Timezone: »
With the advent of the Internet it is now possible to collect hundreds of millions of images. These images come with varying degrees of label information. "Clean labels'' can be manually obtained on a small fraction, "noisy labels'' may be extracted automatically from surrounding text, while for most images there are no labels at all. Semi-supervised learning is a principled framework for combining these different label sources. However, it scales polynomially with the number of images, making it impractical for use on gigantic collections with hundreds of millions of images and thousands of classes. In this paper we show how to utilize recent results in machine learning to obtain highly efficient approximations for semi-supervised learning that are linear in the number of images. Specifically, we use the convergence of the eigenvectors of the normalized graph Laplacian to eigenfunctions of weighted Laplace-Beltrami operators. We combine this with a label sharing framework obtained from Wordnet to propagate label information to classes lacking manual annotations. Our algorithm enables us to apply semi-supervised learning to a database of 80 million images with 74 thousand classes.
Author Information
Rob Fergus (DeepMind / NYU)
Rob Fergus is an Associate Professor of Computer Science at the Courant Institute of Mathematical Sciences, New York University. He received a Masters in Electrical Engineering with Prof. Pietro Perona at Caltech, before completing a PhD with Prof. Andrew Zisserman at the University of Oxford in 2005. Before coming to NYU, he spent two years as a post-doc in the Computer Science and Artificial Intelligence Lab (CSAIL) at MIT, working with Prof. William Freeman. He has received several awards including a CVPR best paper prize, a Sloan Fellowship & NSF Career award and the IEEE Longuet-Higgins prize.
Yair Weiss (Hebrew University)
Yair Weiss is an Associate Professor at the Hebrew University School of Computer Science and Engineering. He received his Ph.D. from MIT working with Ted Adelson on motion analysis and did postdoctoral work at UC Berkeley. Since 2005 he has been a fellow of the Canadian Institute for Advanced Research. With his students and colleagues he has co-authored award winning papers in NIPS (2002),ECCV (2006), UAI (2008) and CVPR (2009).
Antonio Torralba (Massachusetts Institute of Technology)
Related Events (a corresponding poster, oral, or spotlight)
-
2009 Poster: Semi-Supervised Learning in Gigantic Image Collections »
Wed Dec 9th 03:00 -- 07:59 AM Room None
More from the Same Authors
-
2020 Poster: Causal Discovery in Physical Systems from Videos »
Yunzhu Li · Antonio Torralba · Anima Anandkumar · Dieter Fox · Animesh Garg -
2018 Poster: Visual Object Networks: Image Generation with Disentangled 3D Representations »
Jun-Yan Zhu · Zhoutong Zhang · Chengkai Zhang · Jiajun Wu · Antonio Torralba · Josh Tenenbaum · Bill Freeman -
2018 Poster: On GANs and GMMs »
Eitan Richardson · Yair Weiss -
2018 Spotlight: On GANs and GMMs »
Eitan Richardson · Yair Weiss -
2016 Poster: Unsupervised Learning of Spoken Language with Visual Context »
David Harwath · Antonio Torralba · James Glass -
2016 Poster: Learning Multiagent Communication with Backpropagation »
Sainbayar Sukhbaatar · arthur szlam · Rob Fergus -
2015 Poster: The Return of the Gating Network: Combining Generative Models and Discriminative Training in Natural Image Priors »
Dan Rosenbaum · Yair Weiss -
2015 Spotlight: The Return of the Gating Network: Combining Generative Models and Discriminative Training in Natural Image Priors »
Dan Rosenbaum · Yair Weiss -
2014 Poster: Depth Map Prediction from a Single Image using a Multi-Scale Deep Network »
David Eigen · Christian Puhrsch · Rob Fergus -
2014 Poster: Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation »
Emily Denton · Wojciech Zaremba · Joan Bruna · Yann LeCun · Rob Fergus -
2014 Spotlight: Depth Map Prediction from a Single Image using a Multi-Scale Deep Network »
David Eigen · Christian Puhrsch · Rob Fergus -
2014 Poster: Learning Deep Features for Scene Recognition using Places Database »
Bolei Zhou · Agata Lapedriza · Jianxiong Xiao · Antonio Torralba · Aude Oliva -
2014 Poster: Learning to Discover Efficient Mathematical Identities »
Wojciech Zaremba · Karol Kurach · Rob Fergus -
2014 Spotlight: Learning Deep Features for Scene Recognition using Places Database »
Bolei Zhou · Agata Lapedriza · Jianxiong Xiao · Antonio Torralba · Aude Oliva -
2014 Spotlight: Learning to Discover Efficient Mathematical Identities »
Wojciech Zaremba · Karol Kurach · Rob Fergus -
2013 Poster: Learning the Local Statistics of Optical Flow »
Dan Rosenbaum · Daniel Zoran · Yair Weiss -
2013 Tutorial: Deep Learning for Computer Vision »
Rob Fergus -
2012 Poster: Natural Images, Gaussian Mixtures and Dead Leaves »
Daniel Zoran · Yair Weiss -
2012 Poster: Modeling the Forgetting Process using Image Regions »
Aditya Khosla · Jianxiong Xiao · Antonio Torralba · Aude Oliva -
2012 Poster: Learning about Canonical Views from Internet Image Collections »
Elad Mezuman · Yair Weiss -
2012 Poster: Localizing 3D cuboids in single-view images »
Jianxiong Xiao · Bryan C Russell · Antonio Torralba -
2011 Workshop: Machine Learning meets Computational Photography »
Michael Hirsch · Stefan Harmeling · Rob Fergus · Peyman Milanfar -
2011 Poster: Learning to Learn with Compound HD Models »
Russ Salakhutdinov · Josh Tenenbaum · Antonio Torralba -
2011 Poster: Understanding the Intrinsic Memorability of Images »
Phillip Isola · Devi Parikh · Antonio Torralba · Aude Oliva -
2011 Spotlight: Learning to Learn with Compound HD Models »
Russ Salakhutdinov · Josh Tenenbaum · Antonio Torralba -
2011 Poster: Facial Expression Transfer with Input-Output Temporal Restricted Boltzmann Machines »
Matthew D Zeiler · Graham Taylor · Leonid Sigal · Iain Matthews · Rob Fergus -
2011 Poster: Transfer Learning by Borrowing Examples »
Joseph Lim · Russ Salakhutdinov · Antonio Torralba -
2011 Session: Spotlight Session 1 »
Rob Fergus -
2010 Session: Oral Session 17 »
Rob Fergus -
2010 Poster: Pose-Sensitive Embedding by Nonlinear NCA Regression »
Graham Taylor · Rob Fergus · George Williams · Ian Spiro · Christoph Bregler -
2009 Poster: Unsupervised Detection of Regions of Interest Using Iterative Link Analysis »
Gunhee Kim · Antonio Torralba -
2009 Poster: Fast Image Deconvolution using Hyper-Laplacian Priors »
Dilip Krishnan · Rob Fergus -
2009 Spotlight: Fast Image Deconvolution using Hyper-Laplacian Priors »
Dilip Krishnan · Rob Fergus -
2009 Invited Talk: Learning and Inference in Low-Level Vision »
Yair Weiss -
2009 Session: Oral session 7: Vision and Inference »
Antonio Torralba -
2009 Poster: Nonparametric Bayesian Texture Learning and Synthesis »
Leo Zhu · Yuanhao Chen · Bill Freeman · Antonio Torralba -
2009 Poster: The "tree-dependent components" of natural scenes are edge filters »
Daniel Zoran · Yair Weiss -
2009 Tutorial: Understanding Visual Scenes »
Antonio Torralba -
2008 Poster: Spectral Hashing »
Yair Weiss · Antonio Torralba · Rob Fergus -
2007 Spotlight: Object Recognition by Scene Alignment »
Bryan C Russell · Antonio Torralba · Ce Liu · Rob Fergus · William Freeman -
2007 Poster: Object Recognition by Scene Alignment »
Bryan C Russell · Antonio Torralba · Ce Liu · Rob Fergus · William Freeman