute the computations among the agents. To the best of our knowledge, this is the first distributed algorithm with provable convergence for the DL problem and, more in general, bi-convex optimization problems over (time-varying) directed graphs.

Cited by 0Open access

Distributed Reinforcement Learning

Michael Y. Hu · Apress eBooks · 2023

This chapter explores the use of distributed reinforcement learning, which involves multiple agents running in parallel to interact with the environment to generate sample trajectories or transitions, and use samples to train the agent (e.g., to learn the optimal policy or value function). This approach offers several benefits over single-agent architectures, including faster convergence, better exploration, improved robustness, and increased scalability.

Cited by 0

Distributed Learning (archived)

Calhoun: The Naval Postgraduate School Institutional Archive (Naval Postgraduate School) · 2014

Screen shot of Naval Postgraduate School webpage.

Cited by 0

Learning Distributed Representations

Ramon Krosley, Manavendra Misra · 2007

This paper describes a neural computing architecture which develops distributed symbolic representations of its environment. Experiments applied the neural system to the sensory and motor environment of a simulated robot navigating across a cluttered floor. The system autonomously defines and adjusts the meanings of its symbols. Another feature of the system is its ability to remember an event in a single presentation. 1 Introduction Is it possible to perform symbolic computations in a neural network? Such a capability would enable implementation of symbolic artificial intelligence structures in the massively parallel computing architecture of neural networks. The first step toward neural symbolic computation is to implement symbols in a neural network. Later steps include the development of computing mechanisms which use these symbols in such applcations as planning behavior. This paper focuses on the first step, describing a neural computing architecture which generates symbols and...

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