Hirstglen Machine Learning Research Papers Pdf 2016

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Machine learning research papers pdf 2016

Self-Study Guide to Machine Learning. Paper SAS2360-2016 Best Practices for Machine Learning Applications Brett Wujek, Patrick Hall, and Funda Güneș SAS Institute Inc. ABSTRACT Building representative machine learning models that generalize well on future data requires careful consideration both of the data at hand and of assumptions about the various available training algorithms., Abstract: In machine learning, a computer first learns to perform a task by studying a training set of examples. The computer then performs the same task with data it hasn't encountered before. This article presents a brief overview of machine-learning technologies, with ….

Deep Residual Learning for Image Recognition

Machine Learning Papers and Abstracts. 26/02/2017 · Awesome - Most Cited Deep Learning Papers [Notice] This list is not being maintained anymore because of the overwhelming amount of deep learning papers published every day since 2017. A curated list of the most cited deep learning papers (2012-2016), 05/11/2019 · Pop Music Transformer: Generating Music with Rhythm and Harmony. 1 Feb 2020 • YatingMusic/remi • . By serializing a score as a sequence of MIDI-like events, recent work has demonstrated that state-of-the-art sequence models with self-attention work nicely for this task, especially for composing music with long-range coherence..

pervised classification and reinforcement learning. We explain why we feel that recent directions in machine learning, such as the trend toward deep reinforcement learning and agents acting in broader environments, suggests an increasing relevance for research around accidents. In Sections 3-7, we explore five concrete problems in AI safety Journal of Machine Learning Research. The Journal of Machine Learning Research (JMLR) provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. All published papers are freely available online. JMLR has a commitment to rigorous yet rapid reviewing.

Deep Residual Learning for Image Recognition Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun Microsoft Research {kahe, v-xiangz, v-shren, jiansun}@microsoft.com Abstract Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used Machine learning and Deep Learning research advances are transforming our technology. Here are the 20 most important (most-cited) scientific papers that have been published since 2014, starting with "Dropout: a simple way to prevent neural networks from overfitting".

Impact Factor for Top Journals of Computer Science and Electronics, 2016 Impact Factor for Top Journals of Computer Science and Electronics, 2015 How to chart a successful research … The MIT Media Lab is an interdisciplinary research lab that encourages the unconventional mixing and matching of seemingly disparate research areas. All Publications — MIT Media Lab Search

but the recent success of applying maching learning to other challenging decision-making domains [29,33,3] suggests that the idea may not be too far-fetched. In particular, Rein-forcement Learning (RL) (§2) has become an active area in machine learning research [30,28,32,29,33]. RL deals with agents that learn to make better decisions directly Top 10 AI, Machine Learning Research Articles to know How to Optimize Your Jupyter Notebook KDnuggets Home » News » 2016 » Jan » Publications » 20+ hottest research papers on Computer Vision, Machine Learning ( 16:n02 )

Using Machine Learning Algorithms for Breast (FAMS 2016) Using Machine Learning Algorithms for Breast Cancer Risk Prediction and Diagnosis Hiba Asria*,Hajar Mousannifb,Hassan Al Moatassimec,Thomas Noeld aOSER Research Team,FSTG Cadi Ayyad University,Marrakech 40000,Morocco bLISI Laboratory,FSSM Cadi Ayyad University,Marrakech 40000,Morocco cOSER Research … usability, is machine learning. Promising an answer to many of the old and new challenges of manufacturing, machine learning is widely discussed by researchers and practitioners alike. However, the field is very broad and even confusing which presents a challenge and a barrier hindering wide application. Here, this paper contributes in

Beginner. A beginner is a programmer with an interest in machine learning. They may have started to read a book, Wikipedia page, or taken a few lessons in a course, but they don’t really “get it” yet.They’re frustrated because the advice they are getting is for intermediates and advanced levels. Artificial Intelligence and Machine Learning: Policy Paper internetsociety.org @internetsociety 4 Artificial Intelligence - What it’s all about Artificial intelligence (AI) traditionally refers to an artificial creation of human-like intelligence that can learn, reason, plan, perceive, or process natural language5.

Using Machine Learning Algorithms for Breast (FAMS 2016) Using Machine Learning Algorithms for Breast Cancer Risk Prediction and Diagnosis Hiba Asria*,Hajar Mousannifb,Hassan Al Moatassimec,Thomas Noeld aOSER Research Team,FSTG Cadi Ayyad University,Marrakech 40000,Morocco bLISI Laboratory,FSSM Cadi Ayyad University,Marrakech 40000,Morocco cOSER Research … Model-based machine learning Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of

Deep Residual Learning for Image Recognition Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun Microsoft Research {kahe, v-xiangz, v-shren, jiansun}@microsoft.com Abstract Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used You can research machine learning algorithms. Do not be scared off by the formal academic language and medium of papers and articles. You do not need to be a PhD research nor a machine learning algorithm expert. You can read the papers, books and algorithm implementations just as well as anyone.

Beginner. A beginner is a programmer with an interest in machine learning. They may have started to read a book, Wikipedia page, or taken a few lessons in a course, but they don’t really “get it” yet.They’re frustrated because the advice they are getting is for intermediates and advanced levels. Journal of Machine Learning Research. The Journal of Machine Learning Research (JMLR) provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. All published papers are freely available online. JMLR has a commitment to rigorous yet rapid reviewing.

Artificial Intelligence and Machine Learning: Policy Paper internetsociety.org @internetsociety 4 Artificial Intelligence - What it’s all about Artificial intelligence (AI) traditionally refers to an artificial creation of human-like intelligence that can learn, reason, plan, perceive, or process natural language5. but the recent success of applying maching learning to other challenging decision-making domains [29,33,3] suggests that the idea may not be too far-fetched. In particular, Rein-forcement Learning (RL) (§2) has become an active area in machine learning research [30,28,32,29,33]. RL deals with agents that learn to make better decisions directly

Since the undertaken research reflects a data-driven process, the arising gaps and limitations in machine learning research in DM are closely related to the availability of data. Clinical, diagnostic data and EHR are plentiful due to low cost of their retrieval, in contrast to other types of data, such as biological, which are more difficult The MIT Media Lab is an interdisciplinary research lab that encourages the unconventional mixing and matching of seemingly disparate research areas. All Publications — MIT Media Lab Search

Top 10 AI, Machine Learning Research Articles to know How to Optimize Your Jupyter Notebook KDnuggets Home » News » 2016 » Jan » Publications » 20+ hottest research papers on Computer Vision, Machine Learning ( 16:n02 ) Impact Factor for Top Journals of Computer Science and Electronics, 2016 Impact Factor for Top Journals of Computer Science and Electronics, 2015 How to chart a successful research …

Machine Learning Papers and Abstracts To view a paper, click on the ps image (for gzipped postscript file) or pdf image (for pdf file). Book Recommending Using Text Categorization with Extracted Information Raymond J. Mooney, Paul N. Bennett and Loriene Roy Artificial Intelligence and Machine Learning: Policy Paper internetsociety.org @internetsociety 4 Artificial Intelligence - What it’s all about Artificial intelligence (AI) traditionally refers to an artificial creation of human-like intelligence that can learn, reason, plan, perceive, or process natural language5.

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Machine learning research papers pdf 2016

Using Machine Learning Algorithms for Breast Cancer Risk. but the recent success of applying maching learning to other challenging decision-making domains [29,33,3] suggests that the idea may not be too far-fetched. In particular, Rein-forcement Learning (RL) (§2) has become an active area in machine learning research [30,28,32,29,33]. RL deals with agents that learn to make better decisions directly, Top 10 AI, Machine Learning Research Articles to know How to Optimize Your Jupyter Notebook KDnuggets Home » News » 2016 » Jan » Publications » 20+ hottest research papers on Computer Vision, Machine Learning ( 16:n02 ).

XGBoost A Scalable Tree Boosting System

Machine learning research papers pdf 2016

All Publications — MIT Media Lab. Impact Factor for Top Journals of Computer Science and Electronics, 2016 Impact Factor for Top Journals of Computer Science and Electronics, 2015 How to chart a successful research … https://en.wikipedia.org/wiki/CIFAR-10 TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems (Preliminary White Paper, November 9, 2015) Mart´ın Abadi, Ashish Agarwal, Paul ….

Machine learning research papers pdf 2016


Using Machine Learning Algorithms for Breast (FAMS 2016) Using Machine Learning Algorithms for Breast Cancer Risk Prediction and Diagnosis Hiba Asria*,Hajar Mousannifb,Hassan Al Moatassimec,Thomas Noeld aOSER Research Team,FSTG Cadi Ayyad University,Marrakech 40000,Morocco bLISI Laboratory,FSSM Cadi Ayyad University,Marrakech 40000,Morocco cOSER Research … Open PDF in Browser. Add Paper to My Library . Share: Permalink. Using the URL or DOI link below will ensure access to this page indefinitely. Copy URL. Copy URL. Machine Learning with Personal Data. Queen Mary School of Law Legal Studies Research Paper No. 247/2016. 23 Pages Posted: 8 Nov 2016. See all articles by Dimitra Kamarinou Dimitra Kamarinou. Queen Mary University of London, School of

usability, is machine learning. Promising an answer to many of the old and new challenges of manufacturing, machine learning is widely discussed by researchers and practitioners alike. However, the field is very broad and even confusing which presents a challenge and a barrier hindering wide application. Here, this paper contributes in Beginner. A beginner is a programmer with an interest in machine learning. They may have started to read a book, Wikipedia page, or taken a few lessons in a course, but they don’t really “get it” yet.They’re frustrated because the advice they are getting is for intermediates and advanced levels.

Several Google services use TensorFlow in production, we have released it as an open-source project, and it has become widely used for machine learning research. In this paper, we describe the TensorFlow dataflow model and demonstrate the compelling performance that TensorFlow achieves for several real-world applications. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems (Preliminary White Paper, November 9, 2015) Mart´ın Abadi, Ashish Agarwal, Paul …

Open PDF in Browser. Add Paper to My Library . Share: Permalink. Using the URL or DOI link below will ensure access to this page indefinitely. Copy URL. Copy URL. Machine Learning with Personal Data. Queen Mary School of Law Legal Studies Research Paper No. 247/2016. 23 Pages Posted: 8 Nov 2016. See all articles by Dimitra Kamarinou Dimitra Kamarinou. Queen Mary University of London, School of 01/08/2018 · The application and development of machine-learning methods used in experiments at the frontiers of particle physics (such as the Large Hadron Collider) are reviewed, including recent

Papers making claims about learning problems or methods provide solid support via empirical studies, theoretical analysis, or comparison to psychological phenomena. Applications papers show how to apply learning methods to solve important applications problems. Research methodology papers improve how machine learning research is conducted. All Using Machine Learning Algorithms for Breast (FAMS 2016) Using Machine Learning Algorithms for Breast Cancer Risk Prediction and Diagnosis Hiba Asria*,Hajar Mousannifb,Hassan Al Moatassimec,Thomas Noeld aOSER Research Team,FSTG Cadi Ayyad University,Marrakech 40000,Morocco bLISI Laboratory,FSSM Cadi Ayyad University,Marrakech 40000,Morocco cOSER Research …

View Machine Learning Research Papers on Academia.edu for free. Journal of Machine Learning Research. The Journal of Machine Learning Research (JMLR) provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. All published papers are freely available online. JMLR has a commitment to rigorous yet rapid reviewing.

Machine learning research papers pdf 2016

Hi guys! Welcome to r/MachineLearning's 2016 Best Paper Award!. The idea is to have a community-wide vote for the best papers of this year. I hope you find this to be a good idea, mods please tell me if this breaks any rules/if you had something like this in store. Several machine learning approaches have been applied to the problem of classifying research papers. Taheriyan (2011) seeks to classify com-puter science research papers by mapping the relationships among authorship, citations, and references and then using those relationships to infer subject classifications for unclassified

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A Review of Relational Machine Learning for Knowledge Graphs

Machine learning research papers pdf 2016

A Review of Relational Machine Learning for Knowledge Graphs. Model-based machine learning Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of, Abstract Deeplearninghasattractedtremendousattentionfromresearchersinvariousfieldsof informationengineeringsuchasAI,computervision,andlanguageprocessing[Kalch-.

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Resource Management with Deep Reinforcement Learning. but the recent success of applying maching learning to other challenging decision-making domains [29,33,3] suggests that the idea may not be too far-fetched. In particular, Rein-forcement Learning (RL) (§2) has become an active area in machine learning research [30,28,32,29,33]. RL deals with agents that learn to make better decisions directly, TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems (Preliminary White Paper, November 9, 2015) Mart´ın Abadi, Ashish Agarwal, Paul ….

Artificial Intelligence and Machine Learning: Policy Paper internetsociety.org @internetsociety 4 Artificial Intelligence - What it’s all about Artificial intelligence (AI) traditionally refers to an artificial creation of human-like intelligence that can learn, reason, plan, perceive, or process natural language5. Deep Residual Learning for Image Recognition Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun Microsoft Research {kahe, v-xiangz, v-shren, jiansun}@microsoft.com Abstract Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used

06/02/2020 · Machine-learning system should enable developers to improve computing efficiency in a range of applications. January 6, 2020 Finding a good read among billions of choices Using Machine Learning Algorithms for Breast (FAMS 2016) Using Machine Learning Algorithms for Breast Cancer Risk Prediction and Diagnosis Hiba Asria*,Hajar Mousannifb,Hassan Al Moatassimec,Thomas Noeld aOSER Research Team,FSTG Cadi Ayyad University,Marrakech 40000,Morocco bLISI Laboratory,FSSM Cadi Ayyad University,Marrakech 40000,Morocco cOSER Research …

In this paper, we describe XGBoost, a scalable machine learning system for tree boosting. The system is available as an open source package2. The impact of the system has been widely recognized in a number of machine learning and data mining challenges. Take the challenges hosted by the machine learning competition site Kaggle for example. A- Paper SAS2360-2016 Best Practices for Machine Learning Applications Brett Wujek, Patrick Hall, and Funda Güneș SAS Institute Inc. ABSTRACT Building representative machine learning models that generalize well on future data requires careful consideration both of the data at hand and of assumptions about the various available training algorithms.

06/02/2020 · Machine-learning system should enable developers to improve computing efficiency in a range of applications. January 6, 2020 Finding a good read among billions of choices The MIT Media Lab is an interdisciplinary research lab that encourages the unconventional mixing and matching of seemingly disparate research areas. All Publications — MIT Media Lab Search

The Proceedings of Machine Learning Research (formerly JMLR Workshop and Conference Proceedings) is a series aimed specifically at publishing machine learning research presented at workshops and conferences. Each volume is separately titled and associated with a particular workshop or conference. Volumes are published online on the PMLR web site. learning or hierarchical learning, has emerged as a new area of machine learning research [20, 163]. During the past several years, the techniques developed from deep learning research have already been impacting a wide range of signal and information processing work within the traditional and the new, widened scopes including key aspects of

View Statistical machine learning Research Papers on Academia.edu for free. Open PDF in Browser. Add Paper to My Library . Share: Permalink. Using the URL or DOI link below will ensure access to this page indefinitely. Copy URL. Copy URL. Machine Learning with Personal Data. Queen Mary School of Law Legal Studies Research Paper No. 247/2016. 23 Pages Posted: 8 Nov 2016. See all articles by Dimitra Kamarinou Dimitra Kamarinou. Queen Mary University of London, School of

Hi guys! Welcome to r/MachineLearning's 2016 Best Paper Award!. The idea is to have a community-wide vote for the best papers of this year. I hope you find this to be a good idea, mods please tell me if this breaks any rules/if you had something like this in store. objective of this paper is to explore the potential impact of big data challenges, open research issues, and various tools associated with it. As a result, this article provides a platform to explore big data at numerous stages. Additionally, it opens a new horizon for researchers to develop the solution, based on the challenges and open

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems (Preliminary White Paper, November 9, 2015) Mart´ın Abadi, Ashish Agarwal, Paul … Machine Learning Papers and Abstracts To view a paper, click on the ps image (for gzipped postscript file) or pdf image (for pdf file). Book Recommending Using Text Categorization with Extracted Information Raymond J. Mooney, Paul N. Bennett and Loriene Roy

Model-based machine learning Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of View Statistical machine learning Research Papers on Academia.edu for free.

Abstract Deeplearninghasattractedtremendousattentionfromresearchersinvariousfieldsof informationengineeringsuchasAI,computervision,andlanguageprocessing[Kalch- I'll expand the timeline a little and include Dec 2015 as well. I greatly enjoyed the paper:([1512.03385] Deep Residual Learning for Image Recognition that came out in Dec 2015. Deep learning has been driving major breakthroughs in achieving stat...

In this paper, we describe XGBoost, a scalable machine learning system for tree boosting. The system is available as an open source package2. The impact of the system has been widely recognized in a number of machine learning and data mining challenges. Take the challenges hosted by the machine learning competition site Kaggle for example. A- Machine Learning research has been extremely active the last few years. The result is a large number of very accurate and efficient algorithms that are quite easy to use for a practitioner. It seems rewarding and almost mandatory for (computer) scientist and engineers to learn how and where Machine Learning can help to automate tasks 4

Abstract Deeplearninghasattractedtremendousattentionfromresearchersinvariousfieldsof informationengineeringsuchasAI,computervision,andlanguageprocessing[Kalch- In this paper, we describe XGBoost, a scalable machine learning system for tree boosting. The system is available as an open source package2. The impact of the system has been widely recognized in a number of machine learning and data mining challenges. Take the challenges hosted by the machine learning competition site Kaggle for example. A-

Model-based machine learning Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of Papers making claims about learning problems or methods provide solid support via empirical studies, theoretical analysis, or comparison to psychological phenomena. Applications papers show how to apply learning methods to solve important applications problems. Research methodology papers improve how machine learning research is conducted. All

Machine learning the power and promise of computers that. Artificial Intelligence and Machine Learning: Policy Paper internetsociety.org @internetsociety 4 Artificial Intelligence - What it’s all about Artificial intelligence (AI) traditionally refers to an artificial creation of human-like intelligence that can learn, reason, plan, perceive, or process natural language5., it has become widely used for machine learning research. In this paper, we describe the TensorFlow dataflow model and demonstrate the compelling performance that Tensor-Flow achieves for several real-world applications. 1 Introduction In recent years, machine learning has driven advances in many different fields [3, 5, 24, 25, 29, 31, 42, 47, 50,.

Self-Study Guide to Machine Learning

Machine learning research papers pdf 2016

GitHub terryum/awesome-deep-learning-papers The most. Machine Learning Papers and Abstracts To view a paper, click on the ps image (for gzipped postscript file) or pdf image (for pdf file). Book Recommending Using Text Categorization with Extracted Information Raymond J. Mooney, Paul N. Bennett and Loriene Roy, I'll expand the timeline a little and include Dec 2015 as well. I greatly enjoyed the paper:([1512.03385] Deep Residual Learning for Image Recognition that came out in Dec 2015. Deep learning has been driving major breakthroughs in achieving stat....

JMLR Papers Journal of Machine Learning Research Homepage

Machine learning research papers pdf 2016

Papers With Code the latest in machine learning. Hi guys! Welcome to r/MachineLearning's 2016 Best Paper Award!. The idea is to have a community-wide vote for the best papers of this year. I hope you find this to be a good idea, mods please tell me if this breaks any rules/if you had something like this in store. https://en.m.wikipedia.org/wiki/List_of_important_publications_in_computer_science Learning from Electronic Health Data (December 2016) Gesture Recognition (May 2012 - present) Large Scale Learning (Jul 2009 - present) Mining and Learning with Graphs and Relations (February 2009 - present) Grammar Induction, Representation of Language and Language Learning (Nov 2010 - Apr 2011) Causality (Sep 2007 - May 2010).

Machine learning research papers pdf 2016


In this paper, we describe XGBoost, a scalable machine learning system for tree boosting. The system is available as an open source package2. The impact of the system has been widely recognized in a number of machine learning and data mining challenges. Take the challenges hosted by the machine learning competition site Kaggle for example. A- Machine Learning research has been extremely active the last few years. The result is a large number of very accurate and efficient algorithms that are quite easy to use for a practitioner. It seems rewarding and almost mandatory for (computer) scientist and engineers to learn how and where Machine Learning can help to automate tasks 4

Deep Residual Learning for Image Recognition Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun Microsoft Research {kahe, v-xiangz, v-shren, jiansun}@microsoft.com Abstract Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used 06/02/2020 · Machine-learning system should enable developers to improve computing efficiency in a range of applications. January 6, 2020 Finding a good read among billions of choices

Paper SAS2360-2016 Best Practices for Machine Learning Applications Brett Wujek, Patrick Hall, and Funda Güneș SAS Institute Inc. ABSTRACT Building representative machine learning models that generalize well on future data requires careful consideration both of the data at hand and of assumptions about the various available training algorithms. In this paper, we describe XGBoost, a scalable machine learning system for tree boosting. The system is available as an open source package2. The impact of the system has been widely recognized in a number of machine learning and data mining challenges. Take the challenges hosted by the machine learning competition site Kaggle for example. A-

View Machine Learning Research Papers on Academia.edu for free. 06/02/2020 · Machine-learning system should enable developers to improve computing efficiency in a range of applications. January 6, 2020 Finding a good read among billions of choices

Several machine learning approaches have been applied to the problem of classifying research papers. Taheriyan (2011) seeks to classify com-puter science research papers by mapping the relationships among authorship, citations, and references and then using those relationships to infer subject classifications for unclassified it has become widely used for machine learning research. In this paper, we describe the TensorFlow dataflow model and demonstrate the compelling performance that Tensor-Flow achieves for several real-world applications. 1 Introduction In recent years, machine learning has driven advances in many different fields [3, 5, 24, 25, 29, 31, 42, 47, 50,

Journal of Machine Learning Research. The Journal of Machine Learning Research (JMLR) provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. All published papers are freely available online. JMLR has a commitment to rigorous yet rapid reviewing. objective of this paper is to explore the potential impact of big data challenges, open research issues, and various tools associated with it. As a result, this article provides a platform to explore big data at numerous stages. Additionally, it opens a new horizon for researchers to develop the solution, based on the challenges and open

I'll expand the timeline a little and include Dec 2015 as well. I greatly enjoyed the paper:([1512.03385] Deep Residual Learning for Image Recognition that came out in Dec 2015. Deep learning has been driving major breakthroughs in achieving stat... Several machine learning approaches have been applied to the problem of classifying research papers. Taheriyan (2011) seeks to classify com-puter science research papers by mapping the relationships among authorship, citations, and references and then using those relationships to infer subject classifications for unclassified

Journal of Machine Learning Research. The Journal of Machine Learning Research (JMLR) provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. All published papers are freely available online. JMLR has a commitment to rigorous yet rapid reviewing. O'Rorke, P. (1987). LT revisited:Experimental results of applying explanation-based learning to the logic of Principia Mathematica. In Proceedings of the Fourth International Workshop on Machine Learning (pp.148-159). Irvine, CA: Morgan Kaufmann.

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