MLOSS 2019

10 papers

AffectiveTweets: A Weka Package for Analyzing Affect in Tweets Felipe Bravo-Marquez, Eibe Frank, Bernhard Pfahringer, Saif M. Mohammad

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iNNvestigate Neural Networks! Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele, Kristof T. Schütt, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller, Sven Dähne, Pieter-Jan Kindermans

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ORCA: A Matlab/Octave Toolbox for Ordinal Regression Javier Sánchez-Monedero, Pedro A. Gutiérrez, María Pérez-Ortiz

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Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao

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PyOD: A Python Toolbox for Scalable Outlier Detection Yue Zhao, Zain Nasrullah, Zheng Li

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Pyro: Deep Universal Probabilistic Programming Eli Bingham, Jonathan P. Chen, Martin Jankowiak, Fritz Obermeyer, Neeraj Pradhan, Theofanis Karaletsos, Rohit Singh, Paul Szerlip, Paul Horsfall, Noah D. Goodman

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Scikit-Multilearn: A Python Library for Multi-Label Classification Piotr Szymański, Tomasz Kajdanowicz

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SMART: An Open Source Data Labeling Platform for Supervised Learning Rob Chew, Michael Wenger, Caroline Kery, Jason Nance, Keith Richards, Emily Hadley, Peter Baumgartner

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Spark-Crowd: A Spark Package for Learning from Crowdsourced Big Data Enrique G. Rodrigo, Juan A. Aledo, José A. Gámez

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TensorLy: Tensor Learning in Python Jean Kossaifi, Yannis Panagakis, Anima Anandkumar, Maja Pantic

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