Realistic Evaluation of Deep Semi-Supervised Learning Algorithms - PowerPoint PPT Presentation

Mar 13, 2023 •42 likes •212 views

Realistic Evaluation of Deep Semi-Supervised Learning Algorithms Avital Oliver* Augustus Odena* Colin Raffel* Ekin Dogus Cubuk Ian Goodfellow vs. Error rates for our reimplementation of different semi-supervised learning methods. Reported

Realistic Evaluation of Deep Semi-Supervised Learning Algorithms Avital Oliver* Augustus Odena* Colin Raffel* Ekin Dogus Cubuk Ian Goodfellow
vs.
Error rates for our reimplementation of different semi-supervised learning methods.
Reported change in error rate from fully-supervised (no unlabeled data) to semi-supervised learning.
Comparison of error rates for the best-performing semi-supervised learning method and transfer learning.
Paper: https://arxiv.org/abs/1804.09170 Code: https://github.com/brain-research/realistic-ssl-evaluation/ Poster: Today, 10:45 AM - 12:45 PM, Room 210 & 230 AB #95

Recommend

Keepin It Real: Semi-Supervised Learning with Realistic Tuning Andrew B. Goldberg Xiaojin

Keepin It Real: Semi-Supervised Learning with Realistic Tuning Andrew B. Goldberg Xiaojin Zhu goldberg@cs.wisc.edu jerryzhu@cs.wisc.edu Computer Sciences Department University of Wisconsin-Madison Gap between Semi-Supervised Learning

1.26k views • 96 slides

CS330 Paper Presentation: October 16th, 2019 Supervised Classification Semi-Supervised

CS330 Paper Presentation: October 16th, 2019 Supervised Classification Semi-Supervised Classification: More realistic dataset Labelled Unlabelled Semi-Supervised Classification Most biologically plausible learning regime A familiar

650 views • 46 slides

Semi-Supervised Learning Maria-Florina Balcan 03/30/2015 Readings: Semi-Supervised Learning.

Semi-Supervised Learning Maria-Florina Balcan 03/30/2015 Readings: Semi-Supervised Learning. Encyclopedia of Machine Learning. Jerry Zhu, 2010 Combining Labeled and Unlabeled Data with Co- Training. Avrim Blum, Tom Mitchell. COLT

953 views • 45 slides

Semi-supervised Learning with Deep Generative Models Diedrik P. Kingma, Danilo J. Rezende, Shakir

Semi-supervised Learning with Deep Generative Models Diedrik P. Kingma, Danilo J. Rezende, Shakir Mohamed, Max Welling What is Deep Learning very good at? Classifying highly structured data -ImageNet -Part of Speech Tagging -MNIST

195 views • 18 slides

Author Identification Using Semi-supervised Learning Ioannis Kourtis and Efstathios Stamatatos

Author Identification Using Semi-supervised Learning Ioannis Kourtis and Efstathios Stamatatos University of the Aegean Outline Introduction The proposed method Common n-grams SVM Semi-supervised learning Evaluation

533 views • 17 slides

Semi-Supervised Learning Jia-Bin Huang Virginia Tech Spring 2019 ECE-5424G / CS-5824

Semi-Supervised Learning Jia-Bin Huang Virginia Tech Spring 2019 ECE-5424G / CS-5824 Administrative Advanced Topics Semi-supervised learning Ensemble learning Generative models Sequence prediction models Deep reinforcement

345 views • 18 slides

Unsupervised and Semi-supervised Learning of Structure Graham Neubig Site

CS11-747 Neural Networks for NLP Unsupervised and Semi-supervised Learning of Structure Graham Neubig Site https://phontron.com/class/nn4nlp2020/ Supervised, Unsupervised, Semi-supervised Most models handled here are supervised learning

580 views • 39 slides

Unsupervised and Semi-supervised Learning of Structure Graham Neubig Site

CS11-747 Neural Networks for NLP Unsupervised and Semi-supervised Learning of Structure Graham Neubig Site https://phontron.com/class/nn4nlp2018/ Supervised, Unsupervised, Semi-supervised Most models handled here are supervised learning

670 views • 32 slides

Transfer learning and domain adaptation Semi-supervised and transfer learning Myth : you cant

Day 2 Lecture 5 Transfer learning and domain adaptation Semi-supervised and transfer learning Myth : you cant do deep learning unless you have a million labelled examples for your problem. Reality You can learn useful representations

183 views • 15 slides

5 Semi-Supervised Learning BVM Tutorial: Advanced Deep Learning Methods David Zimmerer, Division

5 Semi-Supervised Learning BVM Tutorial: Advanced Deep Learning Methods David Zimmerer, Division of Medical Image Computing Author Division Semi-Supervised Learning 02.11.16 | Page2 2 | David Zimmerer, Division of Medical Image Computing

1.04k views • 87 slides

NEURAL RENDERING MODEL (NRM): JOINT GENERATION AND PREDICTION FOR SEMI-SUPERVISED LEARNING Tan

NEURAL RENDERING MODEL (NRM): JOINT GENERATION AND PREDICTION FOR SEMI-SUPERVISED LEARNING Tan Nguyen Joint work with Nhat Ho, Ankit B. Patel, Anima Anandkumar , Michael I. Jordan, and Richard G. Baraniuk Deep Learning The Current

621 views • 25 slides

Mutual information deep regularization for semi- supervised segmentation J. Peng, M. Pedersoli,

MIDL 2020 presentation Mutual information deep regularization for semi- supervised segmentation J. Peng, M. Pedersoli, C. Desrosiers Outline We proposed a semi-supervised segmentation method for medical image regularized by Mutual Information

256 views • 13 slides

Tangent-Normal Adversarial Regularization for Semi-Supervised Learning Bing Yu , Jingfeng Wu

Tangent-Normal Adversarial Regularization for Semi-Supervised Learning Bing Yu , Jingfeng Wu , Jinwen Ma, Zhanxing Zhu Peking University Beijing Institute of Big Data Research June, 2019 Semi-supervised learning (SSL) Suppose we

201 views • 18 slides

Support Vector Machines (SVMs). Semi-Supervised Learning. Semi-Supervised SVMs.

Support Vector Machines (SVMs). Semi-Supervised Learning. Semi-Supervised SVMs. Maria-Florina Balcan 03/25/2015 Support Vector Machines (SVMs). One of the most theoretically well motivated and practically most e ff ective

792 views • 40 slides

Parallelizing Semi- ReDAS Lab Supervised Learning Algorithms with MapReduce Nick Gauthier

Parallelizing Semi- ReDAS Lab Supervised Learning Algorithms with MapReduce Nick Gauthier Advisor: Dr. Rakesh Verma COMPUTER SCIENCE Motivation Semi-supervised learning(SSL) algorithms are slow when working with large-scale data.

801 views • 14 slides

Particles Competition and Cooperation in Networks for Semi-Supervised Learning Fabricio Breve

Particles Competition and Cooperation in Networks for Semi-Supervised Learning Fabricio Breve Department of Electrical & Computer Engineering University of Alberta Seminar - October 09, 2009 Contents Introduction Semi-Supervised

863 views • 40 slides

Regularizing objective functionals in semi-supervised learning Dejan Slep cev Carnegie Mellon

Regularizing objective functionals in semi-supervised learning Dejan Slep cev Carnegie Mellon University February 9, 2018. . 1 / 47 References S.,Thorpe, Analysis of p-Laplacian regularization in semi-supervised learning , arxiv

742 views • 48 slides

Classification Semi-supervised learning based on network Speakers: Hanwen Wang, Xinxin Huang, and

Classification Semi-supervised learning based on network Speakers: Hanwen Wang, Xinxin Huang, and Zeyu Li CS 249-2 2017 Winter Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions Xiaojin Zhu, Zoubin Ghahramani, John Lafferty

625 views • 45 slides

Link prediction in graph construction for supervised and semi-supervised learning Lilian Berton,

Link prediction in graph construction for supervised and semi-supervised learning Lilian Berton, Jorge Valverde-Rebaza and Alneu de Andrade Lopes Laboratory of Computational Intelligence (LABIC) University of S ao Paulo (USP) Brazil July

398 views • 20 slides

10701 Semi supervised learning Can Unlabeled Data improve supervised learning? Important

10701 Semi supervised learning Can Unlabeled Data improve supervised learning? Important question! In many cases, unlabeled data is plentiful, labeled data expensive Image classification (x=images from the web, y=image type) Text

886 views • 37 slides

Margin-based Semi-supervised Learning Using Apollonius circle MONA EMADI AND JAFAR TANHA T TC S

Margin-based Semi-supervised Learning Using Apollonius circle MONA EMADI AND JAFAR TANHA T TC S 2 0 2 0 Semi-supervised learning Training data Supervised All labeled data Model learning Some labeled data Semi-supervised Model learning

749 views • 23 slides

Deep Generative Models for Clustering: A Semi-supervised and Unsupervised Approach Jhosimar

Deep Generative Models for Clustering: A Semi-supervised and Unsupervised Approach Jhosimar George Arias Figueroa Advisor: Gerberth Ad n Ram rez Rivera Masters Thesis Defense February 19, 2018 Motivation Huge amount of unlabeled

1.26k views • 125 slides

Semi-Supervised Learning Barnabas Poczos Slides Courtesy: Jerry Zhu, Aarti Singh Supervised

Semi-Supervised Learning Barnabas Poczos Slides Courtesy: Jerry Zhu, Aarti Singh Supervised Learning Feature Space Label Space Goal: Optimal predictor (Bayes Rule) depends on unknown P XY , so instead learn a good prediction rule from training

1.03k views • 36 slides

Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning Qimai Li, Zhichao

Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning Qimai Li, Zhichao Han, Xiao-Ming Wu Department of Computing The Hong Kong Polytechnic University Supervised Learning Tons of labeled data A good model 2 Image

880 views • 13 slides