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Pylearn2: a machine learning research library
[article]
2013
arXiv
pre-print
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Pylearn2 is a machine learning research library. ...
This does not just mean that it is a collection of machine learning algorithms that share a common API; it means that it has been designed for flexibility and extensibility in order to facilitate research ...
Introduction Pylearn2 is a machine learning research library developed by LISA at Université de Montréal. The goal of the library is to facilitate machine learning research. ...
arXiv:1308.4214v1
fatcat:nwsear5oenhullzswvv5p6yzae
A Generation Method of Immunological Memory in Clonal Selection Algorithm by Using Restricted Boltzmann Machines
2015
2015 IEEE International Conference on Systems, Man, and Cybernetics
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2018 pre-print arXiv:1804.02816v1 fatcat:vhf4gikxanbkvghks4lk3gj2ja
To verify the effectiveness of the method, some experiments for classification of the subjective data are executed by using machine learning tools for Deep Learning. ...
Recently, a high technique of image processing is required to extract the image features in real time. ...
MACHINE LEARNING TOOL Pylearn2 [10] is one of machine learning tools with libraries for Deep Learning [8] . ...
doi:10.1109/smc.2015.465
dblp:conf/smc/KamadaI15
fatcat:2enxktegxzf7fbeszzqdancf3e
Toolkits and Libraries for Deep Learning
2017
Journal of digital imaging
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Deep learning is an important new area of machine learning which encompasses a wide range of neural network architectures designed to complete various tasks. ...
Whereas traditional machine learning requires determination and calculation of features from which the algorithm learns, deep learning approaches learn the important features as well as the proper weighting ...
creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a ...
doi:10.1007/s10278-017-9965-6
pmid:28315069
pmcid:PMC5537091
fatcat:7obzia6qq5futkdaxq3yyap5z4
Blocks and Fuel: Frameworks for deep learning
[article]
2015
arXiv
pre-print
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Fuel provides a standard format for machine learning datasets. It allows the user to easily iterate over large datasets, performing many types of pre-processing on the fly. ...
Blocks is based on Theano, a linear algebra compiler with CUDA-support. ...
Acknowledgments The authors would like to acknowledge the support of the following agencies for research funding and computing support: NSERC, Calcul Québec, Compute Canada, the Canada Research Chairs ...
arXiv:1506.00619v1
fatcat:xp6wxgav4rcg5pgzityagso63i
A Generic Software Platform for Brain-inspired Cognitive Computing
2015
Procedia Computer Science
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We have been developing BriCA (Brain-inspired Computing Architecture), the generic software platform that can combine an arbitrary number of machine learning modules to construct higher structures such ...
http://deeplearning.net/software/pylearn2/ Brain-inspired Computing Architecture Takahashi et al. ...
Open source generic ML libraries such as Scikit-learn (scikit-learn.org), Theano § § , PyBrain (pybrain.org), PyLearn2 *** , and Weka are available to be embedded in modules. ...
doi:10.1016/j.procs.2015.12.185
fatcat:zeea55rrgfhj3dl7k5oy5b3zwi
Toward content-based image retrieval with deep convolutional neural networks
2015
Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging
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Recent advances in database capacity, algorithm efficiency, and deep Convolutional Neural Networks (dCNN), a machine learning technique, have enabled great CBIR success for general photographic images. ...
Quantitative results were disappointing (averaging a true positive rate of only 20%); however, the data suggest that improvements would be possible with more evenly distributed sampling across labels and ...
This work was conducted in part using the resources of the Advanced Computing Center for Research and Education at Vanderbilt University, Nashville, TN. ...
doi:10.1117/12.2081551
pmid:25914507
pmcid:PMC4405657
dblp:conf/mibam/SklanPFL15
fatcat:bhvrjpdizzganbtecckxzyk37i
Automating Marine Mammal Detection in Aerial Images Captured During Wildlife Surveys: A Deep Learning Approach
[chapter]
2015
Lecture Notes in Computer Science
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In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. ...
Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. ...
However, a few low-level functions had to be written using the Theano library [4] on which Pylearn2 is built. We compared two CNN architectures for our application (see Figure 4 ). ...
doi:10.1007/978-3-319-26350-2_33
fatcat:ygmup4ve2jbu5c2v6grdgime7q
Analysis of using software packages for imaging in medical diagnostics
2016
Electronics and Control Systems
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Libraries Treano and Torch were investigated. ...
Library Torch Torch -library for scientific computing with broad support machine learning algorithms. ...
Theano was developed in the laboratory LISA for supporting the rapid development of machine learning algorithms. ...
doi:10.18372/1990-5548.50.11399
fatcat:hnvdogrbijdvpjy75frjgt37m4
A Step Forward Towards Deep Learning
2017
International Journal of Advanced Research in Computer Science and Software Engineering
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Deep learning is no more just a buzzword but a fast scenario turning reality. The current market is trying to optimize its processes using machine learning and deep learning. ...
Also, the demand for a machine engineer or a deep learning scientist has increased manifold. With this rate, knowing and applying deep learning would not only remain a skill but a necessity. ...
MLpython is a library for organizing machine learning research. ...
doi:10.23956/ijarcsse/v7i3/0121
fatcat:kkww74cx4ffmjltcyqcqx4rrlq
A powerful comparison of deep learning frameworks for Arabic sentiment analysis
2021
International Journal of Power Electronics and Drive Systems (IJPEDS)
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Deep learning (DL) is a machine learning (ML) subdomain that involves algorithms taken from the brain function named artificial neural networks (ANNs). ...
For working on Arabic SA, researchers can use various DL libraries in their projects, but without justifying their choice or they choose a group of libraries relying on their particular programming language ...
There is a set of machine learning models powering natural language processing (NLP) applications. Recently, DL approaches have gained high performance across various NLP tasks [3] . ...
doi:10.11591/ijece.v11i1.pp745-752
fatcat:jmavlc5bdvcq3glvovciwlbitq
The State of the Art when using GPUs in Devising Image Generation Methods Using Deep Learning
[article]
2021
arXiv
pre-print
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Deep learning is a technique for machine learning using multi-layer neural networks. ...
About Deep Learning(2015~2016) Deep learning is a technique for machine learning using multilayer neural networks. ...
It is also highly versatile in that it can be used with cuDNN, a GPU library for deep learning developed by NIVIDIA. ...
arXiv:2109.05783v1
fatcat:thrmmglypjampc23jy2y6qpsre
Musical Audio Synthesis Using Autoencoding Neural Nets
2014
Proceedings of the SMC Conferences
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Our models are trained using the Pylearn2 machine learning library [11] which wraps around Theano [12] for fast evaluation of mathematical expressions. ...
As with any machine learning paradigm, there are also tradeoffs. The ANN is a highly general model and it may be designed in a number of ways. ...
doi:10.5281/zenodo.850877
fatcat:7fc5juwmdrd2ffb74ua3e64evq
Mining Big Data Using Modified Induction Tree Approach
2016
International Journal of Intelligent Engineering and Systems
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The most effective method to separate significant data from huge information has been a famous open issue. In this paper, we are proposing new algorithm of decision tree in big data. ...
It is an interactive algorithm which is learning at different level of abstractions. Pylearn2: It is a user friendly machine learning library [11] , built on top of Theano. ...
It is a research library (who provides flexibility and extensibility) developed by LISA lab. ...
doi:10.22266/ijies2016.0630.03
fatcat:4zhmb4aqtffndobb6mbvu5zbbm
Caffe
2014
Proceedings of the ACM International Conference on Multimedia - MM '14
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Caffe provides multimedia scientists and practitioners with a clean and modifiable framework for state-of-the-art deep learning algorithms and a collection of reference models. ...
The framework is a BSD-licensed C++ library with Python and MATLAB bindings for training and deploying generalpurpose convolutional neural networks and other deep models efficiently on commodity architectures ...
As such, it's an ideal starting point for researchers and other developers looking to jump into state-of-the-art machine learning. ...
doi:10.1145/2647868.2654889
dblp:conf/mm/JiaSDKLGGD14
fatcat:f43ch33ekjel3mbb2ll3n7svsa
Human activity recognition with smartphone sensors using deep learning neural networks
2016
Expert systems with applications
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A wider time span of temporal local correlation can be exploited (1 × 9-1 × 14) and a low pooling size (1 × 2-1 × 3) is shown to be beneficial. ...
Human activity recognition (HAR), a field that has garnered a lot of attention in recent years due to its high demand in various application domains, makes use of time-series sensor data to infer activities ...
Next in line is Pylearn2-a rapidly developing machine learning library in Python ( Goodfellow et al., 2013 ) . ...
doi:10.1016/j.eswa.2016.04.032
fatcat:ewrocoxmwje3zfejbazinqkhue
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