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Weakly Supervised Learning of Mid-Level Features with Beta-Bernoulli Process Restricted Boltzmann Machines

Roni Mittelman, Honglak Lee, Benjamin Kuipers, Silvio Savarese
2013 2013 IEEE Conference on Computer Vision and Pattern Recognition  
We develop a novel extension of the restricted Boltzmann machine (RBM) by incorporating a Beta-Bernoulli process factor potential for hidden units.  ...  In order to address this issue, we propose a weakly supervised approach to learn mid-level features, where only class-level supervision is provided during training.  ...  Acknowledgements We acknowledge the support of the NSF Grant CPS-0931474 and a Google Faculty Research Award.  ... 
doi:10.1109/cvpr.2013.68 dblp:conf/cvpr/MittelmanLKS13 fatcat:3enwsfl7jzadhn7c4lmw4rsoay

Contour Detection-Based Discovery of Mid-Level Discriminative Patches for Scene Classification

Jinfu Yang, Jizhao Zhang, Guanghui Wang, Mingai Li
2016 International Journal of Advanced Robotic Systems  
First, a sketch tokens-based contour detection scheme is proposed to initialize seed blocks for learning mid-level patches and the patches with more contour pixels are selected as seed blocks.  ...  Feature extraction and representation is a key step in scene classification. In this paper, a contour detection-based midlevel features learning method is proposed for scene classification.  ...  They developed a novel extension of the restricted Boltzmann machine (RBM) by incorporating a Beta-Bernoulli process factor potential into hidden units.  ... 
doi:10.5772/62266 fatcat:44w6y5iq5zfkhfa2z5mbot65im

A high-bias, low-variance introduction to Machine Learning for physicists [article]

Pankaj Mehta, Marin Bukov, Ching-Hao Wang, Alexandre G.R. Day, Clint Richardson, Charles K. Fisher, David J. Schwab
2019 arXiv   pre-print
Topics covered in the review include ensemble models, deep learning and neural networks, clustering and data visualization, energy-based models (including MaxEnt models and Restricted Boltzmann Machines  ...  We conclude with an extended outlook discussing possible uses of machine learning for furthering our understanding of the physical world as well as open problems in ML where physicists may be able to contribute  ...  Restricted Boltzmann Machines (RBMs) A Restricted Boltzmann Machine (RBM) is an energybased model with both visible and hidden units where the Boltzmann Machine (RBM) consists of visible units vi and hidden  ... 
arXiv:1803.08823v2 fatcat:vmtp62jyvjfxhpidpdcozfnza4

CORPORATE CONTRIBUTORS

1988 The Hastings center report  
We have recently developed models in which supervised learning takes place at the level of neurons, rather than synapses, through modulation of their response properties.  ...  On this dataset, various linear separating hyperplane algorithms obtained from machine learning, Support Vector Machines, Relevance Vector Machines, mean-of-class prototype learners and K-means clustering  ...  Participant List Computers, E-mail, World Wide Web Grace Auditorium Upper level: E-mail only; Lower level: Word processing and printing.  ... 
doi:10.1002/j.1552-146x.1988.tb03932.x fatcat:bkotcyah2ngbfdk4kbx3xnf5v4

EMG-based Simultaneous and Proportional Estimation of Wrist Kinematics and its Application in Intuitive Myoelectric Control for Unilateral transradial Amputees

Farina Dario
2011 Frontiers in Computational Neuroscience  
Acknowledgements Tuesday, Oct 4 -Data Analyis and Machine Learning Acknowledgements This work was funded through a grant from the German Ministry of Education and Research (BMBF, 01GQ1003B).  ...  Acknowledgements This work was funded by the BFNT-B3 and by the SFB780 [T 62] Model-invariant features of correlations in recurrent networks Moritz Helias 1* , Dmytro Grytskyy 1 , Tom Tetzlaff 1 and  ...  Our approach is to learn to integrate by extracting the underlying causes from the data, via density estimation in a restricted Boltzmann machine (RBM).  ... 
doi:10.3389/conf.fncom.2011.53.00081 fatcat:nkq5wesfpbcjnikbxqh3v3gtqi

Finding Structure in Text, Genome and Other Symbolic Sequences [article]

Ted Dunning
2012 arXiv   pre-print
Generically, these methods allow detection of a difference in the frequency of a single feature, the detection of a difference between the frequencies of an ensemble of features and the attribution of  ...  Since these methods are abstract in nature, they can be applied in novel situations with relative ease.  ...  Evaluations of supervised learning systems are normally done by providing a set of known correct examples. This set is divided into two portions.  ... 
arXiv:1207.1847v1 fatcat:atx6naydzjbzrcrfrbnyn4uqcu

Recognizing film aesthetics, spectators' affect and aesthetic emotions from multimodal signals

Michal Muszynski, Thierry Pun, Guillaume Chanel
2018
subjects for investigation and new aspects of familiar subjects."  ...  The bringing together of theory and practice leads to the most favourable results; not only does practice benefit, but the sciences themselves develop under the influence of practice, which reveals new  ...  I am grateful for being able to collaborate with Dr. Leimin Tian. I have certainly learned from you a lot.  ... 
doi:10.13097/archive-ouverte/unige:114609 fatcat:6kmitp7ao5dghhznzhcjffgzka

Dynamics and partitioning of single CLB2 mRNA and its role in cell cycle progression

Severin Ehret, Humboldt-Universität Zu Berlin
2021
The eukaryotic cell cycle is regulated on all levels of gene expression. Genetic screens and functional studies of the involved proteins have shaped our understanding of this fundamental process.  ...  Further, the observation of single CLB2 mRNA partitioning throughout the cell cycle with the use of lattice light sheet microscopy suggested a previously unknown localization behavior of the transcript  ...  1/ ( 1 + 2)d and σ2 = 2σ1 , with d being the approximate feature size.  ... 
doi:10.18452/23613 fatcat:4n6n2oxlazggpiwtv2x6556n5e