3,068 Matching Annotations
  1. Mar 2019
    1. The benefits of personalized learning through technology This resource is included in part because it connects personalized learning and technology. A brief list of benefits, such as increasing student engagement and bridging the gap between teachers and students, are listed. This is presented by a marketing unit of a university so there may be an agenda. Nonetheless it provides useful considerations such as helping learners develop 'design thinking.' rating 3/5

    1. learning in the 21st century mobile devices + social media = personalized learning This appears to be oriented toward K-12 students but several components seem applicable to professional learning. The context is schools. Key findings are listed at the beginning of the report. The report is somewhat dated but still makes some points worth considering, such as the potential for devices to serve as a distraction just as much as a tool. rating 2/5

    1. What's possible with personalized learning: an overview of personalized learning for schools, families, and communities. This 32 page PDF is included in part due to its credibility and also to its breadth. The focus is personalized learning in schools. All ages are considered and there is a discussion of 'what personalized learning means for teachers.' It is sufficiently readable and rather attractively presented for a report. rating 5/5

    1. A national landscape scan of personalized learning in K-12 education in the United States This is included because it is associated with the Bill and Melinda Gates foundation, among other indicators of credibility, and because it provides (as the title suggests) a portrait of the state of personalized learning in schools, addressing topics that are not addressed by other resources in this list. rating 5/5

    1. personalize learning infographic

      This is not quite what it sounds like. It is a Pinterest style page with links to assorted articles that relate to personalized learning, most of which are presented in an infographic. It is sufficiently useful if one has the patience to click through to the infographics. Usability is satisfactory although the top half of the page is taken up with graphics that are not directly related to the content. rating 3/5

    1. Evaluation of technology enhanced learning programs for health care professionals: systematic review This article is included because it is a systematic review. It is presented in academic language. The intention is to evaluate the quality of the articles themselves, not to guide e-learning development. Criteria for evaluating articles was established in advance. The utility of the article for my purposes may be a new search term, continuous professional development. rating 2/5

    1. macro to micro learning: how to transform your course library This short article has limited utility because of its lack of breadth and reading is a bit difficult because of the small gray typeface. Nonetheless it is a current article that provides a few tips for those who seek to have a greater number of micro learning opportunities among their professional development offerings. rating 2/5

    1. what is the definition of mobile learning This is a brief article that explains mobile learning for a layperson (not an academic). It is described in the context of schooling. It does not necessarily relate to informal learning specifically. The advantages (such as motivation and distance) are discussed, as well as the disadvantages (such as the potential for distraction). It is adequate as a definition. rating 3/5

    1. bridging formal and informal learning through technology in the twenty first century: issues and challenges This article is in a fully online journal. It relates to schools but the learning is by students, not teachers. However, professional development is called for. The article addresses the desired topic in that it refers to social networking and other technology enabled forms of learning; however, it does not seem to be substantive enough to be tremendously helpful. rating 1/1

    1. Factors influencing engagement in informal learning activities This article describes features that encourage informal learning among teachers. Those are: initiative, self-efficacy, love of learning, interest in the profession, commitment to professional development, a nurturing personality, and an interesting personality. One noteworthy feature is that the factors they refer to are personal in nature. This article does appear to fill a unique niche among the collection that I have found so far. rating 5/5

    1. informal learning with mobile devices - microblogging as learning resource This article uses the work of Schon, a theorist on learning and reflection whose work is often used to address workplace learning. The paper is on topic, relating to informal learning with mobile devices, but it focuses on high school students--which seems to be a rather unusual use of Schon's writing. Also the writing itself is both general and dated. There is a 2x2 that describes the relationship of formal and informal learning to intentional and unintentional learning as well as the use of devices. rating 1/5

    1. Simulations and games in informal learning contexts This article seems to discuss science learning, which is not my foremost interest, but it does give an example of how informal online learning can be used to allow the learner to explore his or her own interests. It is not specific enough to be of high value but is useful as a preliminary reading that can perhaps inform search terms to use for future research. rting 2/5

    1. Using mobile devices to support formal, informal, and semi-formal learning: uses and implications for teaching and learning This online article is presented with 'draft' stamped across it; it does not appear to be from a recognized publisher. The content does connect the topics I am looking for (informal or personalized learning, mobile devices, and teacher professional development). They discuss their recommendations and connect informal mobile learning to personalized learning. rating 4/5

    1. designing for sustainable mobile learning: evaluating the concepts formal and informal This is a journal article that is freely available online. They argue that informal learning is more 'enriching' than formal learning. They write about mLearning (mobile learning) and state that some 'design aspects' must be left to learners. This is formatted in the standard way and has the usability one would expect of an online journal article. There are citations as one would expect but I am not qualified to evaluate the information quality. rating 5/5

    1. personalized mobile learning solutions to create effective learning paths This appears to blend personalized learning and mobile learning. It is prepared by a specific vendor, MagicBox, so they might be assumed to have their own agenda. This page describes some of the affordances of personalized mobile learning, such as the capacity to track and presumably respond to learner preferences. rating 2/5

    1. This page is meant to demonstrate what personalized learning 'looks like' and that seems to mean the principles or characteristics that it has. This page relates to kids, not adults, but the principles mostly seem relevant to adults just as much as kids. I do not know enough about this topic to evaluate the information quality, but the aspects I can evaluate, such as the writing and presentation, seem to suggest at least moderate credibility. rating 2/5

    1. This is a research based report (of which I have found few) that connects professional development and personalized learning. I had hoped to find links that applied to health care and have not found a great many so far, but this article, which is more oriented toward professional development for teachers, still has applications since public health education professionals participate in many of the same practices. rating; 5/5

    1. train and develop your staff with mobile apps I am not sure why the first two components of this page are included, but there is a bulleted list of contexts or applications of mobile apps for e-learning, such as leadership training, onboarding, and integrating interns who are part of the organization. This is interesting but I do not yet know how essential it is.

    1. This is Bloom's taxonomy of cognitive objectives. I selected this page because it explains both the old and new versions of the taxonomy. When writing instructional objectives for adult learning and training, one should identify the level of learning in Blooms that is needed. This is not the most attractive presentation but it is one of the more thorough ones. rating 4/5

    1. Campus Technology magazine This is the website for a magazine that is also published on paper. Articles are freely accessible (a subscription is not required). The design of the page is messy and as with any magazine, the content varies, but the site does give a description of the use of technology in higher education. The same technologies can sometimes be applied in adult learning in general. Rating 4/5

    1. This link is to a three-page PDF that describes Gagne's nine events of instruction, largely in in the form of a graphic. Text is minimized and descriptive text is color coded so it is easy to find underneath the graphic at the top. The layout is simple and easy to follow. A general description of Gagne's work is not part of this page. While this particular presentation does not have personal appeal to me, it is included here due to the quality of the page and because the presentation is more user friendly than most. Rating 4/5

    1. This page is a simply presented list of many learning theories, both popular and less well known. The layout is clean. The pages to which the listed items link are somewhat minimal in nature so this would give a basic tour or overview of the models and would allow viewers to review the names of some of the learning theories. This page does not prioritize learning theories or identify and establish those theories that are the most prominent.

    1. Edutech wiki This page has a somewhat messy design and does not look very modern but it does offer overviews of many topics related to technologies. Just like wikipedia, it offers a good jumping off point on many topics. Navigation can occur by clicking through categories and drilling down to topics, which is easier for those who already know the topic they are looking for and how it is likely to be characterized. Rating 3/5

    1. This is one of many discussions of Kirkpatrick's four levels of evaluation. More of the page is taken up with decoration and graphics than needs to be the case but this page is included in this list because it offers a printable guide and because the hierarchy of the four levels is clearly shown. The text itself is printed in black on a white background and it is presented as a bulleted list (the bullets are not organized as well as they could be). Nonetheless it is a usable presentation of this model. rating 3/5

  2. www.pblworks.org www.pblworks.org
    1. Phase 3: Student-Centered Learning During Phase 3, students work both individually and in small groups at using strategies and skills from the previous phases to develop lines of inquiry around curricular topics. This type of project requires clear questions, multiple reliable sources, citations, and a final product that communicates that information to others.

      Students should be taught the material but should also be set free in order to collaborate with peers as well as technology to “tinker” and figure out the answer to the problem on their own which promotes a student centered approach to learning

    1. EFFICIENT METHODS AND HARDWARE FOR DEEP LEARNING

      Deep Compression" can reduce the model sizeby 18?to 49?without hurting the prediction accuracy. We also discovered that pruning and thesparsity constraint not only applies to model compression but also applies to regularization, andwe proposed dense-sparse-dense training (DSD), which can improve the prediction accuracy for awide range of deep learning models. To efficiently implement "Deep Compression" in hardware,we developed EIE, the "Efficient Inference Engine", a domain-specific hardware accelerator thatperforms inference directly on the compressed model which significantly saves memory bandwidth.Taking advantage of the compressed model, and being able to deal with the irregular computationpattern efficiently, EIE improves the speed by 13?and energy efficiency by 3,400?over GPU

  3. arxiv.org arxiv.org
    1. One of the challenges of deep learning is that the gradients with respect to the weights in one layerare highly dependent on the outputs of the neurons in the previous layer especially if these outputschange in a highly correlated way. Batch normalization [Ioffe and Szegedy, 2015] was proposedto reduce such undesirable “covariate shift”. The method normalizes the summed inputs to eachhidden unit over the training cases. Specifically, for theithsummed input in thelthlayer, the batchnormalization method rescales the summed inputs according to their variances under the distributionof the data

      batch normalization的出现是为了解决神经元的输入和当前计算值交互的高度依赖的问题。因为要计算期望值,所以需要拿到所有样本然后进行计算,显然不太现实。因此将取样范围和训练时的mini-batch保持一致。但是这就把局限转移到mini-batch的大小上了,很难应用到RNN。因此需要LayerNormalization.

    1. A potential draw-back with such pre-training approach is that themodel may suffer from the mismatch of dialoguestate distributions between supervised training andinteractive learning stages. While interacting withusers, the agent’s response at each turn has a di-rect influence on the distribution of dialogue statethat the agent will operate on in the upcoming di-alogue turns.

      策略学习也是对话过程很重要的一环。 最近的策略学习过程有用基于有监督的预训练然后线上强化学习再训练的来提高学习的方案。但是这种方案有个潜在的毛病,在离线的数据中受限于数据量,线上一旦碰到了不常见的情况,容易直接恢复不来。(这个问题应该只是推断吧?有什么实证么?)

      所以本文其实想说的是用一种方法来减轻线上和离线的差距。

    1. We have developed quite a few concepts and methods for using the computer system to help us plan and supervise sophisticated courses of action, to monitor and evaluate what we do, and to use this information as direct feedback for modifying our planning techniques in the future.

      This reminds me of "personalized learning."

  4. Feb 2019
    1. Does overall time spent reading correlate with assessment scores? Are particular viewing patterns/habits predictive of student success? What are the average viewing patterns of students? Do they differ between courses, course sections, instructors, or student demographics?

      Can H itself capture some of this data? Through the LMS?

    1. ecent advances of deep learning have inspiredmany applications of neural models to dialoguesystems. Wen et al. (2017) and Bordes et al.(2017) introduced a network-based end-to-endtrainable task-oriented dialogue system, whichtreated dialogue system learning as the problemof learning a mapping from dialogue histories tosystem responses, and applied an encoder-decodermodel to train the whole system

      Wen和Bordes介绍了一种基于网络的端到端的任务型对话系统,这个系统将对话系统学习看成是从历史回话到系统回复的映射关系的学习问题,并且应用了一个编码解码器来训练整个系统。

      这个思路很有意思,和我之前想构建一个电销员的语料库来做用户回复响应很像。这个很有可能。

    1. Algorithms will privilege some forms of ‘knowing’ over others, and the person writing that algorithm is going to get to decide what it means to know… not precisely, like in the former example, but through their values. If they value knowledge that is popular, then knowledge slowly drifts towards knowledge that is popular.

      I'm so glad I read Dave's post after having just read Rob Horning's great post, "The Sea Was Not a Mask", also addressing algorithms and YouTube.

    1. Transfusion: Understanding Transfer Learning with Applications to Medical Imaging

      基于模型参数的迁移学习对 proformace 影响不大,当然训练更快啦。有趣的是,迁移 trained 模型参数的均值/方差统计性也可以得到不错的迁移效果。

    1. The cost of not having a comprehensive base of content knowledge can be prohibitive; for example, students can receive incorrect information and develop misconceptions about the content area (National Research Council, 2000; Pfundt, & Duit, 2000)

      The importance of understanding the full extent of the content we are teaching is to give our students correct information. Learning incorrect information and having "misconceptions about the content area" is detrimental to our students' learning.

    1. Connected learning is realized when a young person is able to pursue a personal interest or passion with the support of friends and caring adults, and is in turn able to link this learning and interest to academic achievement, career success or civic engagement

      Helping students to have a relatable interest with their learning can help them to succeed in their futures. Making our lessons more understandable and related to their interests is important when setting up their learning environment.

    1. Connected learning does not rely on a single technology or technique. Rather, it is fostered over time through a combination of supports for developing interests, relationships, skills, and a sense of purpose.

      When we start off the year using different teaching methods and establishing healthy relationships with our students, we can help them to grow immensely in the small amount of time that we know them.

    2. Opportunities

      Providing our students with opportunities to learn outside the classroom or using technology as a tool when we are teaching are good ways to get them involved in their learning and can eventually help them to take control of their learning experience all together, with us being the facilitators of knowledge.

    1. We present MILABOT: a deep reinforcement learning chatbot developed by theMontreal Institute for Learning Algorithms (MILA) for the Amazon Alexa Prizecompetition. MILABOT is capable of conversing with humans on popular smalltalk topics through both speech and text. The system consists of an ensemble ofnatural language generation and retrieval models, including template-based models,bag-of-words models, sequence-to-sequence neural network and latent variableneural network models. By applying reinforcement learning to crowdsourced dataand real-world user interactions, the system has been trained to select an appropriateresponse from the models in its ensemble. The system has been evaluated throughA/B testing with real-world users, where it performed significantly better thanmany competing systems. Due to its machine learning architecture, the system islikely to improve with additional data
    1. In such a future working relationship between human problem-solver and computer 'clerk,' the capability of the computer for executing mathematical processes would be used whenever it was needed. However, the computer has many other capabilities for manipulating and displaying information that can be of significant benefit to the human in nonmathematical processes of planning, organizing, studying, etc.
    2. For instance, an aborigine who possesses all of our basic sensory-mental-motor capabilities, but does not possess our background of indirect knowledge and procedure, cannot organize the proper direct actions necessary to drive a car through traffic, request a book from the library, call a committee meeting to discuss a tentative plan, call someone on the telephone, or compose a letter on the typewriter.

      In other words: culture. I'm pretty sure that Engelbart would agree with the statement that someone who could order a book from a library would likely not know the best way to find a nearby water source, as the right kind of aborigine would know. Collective intelligence is a monotonically increasing store of knowledge that is maintained through social learning -- not just social learning, but teaching. Many species engage in social learning, but humans are the only primates with visible sclera -- the whites of our eyeballs -- which enables even infants to track where their teacher/parent is looking. I think this function of culture is what Engelbart would call "C work"

      A Activity: 'Business as Usual'. The organization's day to day core business activity, such as customer engagement and support, product development, R&D, marketing, sales, accounting, legal, manufacturing (if any), etc. Examples: Aerospace - all the activities involved in producing a plane; Congress - passing legislation; Medicine - researching a cure for disease; Education - teaching and mentoring students; Professional Societies - advancing a field or discipline; Initiatives or Nonprofits - advancing a cause.
      
      B Activity: Improving how we do that. Improving how A work is done, asking 'How can we do this better?' Examples: adopting a new tool(s) or technique(s) for how we go about working together, pursuing leads, conducting research, designing, planning, understanding the customer, coordinating efforts, tracking issues, managing budgets, delivering internal services. Could be an individual introducing a new technique gleaned from reading, conferences, or networking with peers, or an internal initiative tasked with improving core capability within or across various A Activities.
      
      C Activity: Improving how we improve. Improving how B work is done, asking 'How can we improve the way we improve?' Examples: improving effectiveness of B Activity teams in how they foster relations with their A Activity customers, collaborate to identify needs and opportunities, research, innovate, and implement available solutions, incorporate input, feedback, and lessons learned, run pilot projects, etc. Could be a B Activity individual learning about new techniques for innovation teams (reading, conferences, networking), or an initiative, innovation team or improvement community engaging with B Activity and other key stakeholders to implement new/improved capability for one or more B activities.
      

      In other words, human culture, using language, artifacts, methodology, and training, bootstrapped collective intelligence; what Engelbart proposed, then was to apply C work to culture's bootstrapping capabilities.

    3. Our culture has evolved means for us to organize the little things we can do with our basic capabilities so that we can derive comprehension from truly complex situations, and accomplish the processes of deriving and implementing problem solutions. The ways in which human capabilities are thus extended are here called augmentation means, and we define four basic classes of them: 2a4 Artifacts—physical objects designed to provide for human comfort, for the manipulation of things or materials, and for the manipulation of symbols.2a4a Language—the way in which the individual parcels out the picture of his world into the concepts that his mind uses to model that world, and the symbols that he attaches to those concepts and uses in consciously manipulating the concepts ("thinking"). 2a4b Methodology—the methods, procedures, strategies, etc., with which an individual organizes his goal-centered (problem-solving) activity. 2a4c Training—the conditioning needed by the human being to bring his skills in using Means 1, 2, and 3 to the point where they are operationally effective. 2a4d The system we want to improve can thus be visualized as a trained human being together with his artifacts, language, and methodology. The explicit new system we contemplate will involve as artifacts computers, and computer-controlled information-storage, information-handling, and information-display devices. The aspects of the conceptual framework that are discussed here are primarily those relating to the human being's ability to make significant use of such equipment in an integrated system.

      To me, this is the most prescient of Engelbart's future visions, and the seed for future study of culture-technology co-evolution. I talked with Engelbart about this passage over the years and we agreed that although the power of the artifacts, from RAM to CPU speed to network bandwidth, had improved by the billionfold since 1962, the "softer" parts of the formula -- the language, methodology, and training -- have not advanced so much. Certainly language, training methods and pedagogy, and collaborative strategies have evolved with the growth and spread of digital media, but are still lagging. H/LAMT interests me even more today than it did thirty years ago because Engelbart unknowingly forecast the fundamental elements of what has come to be called cultural-biological co-evolution. I gave a TED talk in 2005, calling for an interdisciplinary study of human cooperation -- and obstacles to cooperation. It seems that in recent years an interdisciplinary understanding has begun to emerge. Joseph Henrich at Harvard, for one, in his recent book, The Secret of Our Success, noted:

      Drawing insights from lost European Explorers, clever chimpanzees, hunter-gatherers, cultural neuroscience, ancient bones and the human genome, Henrich shows that it’s not our general intelligence, innate brain power, or specialized mental abilities that explain our success. Instead, it’s our collective brains, which arise from a combination of our ability to learn selectively from each and our sociality. Our collective brains, which often operate outside of any individual’s conscious awareness, gradually produce increasingly complex, nuanced and subtle technological, linguistic and social products over generations.

      Tracking this back into the mist of our evolutionary past, and to the remote corners of the globe, Henrich shows how this non-genetic system of cultural inheritance has long driven human genetic evolution. By producing fire, cooking, water containers, tracking know-how, plant knowledge, words, hunting strategies and projectiles, culture-driven genetic evolution expanded our brains, shaped our anatomy and physiology, and influenced our psychology, making us into the world’s only living cultural species. Only by understanding cultural evolution, can we understand human genetic evolution.

      Henrich, Boyd, and RIcherson wrote, about the social fundamentals that distinguish human culture's methods of evolving collective intelligence in The Origin and Evolution of Culture:

      Surely, without punishment, language, technology, individual intelligence and inventiveness, ready establishment of reciprocal arrangements, prestige systems and solutions to games of coordination, our societies would take on a distinctly different cast. Thus, a major constraint on explanations of human sociality is its systemic structure

    4. executive capability

      Executive capabilities/processes compared. Latter are tied to metacognition in some learning theories. Here tacit knowledge is included in capabilities and excluded from processes (i.e. as inferior or biasing?)- if I'm reading correctly.

    1. The kind of participatory connected learning experiences that we are advocating for arenot easily described

      What are some ways we who seem to "grok" participatory connected learning (or think we do) can make this concept more accessible to colleagues who lament the failure of "sit-and-get" faculty development/PD, but don't know what to do next? I was reminded of this a few days ago in a "mixed" meeting of faculty, staff, and administrators. We all meant well, but could have done better in planning some upcoming sessions that (we hope) will become a Community of Practice. I think a way to describe participatory culture in a room full of people who don't already know Henry Jenkins and Mimi Ito would help.

    1. Yet, as early adopters, history’s first generation of “always connected” individuals do not have the knowledge and skills to critically explore, build, and connect online

      Knowing how to navigate the internet is very different than understanding the internet and internet uses. Understanding how to use the internet is essential to communication, sharing, and learning on the internet.

    1. Nearly half of FBI rap sheets failed to include information on the outcome of a case after an arrest—for example, whether a charge was dismissed or otherwise disposed of without a conviction, or if a record was expunged

      This explains my personal experience here: https://hyp.is/EIfMfivUEem7SFcAiWxUpA/epic.org/privacy/global_entry/default.html (Why someone who had Global Entry was flagged for a police incident before he applied for Global Entry).

    2. Applicants also agree to have their fingerprints entered into DHS’ Automatic Biometric Identification System (IDENT) “for recurrent immigration, law enforcement, and intelligence checks, including checks against latent prints associated with unsolved crimes.

      Intelligence checks is very concerning here as it suggests pretty much what has already been leaked, that the US is running complex autonomous screening of all of this data all the time. This also opens up the possibility for discriminatory algorithms since most of these are probably rooted in machine learning techniques and the criminal justice system in the US today tends to be fairly biased towards certain groups of people to begin with.

    3. It cited research, including some authored by the FBI, indicating that “some of the biometrics at the core of NGI, like facial recognition, may misidentify African Americans, young people, and women at higher rates than whites, older people, and men, respectively.

      This re-affirms the previous annotation that the set of training data for the intelligence checks the US runs on global entry data is biased towards certain groups of people.

  5. Jan 2019
    1. Active-learning techniques — like sharing the responsibility for leading discussions or framing classroom expectations with our students — show them they indeed belong in this "scholarly space" and give them the confidence to engage with the course and one another.

      The ProfHacker article by Maha Bali and Steve Greenlaw explores this more concretely. Active learning for inclusion needs to be scaffolded in such a way that it does not reinforce the privilege of dominant cultures and personalities.

    1. More and more, employers are offering professional development courses online, he noted. “Learning online is different from face-to-face, and [graduates] won’t have any experience. If the college wants students to be lifelong learners, give them the opportunity to” take virtual courses."

      This paragraph mentions that employers are offering more training online, so having online course experience will benefit students once they enter the job market, What are some other potential benefits of students learning online?

    1. The Grid is based around ideas familiar to Bitwig Studio

      The continuity between these new modular features and the rest of the DAW’s workflow probably has unexpected consequences. Before getting information about BWS3, one might have thought that the “Native Modular System” promised since the first version might still be an add-on. What the marketing copy around this “killer feature” makes clear, it’s the result of a very deliberate process from the start and it’ll make for a qualitatively different workflow.

    1. Encourage students to apply their expertise to serve their community. Partner with nonprofit organizations to create opportunities for students to apply their research or marketing skills.

      Service-learning approaches - real-life application of skills gained in class to make society better.

    1. Please check out Software Carpentry as well. This is a great intro that covers not just programming and data analysis (R/Python), but a lot of crucial stuff that every bioinformatician should know but usually is not covered in courses, such as Unix shell Git and version control Unit testing SQL and databases Data management and provenance I also like A Quick Guide to Organizing A Computational Biology Project for organizational techniques that usually have to be learned by experience
    1. In my opinion if you can get enrolled into a degree program for systems biology then that would be best. However, if you are just exploring the field on your own I would recommend going through these resources.Video lectures by Uri AlonVideo Lectures by Jeff GorePrinciples of Synthetic Biology (at edx)Coursera specialization on systems biology.If you are looking for mathematical intensive start with first 2 and if you are looking for biologically intensive begin with last 2. Either way go through all 4 of them as they provide diverse perspective on systems biology which is very important. As you will move through these materials all the necessary supplementary information like books, papers and softwares will be informed within these materials itself.Hope this helps!
    1. It is especially thanks to the work of Yann LeCun and Yoshua Bengio (LeCun et al., 2015) that the application of deep neural networks has boomed in recent years. The technique, which utilizes neural networks with many layers and enhanced backpropagation algorithms for learning, was made possible through both new research and the ever increasing performance of computer chips.
  6. Dec 2018
    1. Are All Training Examples Created Equal? An Empirical Study

      从此paper了解到了叫 Active learning 的有趣概念,这似乎和自己设计的连续参数训练数据采样池很接近。。。。

      这篇文章的主要工作是给出了一个在图像分类中关于训练样本重要性的研究,对于样本的重要度采用基于梯度的方法进行度量。文章的结论可能表明在深度学习中主动学习或许并不总是有效的。

    1. Teachers must honor and respect youth-led and youth-centered writing practices

      I've been recently returning to descriptive processes and "looking" at student work (a la Carini) just to keep abreast of what youth are doing and creating today. It's always changing and I think we can support this honoring and respecting by spending time learning from the work itself. I also think it opens up the ideas that would support educators in creating the opportunities for students to write in multiple ways, for multiple purposes, etc.

      Christina Puntel's piece on Looking with the Heart is one of my favorites that I return to/share time and time again: https://thecurrent.educatorinnovator.org/resource/looking-with-the-heart-celebrating-the-human-in-the-digital

  7. Nov 2018
    1. Learning with Random Learning Rates

      作者提出了一种新的Alrao优化算法,让网络中每个 unit 或 feature 都各自从不同级别的随机分布中采样获得其自己的学习率。该算法没有额外计算损耗,可以更快速达到理想 lr 下的SGD性能,用来测试 DL 模型很棒!

    2. An analytic theory of generalization dynamics and transfer learning in deep linear networks

      这是一篇谈论泛化error和Transfer L.的理论 paper. 虽实验细节还没看懂, 但结论很意义:新提出一个解析的理论方法,发现网络最首要先学到并依赖的是tast structure(通过early-stoping)而不是网络size!这也就解释了为啥随机data比real data更容易被学习,似乎存在更好的non-GD优化策略.

      关于 SNR 也有迁移实验,说可以从高 SNR 迁移到低 SNR。。。

    3. A Survey on Deep Transfer Learning

      不仅综述了迁移学习的现状,也对其进行了分类。同时,还给出了“深度迁移”的概念,强调了待迁移的两个学习任务之间的非线性关系。其实这也很自然,我们本来对线性的“相似”学习任务迁移就兴趣一般,也没多大研究意义。。。。

    1. At the same time, a large share of YouTube users say the site is important for helping them figure out how to do things they haven’t done before. Fully 87% of users say the site is important for this reason, with 51% saying it is very important. And the ability to learn how to do new things is important to users from a wide range of age groups. Roughly half (53%) of users ages 18 to 29 say the site is very important to them for this reason, and that view is shared by 41% of users ages 65 and older. In some cases, users’ responses to these questions show substantial variation based on how frequently they visit the site. Most notably, people who use the site regularly place an especially high level of importance on YouTube for learning about world events. Some 32% of users who visit the site several times a day – and 19% of those who visit once a day – say it is very important for helping them understand things that are happening in the world. That compares with 10% of users who visit less often.

      87% of users say that YouTube is an important outlet for informal learning (51% say it is very important).

    1. People learn best when they care about a topic and believe they can master it. This presents us with a problem because most scientists don’t want to program: they want to do science. In addition, their early experiences with computers are often demoralizing, and believing that something will be hard to learn is a self-fulfilling prophecy.

      From the revelations in How Learning Works (p. 79) that value and expectancies drive motivation and how these interact derives from the learning environment, I see that in this situation, we need to build a positive learning environment more via the third and fourth factors listed above (Encouraging learners to learn from each other and acknowledging confusion). Setting learning goals that show the relevance of the coding skills to the learners' future professional existence and our own enthusiasm for the coding, will help us create value and design assessments and activities that are in alignment with the goals. Thus, learners' expectations can be enhanced.