| copyright_years | title |
|---|---|
2020 |
Archive |
- 2019
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2019/05/01, Ellie Yang
Classification Algorithms in Modeling Categorical Variables: A Comparison of Multinomial Logistic Regression
Ellie Yang
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2019/04/24, Ron Stewart
A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications
Finn Kuusisto, John Steill, Zhaobin Kuang, James Thomson, David Page, Ron Stewart
AMIA Joint Summits on Translational Science, 2017
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2019/04/24, Ron Stewart
Rediscovering Don Swanson: The Past, Present and Future of Literature-based Discovery
Neil R. Smalheiser
Journal of Data and Information Science 2(4), 2017
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2019/04/24, Ron Stewart
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova
arXiv, 2018
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2019/04/17, Xiaomin Zhang
Robust Regression via Hard Thresholding
Kush Bhatia, Prateek Jain, Purushottam Kar
NIPS 28, 2015
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2019/04/17, Xiaomin Zhang
Consistent Robust Regression
Kush Bhatia, Prateek Jain, Parameswaran Kamalaruban, Purushottam Kar
NIPS 30, 2017
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2019/04/03, Ankit Pensia
Bandits With Heavy Tail
Sébastien Bubeck, Nicolò Cesa-Bianchi, Gábor Lugosi
IEEE Transactions on Information Theory 59(11), 2013
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2019/04/03, Ankit Pensia
Geometric median and robust estimation in Banach spaces
Stanislav Minsker
Bernoulli 21(4), 2015
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2019/03/27, David Merrell
Variational Inference: A Review for Statisticians
David M. Blei, Alp Kucukelbir, Jon D. McAuliffe
JASA 112(518), 2017
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2019/03/13, Tim Huegerich
Causal inference in statistics: An overview
Judea Pearl
Statistics Surveys 3, 2009
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2019/03/06, Matthew Bernstein
Using deep learning to model the hierarchical structure and function of a cell
Jianzhu Ma, Michael Ku Yu, Samson Fong, Keiichiro Ono, Eric Sage, Barry Demchak, Roded Sharan, Trey Ideker
Nature Methods 15, 2018
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2019/02/27, Sid Kiblawi
Deep Neural Networks for YouTube Recommendations
Paul Covington, Jay Adams, Emre Sargin
RecSys 10, 2016
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2019/02/20, Sathya Ravi
Explicitly Imposing Constraints in Deep Networks via Conditional Gradients Gives Improved Generalization and Faster Convergence
Sathya N. Ravi, Tuan Dinh, Vishnu Suresh Lokhande, Vikas Singh
AAAI 33, 2019
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2019/02/20, Sathya Ravi
Experimental Design on a Budget for Sparse Linear Models and Applications
Sathya Narayanan Ravi, Vamsi Ithapu, Sterling Johnson, Vikas Singh
ICML 33, 2016
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2019/02/13, Finn Kuusisto
The Hanabi Challenge: A New Frontier for AI Research
Nolan Bard, Jakob N. Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, H. Francis Song, Emilio Parisotto, Vincent Dumoulin, Subhodeep Moitra, Edward Hughes, Iain Dunning, Shibl Mourad, Hugo Larochelle, Marc G. Bellemare, Michael Bowling
arXiv, 2019
arxiv: toc meta pdf | info: research platform board game
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- 2018
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2018/12/12, David Merrell
Geometric Deep Learning: Going Beyond Euclidean Data
Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, Pierre Vandergheynst
IEEE Signal Processing Magazine 34(4), 2017
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2018/12/12, David Merrell
Spectral Networks and Locally Connected Networks on Graphs
Joan Bruna, Wojciech Zaremba, Arthur Szlam, Yann LeCun
ICLR 2, 2014
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2018/12/05, Yunyang Xiong
Resource-Constrained Neural Network Architecture Search
Yunyang Xiong, Ronak Mehta, Vikas Singh
arXive, 2019
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2018/11/28, Lucas Morton
Discovering Structure in High-Dimensional Data Through Correlation Explanation
Greg Ver Steeg, Aram Galstyan
NIPS 27, 2014
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2018/11/14, Ross Kleiman
AUCμ: A Performance Metric for Multi-Class Models
Ross Kleiman, David Page
ICML 36, 2019
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2018/11/07, Xianda (Bryce) Xu
Binarized Neural Networks
Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, Yoshua Bengio
NIPS 29, 2016
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2018/10/31, Yuriy Sverchkov
Anchors: High-Precision Model-Agnostic Explanations
Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin
AAAI 32, 2018
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2018/10/31, Yuriy Sverchkov
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin
KDD 22, 2016
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2018/10/31, Yuriy Sverchkov
Extracting Tree-Structured Representations of Trained Networks
Mark Craven, Jude W. Shavlik
NIPS 8, 1995
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2018/10/24, Jinman Zhao
Generalizing Word Embeddings using Bag of Subwords
Jinman Zhao, Sidharth Mudgal, Yingyu Liang
EMNLP, 2018
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2018/10/17, Finn Kuusisto
Learning Dexterous In-Hand Manipulation
OpenAI: Marcin Andrychowicz, Bowen Baker, Maciek Chociej, Rafal Jozefowicz, Bob McGrew, Jakub Pachocki, Arthur Petron, Matthias Plappert, Glenn Powell, Alex Ray, Jonas Schneider, Szymon Sidor, Josh Tobin, Peter Welinder, Lilian Weng, Wojciech Zaremba
arXiv, 2018
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2018/10/10, Collin Engstrom
Applying family analyses to electronic health records to facilitate genetic research
Xiayuan Huang, Robert C. Elston, Guilherme J. Rosa, John Mayer, Zhan Ye, Terrie Kitchner, Murray H. Brilliant, David Page, Scott J. Hebbring
Bioinformatics 34(4), 2018
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2018/10/03, Matthew Bernstein
Bayesian Inference for a Generative Model of Transcriptome Profiles from Single-Cell RNA Sequencing
Romain Lopez, Jeffrey Regier, Michael B. Cole, Michael I. Jordan, Nir Yosef
bioRXiv, 2018
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2018/09/26, Vishnu Lokhande
Learning One-Hidden-Layer Neural Networks with Landscape Design
Rong Ge, Jason D. Lee, Tengyu Ma
ICLR 6, 2018
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2018/09/26, Vishnu Lokhande
Identifying Generalization Properties in Neural Networks
Huan Wang, Nitish Shirish Keskar, Caiming Xiong, Richard Socher
arXiv, 2018
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2018/09/12, Jinman Zhao
code2vec: Learning Distributed Representations of Code
Uri Alon, Meital Zilberstein, Omer Levy, Eran Yahav
(to appear) POPL 46, 2019
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2018/09/12, Jinman Zhao
A General Path-Based Representation for Predicting Program Properties
Uri Alon, Meital Zilberstein, Omer Levy, Eran Yahav
PLDI 39, 2018
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2018/05/02, Felipe Gutierrez Barragan
Matrix capsules with EM routing
Geoffrey E. Hinton, Sara Sabour, Nicholas Frosst
ICLR 6, 2018
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2018/04/25, Finn Kuusisto
Hominin skeletal part abundances and claims of deliberate disposal of corpses in the Middle Pleistocene
Charles P. Egeland, Manuel Domínguez-Rodrigo, Travis Rayne Pickering, Colin G. Menter, Jason L. Heaton
PNAS 115(18), 2018
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2018/04/18, Ross Kleiman
Cost-Sensitive Multi-class Classification from Probability Estimates
Deirdre O'Brien, Maya Gupta, and Robert Gray
ICML 25, 2008
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2018/04/11, Jiefeng Chen
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Adrian Vladu
ICLR 6, 2018
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2018/04/04, Wei Zhang
RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism
Edward Choi, Mohammad Taha Bahadori, Jimeng Sun, Joshua Kulas, Andy Schuetz, Walter Stewart
NIPS 29, 2016
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2018/03/21, Nikhil Nakhate
SSD: Single Shot MultiBox Detector
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg
ECCV 14, 2016
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2018/03/07, Aubrey Barnard
Inference via low-dimensional couplings
Alessio Spantini, Daniele Bigoni, Youssef Marzouk
arXiv, 2017
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2018/02/28, Jinnian Zhang
PacGAN: The power of two samples in generative adversarial networks
Zinan Lin, Ashish Khetan, Giulia Fanti, Sewoong Oh
arXiv, 2018
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2018/02/21, Jinman Zhao
Enriching Word Vectors with Subword Information
Piotr Bojanowski, Edouard Grave, Armand Joulin, Tomas Mikolov
TACL 5, 2017
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2018/02/14, Matthew Bernstein
Semi-Supervised Prediction-Constrained Topic Models
Michael Hughes, Gabriel Hope, Leah Weiner, Thomas McCoy, Roy Perlis, Erik Sudderth, Finale Doshi-Velez
AISTATS 21, 2018
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2018/01/31, Xuezhou Zhang
Training Set Debugging Using Trusted Items
Xuezhou Zhang, Xiaojin Zhu, Stephen Wright
AAAI 32, 2018
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- 2017
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2017/12/13, Aubrey Barnard
Mastering the game of Go without human knowledge
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche, Thore Graepel, Demis Hassabis
Nature 550(7676), 2017
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2017/12/06, Sathya Ravi
Gradient Descent Only Converges to Minimizers
Jason D. Lee, Max Simchowitz, Michael I. Jordan, Benjamin Recht
COLT 29, 2016
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2017/12/06, Sathya Ravi
Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers
Jacob Steinhardt, Moses Charikar, Gregory Valiant
ITCS, 2018
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2017/11/29, Matthew Bernstein
Visualizing Data using t-SNE
Laurens van der Maaten, Geoffrey Hinton
JMLR 9, 2008
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2017/11/29, Matthew Bernstein
How to Use t-SNE Effectively
Martin Wattenberg, Fernanda Viégas, Ian Johnson
Distill, 2016
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2017/11/15, Ayon Sen
Understanding deep learning requires rethinking generalization
Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, Oriol Vinyals
ICLR 5, 2017
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2017/11/08, Sumeet Katariya
Improved Algorithms for Linear Stochastic Bandits
Yasin Abbasi-Yadkori, Dávid Pál, Csaba Szepesvári
NIPS 24, 2011
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2017/11/01, Ronak Mehta
Auto-Encoding Variational Bayes
Diederik P. Kingma, Max Welling
ICLR 2, 2014
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2017/10/25, Tyler Bradshaw
Machine Learning in Positron Emission Tomography
Tyler Bradshaw
info: bio
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2017/10/18, Vamsi Ithapu
Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
CVPR, 2016
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2017/10/18, Vamsi Ithapu
Densely Connected Convolutional Networks
Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger
CVPR, 2017
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2017/10/11, Felipe Gutierrez Barragan
Generative Adversarial Nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio
NIPS 27, 2014
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2017/10/04, Vamsi Ithapu
Going Deeper With Convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich
CVPR, 2015
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2017/09/27, Hyunwoo Kim
Scene Graph Generation by Iterative Message Passing
Danfei Xu, Yuke Zhu, Christopher B. Choy, Li Fei-Fei
CVPR, 2017
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2017/09/20, Ross Kleiman
Artificial Intelligence and Life in 2030
Peter Stone, Rodney Brooks, Erik Brynjolfsson, Ryan Calo, Oren Etzioni, Greg Hager, Julia Hirschberg, Shivaram Kalyanakrishnan, Ece Kamar, Sarit Kraus, Kevin Leyton-Brown, David Parkes, William Press, AnnaLee Saxenian, Julie Shah, Milind Tambe, Astro Teller
One Hundred Year Study on Artificial Intelligence, Stanford University, 2016
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2017/05/03, Charles Kuang
Trace Lasso: A Trace Norm Regularization for Correlated Designs
Edouard Grave, Guillaume R. Obozinski, Francis R. Bach
NIPS 24, 2011
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2017/04/26, Sid Kiblawi
Data Programming: Creating Large Training Sets, Quickly
Alexander J. Ratner, Christopher M. De Sa, Sen Wu, Daniel Selsam, Christopher Ré
NIPS 29, 2016
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2017/04/19, Ara Vartanian
Wasserstein Generative Adversarial Networks
Martin Arjovsky, Soumith Chintala, Léon Bottou
ICML 34, 2017
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2017/04/12, Vamsi Ithapu
Multiresolution Matrix Factorization
Risi Kondor, Nedelina Teneva, Vikas Garg
ICML 31, 2014
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2017/04/05, Finn Kuusisto
Inferring Regulatory Networks from Experimental Morphological Phenotypes: A Computational Method Reverse-Engineers Planarian Regeneration
Daniel Lobo, Michael Levin
PLOS Computational Biology 11(6), 2015
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2017/03/29, Hyunwoo Kim
A Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis
Daniela M. Witten, Robert Tibshirani, Trevor Hastie
Biostatistics 10(3), 2009
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2017/03/08, Akshay Sood
A Critical Review of Recurrent Neural Networks for Sequence Learning
Zachary C. Lipton, John Berkowitz, Charles Elkan
arXiv, 2015
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2017/03/01, Ronak Mehta
Sparse Inverse Covariance Estimation with the Graphical Lasso
Jerome Friedman, Trevor Hastie, Robert Tibshirani
Biostatistics 9(3), 2008
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2017/02/15, Aubrey Barnard
Finding Optimal Bayesian Networks
David Maxwell Chickering, Christopher Meek
UAI 18, 2002
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- 2011
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2011/04/27, Chris Hinrichs
Maximum Relative Margin and Data-Dependent Regularization
Pannagadatta K. Shivaswamy, Tony Jebara
JMLR 11(Feb), 2010
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2011/04/13, Andreas Vlachos
Learning Semantic Correspondences with Less Supervision
Percy Liang, Michael Jordan, Dan Klein
International Joint Conference on Natural Language Processing (IJCNLP) 4, 2009
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2011/03/30, Kwang-Sun Jun
Modeling Dyadic Data with Binary Latent Factors
Edward Meeds, Zoubin Ghahramani, Radford M. Neal, Sam T. Roweis
NIPS 19, 2006
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2011/03/02, Junming Sui
When is There a Representer Theorem? Vector Versus Matrix Regularizers
Andreas Argyriou, Charles A. Micchelli, Massimiliano Pontil
JMLR 10(Nov), 2009
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- 2010
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2010/12/08, Andreas Vlachos
A Multi-Pass Sieve for Coreference Resolution
Karthik Raghunathan, Heeyoung Lee, Sudarshan Rangarajan, Nate Chambers, Mihai Surdeanu, Dan Jurafsky, Christopher Manning
Empirical Methods in Natural Language Processing (EMNLP), 2010
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2010/11/10, Bryan Gibson
PAC Generalization Bounds for Co-training
Sanjoy Dasgupta, Michael L. Littman, David A. McAllester
NIPS 14, 2001
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2010/10/27, Debbie Chasman
Occam's Two Razors: The Sharp and the Blunt
Pedro Domingos
KDD 4, 1998
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2010/10/13, Suhail Shergill
Structured Ranking Learning using Cumulative Distribution Networks
Jim C. Huang, Brendan J. Frey
NIPS 21, 2008
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2010/09/29, Chris Hinrichs
Proximal Methods for Sparse Hierarchical Dictionary Learning
Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis Bach
ICML 27, 2010
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2010/04/07, Suhail Shergill
Bayesian Algorithms for Causal Data Mining
Subramani Mani, Constantin F. Aliferis, Alexander Statnikov
NIPS 2008 Workshop on Causality PMLR 6, 2010
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2010/03/24, Ameet Soni
Model Selection: Beyond the Bayesian/Frequentist Divide
Isabelle Guyon, Amir Saffari, Gideon Dror, Gavin Cawley
JMLR 11(Jan), 2010
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2010/03/10, Andrew Goldberg
Semi-Supervised Sequence Modeling with Syntactic Topic Models
Wei Li, Andrew McCallum
AAAI 20, 25
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2010/02/24, Kwang-Sun Jun
Dynamic Non-Parametric Mixture Models and The Recurrent Chinese Restaurant Process: with Applications to Evolutionary Clustering
Amr Ahmed, Eric Xing
SDM 8, 2008
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2010/02/10, Bryan Gibson
DUOL: A Double Updating Approach for Online Learning
Peilin Zhao, Steven C. Hoi, Rong Jin
NIPS 22, 2009
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- 2009
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2009/11/11, Ameet Soni
Supervised Learning from Multiple Experts: Whom to trust when everyone lies a bit
Vikas Raykar, Shipeng Yu, Linda Zhao, Anna Jerebko, Charles Florin, Gerardo Valadez, Luca Bogoni, Linda Moy
ICML 26, 2009
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2009/10/28, Kendrick Boyd
Learning Markov Logic Network Structure via Hypergraph Lifting
Stanley Kok, Pedro Domingos
ICML 26, 2009
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2009/10/14, Chris Hinrichs
Let the Kernel Figure it Out; Principled Learning of Pre-Processing for Kernel Classifiers
Peter Vincent Gehler, Sebastian Nowozin
CVPR, 2009
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2009/09/30, Debbie Chasman
Uncertainty Sampling and Transductive Experimental Design for Active Dual Supervision
Vikas Sindhwani, Prem Melville, Richard Lawrence
ICML 26, 2009
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2009/09/16, Junming Sui
On the Relation Between Multi-Instance Learning and Semi-Supervised Learning
Zhi-Hua Zhou, Jun-Ming Xu
ICML 24, 2007
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2009/04/22, Lisa Torrey
Learning Classifiers from Only Positive and Unlabeled Data
Charles Elkan, Keith Noto
KDD 14, 2008
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2009/04/08, Hidayath Ansari
Clustering with Local and Global Regularization
Fei Wang, Changshui Zhang, Tao Li
AAAI 22, 2007
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2009/04/01, David Andrzejewski
Training Products of Experts by Minimizing Contrastive Divergence
Geoffrey E. Hinton
Neural Computation 14(8), 2002
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2009/03/11, Chris Hinrichs
Robust Support Vector Machine Training via Convex Outlier Ablation
Linli Xu, Koby Crammer, Dale Schuurmans
AAAI 21, 2006
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2009/03/04, Nate Fillmore
The Tradeoffs of Large Scale Learning
Léon Bottou, Olivier Bousquet
NIPS 20, 2007
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2009/02/18, Andrew Goldberg
Large Scale Manifold Transduction
Michael Karlen, Jason Weston, Ayse Erkan, Ronan Collobert
ICML 25, 2008
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2009/02/04, Gautam Kunapuli
Model Selection via Bilevel Optimization
Kristin P. Bennett, Jing Hu, Gautam Kunapuli, Jong-Shi Pang
International Joint Conference on Neural Networks, 2006
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- 2008
-
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2008/11/24, Bess Berg
Boosted Bayesian network classifiers
Yushi Jing, Vladimir Pavlović, James M. Rehg
Machine Learning 73(2), 2008
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2008/11/10, Andrew Goldberg
A Unified Architecture for Natural Language Processing: Deep Neural Networks with Multitask Learning
Ronan Collobert, Jason Weston
ICML 25, 2008
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2008/10/13, Burr Settles
Learning from Labeled Features using Generalized Expectation Criteria
Gregory Druck, Gideon Mann, Andrew McCallum
SIGIR 31, 2008
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2008/09/29, David Andrzejewski
Beam Sampling for the Infinite Hidden Markov Model
Jurgen Van Gael, Yunus Saatci, Yee Whye Teh, and Zoubin Ghahramani
ICML 25, 2008
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2008/09/15, Eric Lantz
SVM Optimization: Inverse Dependence on Training Set Size
Shai Shalev-Shwartz, Nathan Srebro
ICML 25, 2008
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2008/05/07, Louis Oliphant
Predicting Good Probabilities with Supervised Learning
Alexandru Niculescu-Mizil, Rich Caruana
ICML 22, 2005
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2008/04/30, David Andrzejewski
Non-redundant clustering with conditional ensembles
David Gondek, Thomas Hofmann
KDD 11, 2005
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2008/04/09, Lisa Torrey
WebCrow: A Web-Based System for Crossword Solving
Marco Ernandes, Giovanni Angelini, Marco Gori
AAAI 20, 2005
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2008/03/26, Ted Wild
Online Bayes Point Machines
Edward Harrington, Ralf Herbrich, Jyrki Kivinen, John Platt, Robert C. Williamson
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PACKDD) 7, 2003
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2008/03/05, Sriraam Natarajan
Online Passive-Aggressive Algorithms
Shai Shalev-Shwartz, Koby Crammer, Ofer Dekel, Yoram Singer
NIPS 16, 2003
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2008/02/20, Ted Wild
Privacy-Preserving Classification of Vertically Partitioned Data via Random Kernels
Olvi L. Mangasarian, Edward W. Wild, Glenn M. Fung
TKDD 2(3), 2008
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2008/02/20, Ted Wild
Privacy-Preserving Classification of Horizontally Partitioned Data via Random Kernels
Olvi L. Mangasarian, Edward W. Wild
UW-Madison Data Mining Institute Technical Reports, 2007
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2008/02/13, Héctor Corrada Bravo
Colored Maximum Variance Unfolding
Le Song, Arthur Gretton, Karsten Borgwardt, Alex J. Smola
NIPS 20, 2007
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- 2007
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2007/12/10, Chris Hinrichs
Spatial Latent Dirichlet Allocation
Xiaogang Wang, Eric Grimson
NIPS 20, 2007
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2007/11/26, Louis Oliphant
Searching for Interacting Features
Zheng Zhao, Huan Liu
IJCAI 20, 2007
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2007/11/12, Lisa Torrey
Transfer Learning in Real-Time Strategy Games Using Hybrid CBR / RL
Manu Sharma, Michael Holmes, Juan Santamaria, Arya Irani, Charles Isbell, Ashwin Ram
IJCAI 20, 2007
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2007/11/05, David Andrzejewski
Nonparametric Bayes Pachinko Allocation
Wei Li, David Blei, Andrew McCallum
UAI 23, 2007
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2007/10/15, Andrew Goldberg
Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification
John Blitzer, Mark Dredze, Fernando Pereira
ACL 45, 2007
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2007/10/01, Héctor Corrada Bravo
Convex optimization techniques for fitting sparse Gaussian graphical models
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'Aspremont, Georges Natsoulis
ICML 23, 2006
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2007/09/17, Ted Wild
Model selection for support vector machines via uniform design
Chien-Ming Huang, Yuh-Jye Lee, Dennis K. J. Lin, Su-Yun Huang
Computational Statistics & Data Analysis 52(1), 2007
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2007/03/14, Ted Wild
Rule extraction from linear support vector machines
Glenn Fung, Sathyakama Sandilya, R. Bharat Rao
KDD 11, 2005
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2007/02/14, Lisa Torrey
Relating reinforcement learning performance to classification performance
John Langford, Bianca Zadrozny
ICML 22, 2005
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2007/01/31, Louis Oliphant
On Discriminative vs. Generative classifiers: A comparison of logistic regression and naive Bayes
Andrew Y. Ng, Michael I. Jordan
NIPS 14, 2001
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2007/01/31, Louis Oliphant
Classification with Hybrid Generative / Discriminative Models
Rajat Raina, Yirong Shen, Andrew McCallum, Andrew Y. Ng
NIPS 16, 2003
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- 2006
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2006/12/13, Ameet Soni
CONTRAfold: RNA secondary structure prediction without physics-based models
Chuong B. Do, Daniel A. Woods, Serafim Batzoglou
Bioinformatics 22(14), 2006
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2006/11/29, Jurgen Van Gael
Gaussian Processes for Machine Learning: Chapter 2: Regression
Carl Edward Rasmussen, Christopher K. I. Williams
MIT Press, 2006
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2006/11/15, Adam Smith
Multiple Alignment of Continuous Time Series
Jennifer Listgarten, Radford M. Neal, Sam T. Roweis, Andrew Emili
NIPS 17, 2004
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2006/11/01, Trevor Walker
Predictive State Representations: A New Theory for Modeling Dynamical Systems
Satinder Singh, Michael James, Matthew Rudary
UAI 20, 2004
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2006/10/18, Ted Wild
Choosing Between Two Learning Algorithms Based on Calibrated Tests
Remco R. Bouckaert
ICML 20, 2003
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2006/10/04, Louis Oliphant
A Taxonomy of Global Optimization Methods Based on Response Surfaces
Donald R. Jones
Journal of Global Optimization 21(4), 2001
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2006/09/25, Frank DiMaio
Hot Coupling: A Particle Approach to Inference and Normalization on Pairwise Undirected Graphs of Arbitrary Topology
Firas Hamze, Nando de Freitas
NIPS 18, 2005
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2006/08/30, Mark Goadrich
Cost curves: An improved method for visualizing classifier performance
Chris Drummond, Robert C. Holte
Machine Learning 65(1), 2006
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2006/08/16, Jurgen Van Gael
Topic Modeling: Beyond Bag-of-Words
Hanna M. Wallach
ICML 23, 2006
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2006/08/16, Jurgen Van Gael
Latent Dirichlet Allocation
David M. Blei, Andrew Y. Ng, and Michael I. Jordan
JMLR 3, 2003
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2006/07/19, David Andrzejewski
Hierarchical Topic Models and the Nested Chinese Restaurant Process
Thomas L. Griffiths, Michael I. Jordan, Joshua B. Tenenbaum, David M. Blei
NIPS 16, 2003
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2006/07/05, Ted Wild
Generalized Approximate Cross Validation for Support Vector Machines, or, Another Way to Look at Margin-Like Quantities
Grace Wahba, Yi Lin, Hao Zhang
Advances in Large Margin Classifiers, MIT Press, 2000
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2006/06/21, Lisa Torrey
Exploiting Task Relatedness for Multiple Task Learning
Shai Ben-DavidReba Schuller
COLT 16, 2003
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2006/06/07, Keith Noto
Evolving the Structure of Hidden Markov Models
Kyoung-Jae Won, Adam Prügel-Bennett, Anders Krogh
IEEE Transactions on Evolutionary Computation 10(1), 2006
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2006/05/24, Frank DiMaio
Generalized Belief Propagation
Jonathan S. Yedidia, William T. Freeman, Yair Weiss
NIPS 13, 2000
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2006/05/05, Keith Noto
Being Bayesian about Network Structure
Nir Friedman, Daphne Koller
UAI 16, 2000
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2006/04/21, Louis Oliphant
Probabilistic Reasoning with Hierarchically Structured Variables
Rita Sharma, David Poole
IJCAI 19, 2005
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2006/04/07, Trevor Walker
Recent Advances in Hierarchical Reinforcement Learning
Andrew G. Barto, Sridhar Mahadevan
Discrete Event Dynamic Systems 13(4), 2003
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2006/03/24, Jesse Davis
Combining Top-down and Bottom-up Techniques in Inductive Logic Programming
John M. Zelle, Raymond J. Mooney, Joshua B. Konvisser
ICML 11, 1994
author: pdf
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2006/03/24, Jesse Davis
Machine Invention of First-Order Predicates by Inverting Resolution
Stephen Muggleton, Wray Buntine
ICML 5, 1988
author: pdf
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2006/03/10, Pradheep Elango
A Survey of Kernels for Structured Data
Thomas Gärtner
SIGKDD Explorations 5(1), 2003
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2006/02/24
Learning to Map Sentences to Logical Form: Structured Classification with Probabilistic Categorial Grammars
Luke Zettlemoyer, Michael Collins
UAI 21, 2005
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2006/02/06, Ted Wild
Statistical Comparisons of Classifiers over Multiple Data Sets
Janez Demšar
JMLR 7, 2006
-
- 2005
-
-
2005/12/07, Ted Wild
Latent Dirichlet Allocation
David M. Blei, Andrew Y. Ng, and Michael I. Jordan
JMLR 3, 2003
-
2005/11/30, Héctor Corrada Bravo
Markov Logic Networks
Matthew Richardson, Pedro Domingos
Machine Learning 62(1-2), 2005
-
2005/11/09, Ted Wild
The Entire Regularization Path for the Support Vector Machine
Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu
NIPS 17, 2004
-
2005/10/26, Lisa Torrey
Relational Instance Based Regression for Relational Reinforcement Learning
Kurt Driessens, Jan Ramon
ICML 20, 2003
-
2005/10/12, Jerry Zhu
Graph Kernels by Spectral Transforms
Xiaojin Zhu, Jaz Kandola, John Lafferty, Zoubin Ghahramani
Semi-Supervised Learning, MIT Press, 2006
-
- 2003
-
-
2003/12/04, Beverly Seavy
Learning from Cluster Examples
Toshihiro Kamishima, Fumio Motoyoshi
Machine Learning 53(3), 2003
-
2003/11/20, Michael Shultz
Finding Motifs Using Random Projections
Jeremy Buhler, Martin Tompa
Journal of Computational Biology 9(2), 2002
-
2003/11/20, Michael Shultz
Genome-scale approaches to resolving incongruence in molecular phylogenies
Antonis Rokas, Barry L. Williams, Nicole King, Sean B. Carroll
Nature 425(6960), 2003
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2003/11/06, Louis Oliphant
Advantages of Decision Lists and Implicit Negatives in Inductive Logic Programming
Mary Elaine Califf, Raymond J. Mooney
New Generation Computing 16(3), 1998
-
2003/10/30, Michael Waddell
Human-Machine Collaborative Planning
James Allen, George Ferguson
International NASA Workshop on Planning and Scheduling for Space 3, 2002
-
2003/10/16, Mark Goadrich
Scaling Up ILP to Large Examples: Results on Link Discovery for Counter-Terrorism
Lappoon R. Tang, Raymond J. Mooney, Prem Melville
KDD Workshop on Multi-Relational Data Mining (MRDM), 2003
-
2003/10/02, Soumya Ray
Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm
Nick Littlestone
Machine Learning 2(4), 1988
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- 2002
-
-
2002/12/06, Glenn Fung
Transductive Inference for Text Classification using Support Vector Machines
Thorsten Joachims
ICML 16, 1999
-
2002/11/22, Michael Molla
Genes, Themes, and Microarrays: Using Information Retrieval for Large-Scale Gene Analysis
Hagit Shatkay, Stephen Edwards, W. John Wilbur, Mark Boguski
ISMB 8, 2000
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2002/11/08, Sean McIlwain
A Sequence-Profile-Based HMM for Predicting and Discriminating β Barrel Membrane Proteins
Pier Luigi Martelli, Piero Fariselli, Anders Krogh, Rita Casadio
Bioinformatics 18, 2002
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2002/10/25, Frank DiMaio
A Study of Two Probabilistic Methods for Searching Large Spaces with ILP
Ashwin Srinivasan
1999
-
2002/10/11, Mark Rich
Boosted Wrapper Induction
Dayne Freitag, Nicholas Kushmerick
AAAI 17, 2000
-
2002/09/27, Louis Oliphant
Data Perturbation for Escaping Local Maxima in Learning
Gal Elidan, Matan Ninio, Nir Friedman, Dale Shuurmans
AAAI 18, 2002
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2002/09/13, Soumya Ray
Boosting the Margin: A New Explanation for the Effectiveness of Voting Methods
Robert E. Shapire, Yoav Freund, Peter Bartlett, Wee Sun Lee
Annals of Statistics 26, 1998
-
2002/04/26, Joe Bockhorst
Exploiting Generative Models in Discriminative Classifiers
Tommi Jaakkola, David Haussler
NIPS 11, 1998
-
2002/04/26, Joe Bockhorst
A Discriminative Framework for Detecting Remote Protein Homologies
Tommi Jaakkola, Mark Diekhans, David Haussler
Journal of Computational Biology 7, 2000
venue: meta
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2002/04/12, Darryl Roy
The Ant Colony Optimization Metaheuristic: Algorithms, Applications, and Advances
Marco Dorigo, Thomas Stützle
Handbook of Metaheuristics 57, International Series in Operations Research, 2003
venue: meta
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2002/03/15, Glenn Fung
A Tutorial on Support Vector Machines for Pattern Recognition
Christopher J. C. Burges
Data Mining and Knowledge Discovery 2, 1998
venue: meta
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2002/03/01, Irene Ong
Feature Construction with Version Spaces for Biochemical Applications
Stefan Kramer, Luc De Raedt
ICML 18, 2001
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2002/03/01, Irene Ong
Feature Selection for High-Dimensional Genomic Microarray Data
Eric P. Xing, Michael I. Jordan, Richard M. Karp
ICML 18, 2001
venue: meta
-
2002/02/15, Mark Rich
Stochastic Logic Programs
Stephen Muggleton
Advances in Inductive Logic Programming, IOS Press, 1996
-
2002/02/15, Mark Rich
Learning Stochastic Logic Programs
Stephen Muggleton
AAAI Technical Report WS-00-06, 2000
-
2002/02/01, Marios Skounakis
Global Training of Document Processing Systems using Graph Transformer Networks
Léon Bottou, Yoshua Bengio, Yann Le Cun
CVPR, 1997
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