Jeffrey > Learning

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1Just-in-Time Teaching (JiTT): Using the Web to Enhance Classroom Learning
A. Gavrin, J. Watt, K. Marrs, и R. Jr. Computers in Education Journal,, (in press)
19 лет назад , @yish
web
elearning
learning
teaching
just-in-time
blended
webelearninglearningteachingjust-in-timeblended
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10Language Models are Few-Shot Learners
T. Brown, B. Mann, N. Ryder, M. Subbiah, J. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell и 21 other автор(ы). (2020)cite arxiv:2005.14165Comment: 40+32 pages.
4 лет назад , @parismic
language
few
learning
gpt
model
shot
languagefewlearninggptmodelshot
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2In Defense of Uniform Convergence: Generalization via derandomization with an application to interpolating predictors
J. Negrea, G. Dziugaite, и D. Roy. (2019)cite arxiv:1912.04265Comment: 12 pages.
5 лет назад , @kirk86
readings
generalization
bounds
learning
readingsgeneralizationboundslearning
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6Language models are unsupervised multitask learners
A. Radford, J. Wu, R. Child, D. Luan, D. Amodei, и I. Sutskever. (2019)
4 лет назад , @schwemmlein
models
multi-task
language
unsupervised
learning
antrag
deconspire
gpt
modelsmulti-tasklanguageunsupervisedlearningantragdeconspiregpt
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3DeepHeart: Semi-Supervised Sequence Learning for Cardiovascular Risk Prediction.
B. Ballinger, J. Hsieh, A. Singh, N. Sohoni, J. Wang, G. Tison, G. Marcus, J. Sanchez, C. Maguire, J. Olgin и 1 other автор(ы). AAAI, стр. 2079-2086. AAAI Press, (2018)
5 лет назад , @nosebrain
sequence
Cardiovascular
deep
prediction
learning
risk
paper-dzhi
sequenceCardiovasculardeeppredictionlearningriskpaper-dzhi
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1Automatic Differentiation in Machine Learning: a Survey
A. Baydin, B. Pearlmutter, A. Radul, и J. Siskind. Journal of Machine Learning Research, v18 (153): 1-43 (2018)
3 лет назад , @sdo
ad
differentiation
deep
automatic
learning
addifferentiationdeepautomaticlearning
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1Language Models are Unsupervised Multitask Learners
A. Radford, J. Wu, R. Child, D. Luan, D. Amodei, и I. Sutskever. (2018)
6 лет назад , @kirk86
multitask
learning
multitasklearning
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1Forward Thinking: Building Deep Random Forests
K. Miller, C. Hettinger, J. Humpherys, T. Jarvis, и D. Kartchner. (2017)cite arxiv:1705.07366.
7 лет назад , @cscholz
deep
learning
deeplearning
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1Design and Development of a Learning Design Virtual Internship Program
D. Ruggiero, и J. Boehm. (2016)
8 лет назад , @yish
teacher
development
design
academic
learning
training
teacherdevelopmentdesignacademiclearningtraining
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4Retrieval Practice Produces More Learning than Elaborative Studying with Concept Mapping
J. Karpicke, и J. Blunt. Science, 331 (6018): 772-775 (2011)
12 лет назад , @jennymac
learning
active
learningactive
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1Online and Blended Learning: A Survey of Policy and Practice from K-12 Schools around the World.
M. Barbour, R. Brown, L. Waters, R. Hoey, J. Hunt, K. Kennedy, C. Ounsworth, A. Powell, и T. Trimm. report by International Association for K-12 Online Learning, (2011)
6 лет назад , @yish
learning
survey
blended
international
learningsurveyblendedinternational
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4Retrieval practice produces more learning than elaborative studying with concept mapping
J. Karpicke, и J. Blunt. Science, 331 (6018): 772-775 (2011)
4 лет назад , @yish
retrieval
assessment
practice
design
learning
education
retrievalassessmentpracticedesignlearningeducation
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2Use and Trust of Simple Independent Open Learner Models to Support Learning within and across Courses
S. Bull, P. Gardner, N. Ahmad, J. Ting, и B. Clarke. User Modeling, Adaptation, and Personalization, Springer, Heidelberg, (2009)
15 лет назад , @tobold
open_learner_model
sota_mcitn2
user_model
learning
open_learner_modelsota_mcitn2user_modellearning
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1Metacognitive control and strategy selection: Deciding to practice retrieval during learning.
J. Karpicke. Journal of Experimental Psychology: General, 138 (4): 469--486 (2009)
14 лет назад , @smatthiesen
meta-attention
metacognition
learning
meta-attentionmetacognitionlearning
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2Text Classification without Labeled Negative Documents.
G. Fung, J. Yu, H. Lu, и P. Yu. Proceedings of the 21st International Conference on Data, стр. 594-605. Tokyo, Japan, IEEE Computer Society, (апреля 2005)
18 лет назад , @kzhou
learning
positive
learningpositive
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1Handbook of computer game studies
J. Raessens, и J. Goldstein. The MIT Press, (2005)
14 лет назад , @yish
game
computer
haifa-games-course
design
games
learning
handbook
gamesresearch
theory
gamecomputerhaifa-games-coursedesigngameslearninghandbookgamesresearchtheory
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1Violent video games
J. Goldstein. MIT Press, Boston, (2005)
14 лет назад , @yish
violent
haifa-games-course
games
learning
video
violence
violenthaifa-games-coursegameslearningvideoviolence
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1Dynamics of an Information-Filtering Economy
J. Kephart, J. Hanson, D. Levine, B. Grosof, J. Sairamesh, R. Segal, и S. White. IBM Thomas J. Watson Research Center, (19xx)
18 лет назад , @jmm
Learning
Agents,
economics,
Info
LearningAgents,economics,Info
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1Courtz: An Agent that Pleases You (An Extended Abstract)
C. Goldman, Y. Mor, и J. Rosenschein. Proceedings of the First International Conference on Practical Applications of Intelligent Agents and Multi-Agents Technology (PAAM96), стр. 837--842. London, UK, (1996)
19 лет назад , @yish
assistive
learning
multiagent
user
agents
hci
interface
assistivelearningmultiagentuseragentshciinterface
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1Learn Your Opponent's Strategy (in Polynomial Time)! (Extended Abstract)
Y. Mor, C. Goldman, и J. Rosenschein. 1042, Springer Verlag, (1996)
18 лет назад , @grahl
AI
learning
multiagent
computational
gametheory
AIlearningmultiagentcomputationalgametheory
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публикации (спрятать)24
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1Just-in-Time Teaching (JiTT): Using the Web to Enhance Classroom Learning

10Language Models are Few-Shot Learners

2In Defense of Uniform Convergence: Generalization via derandomization with an application to interpolating predictors

6Language models are unsupervised multitask learners

3DeepHeart: Semi-Supervised Sequence Learning for Cardiovascular Risk Prediction.

1Automatic Differentiation in Machine Learning: a Survey

1Language Models are Unsupervised Multitask Learners

1Forward Thinking: Building Deep Random Forests

1Design and Development of a Learning Design Virtual Internship Program

4Retrieval Practice Produces More Learning than Elaborative Studying with Concept Mapping

1Online and Blended Learning: A Survey of Policy and Practice from K-12 Schools around the World.

4Retrieval practice produces more learning than elaborative studying with concept mapping

2Use and Trust of Simple Independent Open Learner Models to Support Learning within and across Courses

1Metacognitive control and strategy selection: Deciding to practice retrieval during learning.

2Text Classification without Labeled Negative Documents.

1Handbook of computer game studies

1Violent video games

1Dynamics of an Information-Filtering Economy

1Courtz: An Agent that Pleases You (An Extended Abstract)

1Learn Your Opponent's Strategy (in Polynomial Time)! (Extended Abstract)

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