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A New Look at an Old Problem: A Universal Learning Approach to Linear Regression [article]

Koby Bibas, Yaniv Fogel, Meir Feder
2019 arXiv   pre-print
Linear regression is a classical paradigm in statistics. A new look at it is provided via the lens of universal learning.  ...  In applying universal learning to linear regression the hypotheses class represents the label y∈ R as a linear combination of the feature vector x^Tθ where x∈ R^M, within a Gaussian error.  ...  This work provides a new view of this problem based on recent results in universal learning.  ... 
arXiv:1905.04708v1 fatcat:li5a5s74lrahdiwupir6tp3jsm

Which Problem is Being Solved?

Neil Charness
1991 Contemporary Psychology  
In many ways, the approach adopted by the authors in the context of the univariate general linear model is similar to the hi- erarchical multiple regression approach that forms the basis of the exposition  ...  There are strengths and weaknesses to such an approach.  ... 
doi:10.1037/029526 fatcat:x7747csmvzcadg2yu7p6unpw3q

Using the 4MAT Framework to Design a Problem-Based Learning Biostatistics Course

Amy S. Nowacki
2011 Journal of Statistics Education  
The study presents and applies the 4MAT theoretical framework to educational planning to transform a biostatistics course into a problem-based learning experience.  ...  Using a four-question approach, described are specific activities/materials utilized at both the class and course levels.  ...  The class time saved with such an approach should be more than sufficient for problem-based learning exercises.  ... 
doi:10.1080/10691898.2011.11889622 fatcat:jtxklwr4xzdzbd6jwjakwtfixe

Impact of Context-Rich, Multifaceted Problems on Students' Attitudes Towards Problem-Solving [article]

C.A. Ogilvie
2008 arXiv   pre-print
Students enrolled in a physics course submitted a written reflection both at the start and the end of the course on how they solve problems.  ...  We then describe the extent to which students' beliefs about physics problem-solving change due to their experience throughout a semester with context-rich, multifaceted problems.  ...  to me that student reflections may have beneficial impact on how students approach their studies.  ... 
arXiv:0809.1081v1 fatcat:5q5gfl4n65dyzpr3jtnhbkbkny

Linear inverse problems in imaging

Alejandro Ribes, Francis Schmitt
2008 IEEE Signal Processing Magazine  
He is currently a visiting scholar at the National Yang-Ming University, Taipei, Taiwan.  ...  He has been a research assistant at the University of Oxford, U.K., and a lecturer at the Computer Science Department of Ecole Polytechnique, Palaiseau, France.  ...  MULTIVARIATE LINEAR REGRESSION If we take a closer look at (22) , we observe that this equation represents a multivariate linear regression model, a well-known expression that can be found in any multivariate  ... 
doi:10.1109/msp.2008.923099 fatcat:mfii2gilkjbh3pmqsaabklhqg4

Acceptance of Problem Based Learning among Medical Students

Redhwan Ahmed Al-Naggar, Yuri V Bobryshev
2012 Journal of Community Medicine & Health Education  
Aim: The objective of this study is to determine the acceptance of Problem Based Learning (PBL) among medical students.  ...  T-test and ANOVA test which were conducted to determine if there was a significant difference between the study parameters. Multiple linear regressions were used in multivariate analysis.  ...  Acknowledgements The study was supported by the International Medical School, Management and Science University Malaysia.  ... 
doi:10.4172/2161-0711.1000146 fatcat:35v5tminmrbobbj3p2avg74b7q

Constructive algorithms for structure learning in feedforward neural networks for regression problems

Tin-Yau Kwok, Dit-Yan Yeung
1997 IEEE Transactions on Neural Networks  
In this survey paper, we review the constructive algorithms for structure learning in feedforward neural networks for regression problems.  ...  The basic idea is to start with a small network, then add hidden units and weights incrementally until a satisfactory solution is found.  ...  ACKNOWLEDGMENT The authors would like to thank the anonymous reviewers for their constructive comments on an earlier version of this paper.  ... 
doi:10.1109/72.572102 pmid:18255666 fatcat:y3zcqk5zpjgvxb5trqmd5gbayy

Sensor Management Problems of Nuclear Detection [chapter]

Tamra Carpenter, Jerry Cheng, Fred Roberts, Minge Xie
2011 Springer Series in Reliability Engineering  
This article describes a variety of approaches to sensor management in a multi-institution project on nuclear detection, which is based at Rutgers University and supported by the US Department of Homeland  ...  These approaches revolve around formulating the related problems using precise mathematical language and then developing tools of the mathematical sciences to solve them.  ...  It emphasizes a variety of approaches to sensor management in a multi-institution project on nuclear detection, which is based at Rutgers University and includes Princeton University and Texas State University-San  ... 
doi:10.1007/978-0-85729-470-8_11 fatcat:a4f2ku7iqzdozmwia7vf6s3pha

Numerical Approximation in CFD Problems Using Physics Informed Machine Learning [article]

Siddharth Rout, Vikas Dwivedi, Balaji Srinivasan
2021 arXiv   pre-print
The thesis focuses on various techniques to find an alternate approximation method that could be universally used for a wide range of CFD problems but with low computational cost and low runtime.  ...  Extreme learning machine (ELM) is a very fast neural network algorithm at the cost of tunable parameters. The ELM based variant of the proposed model is tested over the advection-diffusion problem.  ...  Addition of a new term 'Ax' helps the convergence by guiding the weights towards linear fitting at early stage of learning.  ... 
arXiv:2111.02987v1 fatcat:i4l3q2keyngehb7ss737d57qt4

Mining the past to determine the future: Problems and possibilities

David J. Hand
2009 International Journal of Forecasting  
This paper looks at some of these difficulties, using illustrations with applications from various areas.  ...  An awareness of these, and of the weaknesses as well as the possibilities of these large data sets, is necessary if useful forecasts are to be made.  ...  Acknowledgements The author's work on this paper was partially supported by a Royal Society Wolfson Research Merit Award.  ... 
doi:10.1016/j.ijforecast.2008.09.004 fatcat:bbvvgmlpxbhg3e44ynnnuzsuuq


Neslihan Durmuşoğlu Saltalı, Emel Arslan, Coşkun Arslan
2018 Zenodo  
Moreover, appropriately responding to a social situation as a sub-dimension of socio-emotional adaptation is a predictor of only passive-assertive, reserved-submissive and positive problem-solving approaches  ...  Giving appropriate responses to social situations is a significant predictor of assertive, passive assertive and positive problem-solving approaches.  ...  An examination of the current literature on this issue reveals that there are lots of research studies suggesting that there is a linear relationship between development of problem-solving skills and accepting  ... 
doi:10.5281/zenodo.1438398 fatcat:2axhzbuxlzhb3ftnbs4jhjfsce

Regression Tree Fields — An efficient, non-parametric approach to image labeling problems

J. Jancsary, S. Nowozin, T. Sharp, C. Rother
2012 2012 IEEE Conference on Computer Vision and Pattern Recognition  
We introduce Regression Tree Fields (RTFs), a fully conditional random field model for image labeling problems.  ...  of magnitude faster than for DTFs, (ii) RTFs can be applied to both discrete and continuous vector-valued labeling tasks, and (iii) the entire model, including the structure of the regression trees and  ...  The RTF denoising model is as before and we learn to remove these artifacts. Face Colorization Colorization is the task of adding color to a gray-scale image, e.g. an old photograph.  ... 
doi:10.1109/cvpr.2012.6247950 dblp:conf/cvpr/JancsaryNSR12 fatcat:ri2vdnamx5fglibkesqyor3gr4

Comments about Hilbert's 16'th problem [article]

John Atwell Moody
2015 arXiv   pre-print
Local analytic germs can be simultaneously deformed equivariantly for the flow if there is one holomorphic solution whose degree is high compared to local discrepancy.  ...  We may perform a linear regression to see how the logarithmic derivative with respect to time may depend on the real value of this vector.  ...  determined by linear regression on the numbers of individuals of all species.  ... 
arXiv:1110.2154v6 fatcat:bt44zctqvfentloskxeyw6wgte

Simultaneous co-clustering and learning to address the cold start problem in recommender systems

Andre Luiz Vizine Pereira, Eduardo Raul Hruschka
2015 Knowledge-Based Systems  
The approach is based on an existing algorithm, SCOAL (Simultaneous Co-Clustering and Learning), and provides a hybrid recommendation approach that can address the (pure) cold start problem, where no collaborative  ...  Despite recent advances in RS, the cold start problem is still a relevant issue that deserves further attention, and arises due to the lack of prior information about new users and new items.  ...  The Pearson correlation measures the linear correlation between two vectors of ratings; the cosine measure looks at the angle between two vectors of ratings where a smaller angle is regarded as implying  ... 
doi:10.1016/j.knosys.2015.02.016 fatcat:ubpakki4rbeoxm6lwbuw54x2vy

Volatile metabolome: problems and prospects

Bruce A Kimball
2016 Bioanalysis  
Financial & competing interests disclosure The author has no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject  ...  n-alkane added to the sample at a universal concentration.  ...  It is time to stop looking at the volatile metabolome as analysts and start tackling it as scientists.  ... 
doi:10.4155/bio-2016-0203 pmid:27532599 fatcat:houiuswopzekfmpxbcsmgjot4q
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