1![Ranking Subreddits by Classifier Indistinguishability in the Reddit Corpus Faisal Alquaddoomi Deborah Estrin Ranking Subreddits by Classifier Indistinguishability in the Reddit Corpus Faisal Alquaddoomi Deborah Estrin](https://www.pdfsearch.io/img/b1455fdae4805229241329cebdcb71a2.jpg) | Add to Reading ListSource URL: destrin.smalldata.ioLanguage: English - Date: 2018-10-22 18:10:48
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2![Ranking Subreddits by Classifier Indistinguishability in the Reddit Corpus Faisal Alquaddoomi Deborah Estrin Ranking Subreddits by Classifier Indistinguishability in the Reddit Corpus Faisal Alquaddoomi Deborah Estrin](https://www.pdfsearch.io/img/44b93a5072c8226fb00edc476c71bf91.jpg) | Add to Reading ListSource URL: smalldata.ioLanguage: English - Date: 2018-10-24 23:11:34
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3![Calibrating the Classifier: Siamese Neural Network Architecture for End-to-End Arousal Recognition from ECG Andrea Patan`e and Marta Kwiatkowska Department of Computer Science, University of Oxford Calibrating the Classifier: Siamese Neural Network Architecture for End-to-End Arousal Recognition from ECG Andrea Patan`e and Marta Kwiatkowska Department of Computer Science, University of Oxford](https://www.pdfsearch.io/img/aa1fff0eaf0c4af9296b8b6f106d5e2f.jpg) | Add to Reading ListSource URL: qav.comlab.ox.ac.ukLanguage: English - Date: 2018-07-24 04:40:17
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4![Základní informace Jméno projektu Open Data Linker and Classifier Zkratka Základní informace Jméno projektu Open Data Linker and Classifier Zkratka](https://www.pdfsearch.io/img/53382419e9abf99d16f7d1262aba646c.jpg) | Add to Reading ListSource URL: www.ksi.mff.cuni.czLanguage: English - Date: 2016-06-17 11:20:37
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5![Facebook Reaction-Based Emotion Classifier as Cue for Sarcasm Detection Facebook Reaction-Based Emotion Classifier as Cue for Sarcasm Detection](https://www.pdfsearch.io/img/4d597016bf2de8aaa0cf7a971b106f4c.jpg) | Add to Reading ListSource URL: tigpsnhcc.iis.sinica.edu.twLanguage: English - Date: 2017-12-07 03:10:28
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6![Binary classification Learning by classifier combination: boosting n Binary classification Learning by classifier combination: boosting n](https://www.pdfsearch.io/img/62d425edb6c2bc157933181348787ed8.jpg) | Add to Reading ListSource URL: ahistace.chez-alice.frLanguage: English - Date: 2012-01-31 14:42:44
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7![Neurocomputing, vol.80, pp, Importance-Weighted Least-Squares Probabilistic Classifier for Covariate Shift Adaptation with Neurocomputing, vol.80, pp, Importance-Weighted Least-Squares Probabilistic Classifier for Covariate Shift Adaptation with](https://www.pdfsearch.io/img/8d6aa55e48aefd966505892c48a8f71f.jpg) | Add to Reading ListSource URL: www.ms.k.u-tokyo.ac.jpLanguage: English - Date: 2011-12-30 09:22:13
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8![Int J Comput Vis:203–215 DOIs11263z Making a Shallow Network Deep: Conversion of a Boosting Classifier into a Decision Tree by Boolean Optimisation Tae-Kyun Kim · Ignas Budvytis · Robert Int J Comput Vis:203–215 DOIs11263z Making a Shallow Network Deep: Conversion of a Boosting Classifier into a Decision Tree by Boolean Optimisation Tae-Kyun Kim · Ignas Budvytis · Robert](https://www.pdfsearch.io/img/79ef6a6ff00b80267e9afe9425c37b0e.jpg) | Add to Reading ListSource URL: mi.eng.cam.ac.ukLanguage: English - Date: 2018-03-13 12:50:13
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9![ECE 901 Lecture 12: Complexity Regularization and the Squared Loss R. NowakIn the previous lectures we made use of the Chernoff/Hoeffding bounds for our analysis of classifier errors. Hoeffding’s inequality ECE 901 Lecture 12: Complexity Regularization and the Squared Loss R. NowakIn the previous lectures we made use of the Chernoff/Hoeffding bounds for our analysis of classifier errors. Hoeffding’s inequality](https://www.pdfsearch.io/img/62359db165796c033631e40544b9bc5a.jpg) | Add to Reading ListSource URL: nowak.ece.wisc.eduLanguage: English - Date: 2012-03-09 07:34:15
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10![ECE 901 Lecture 5: Plug-in Rules and the Histogram Classifier R. NowakWe return to the topic of classification, and we assume an input (feature) space X and a binary output (label) space Y = {0, 1}. Recall tha ECE 901 Lecture 5: Plug-in Rules and the Histogram Classifier R. NowakWe return to the topic of classification, and we assume an input (feature) space X and a binary output (label) space Y = {0, 1}. Recall tha](https://www.pdfsearch.io/img/3e2dfe065ac90f59da04571a21cea57a.jpg) | Add to Reading ListSource URL: nowak.ece.wisc.eduLanguage: English - Date: 2012-03-09 07:34:15
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