Search Results - "sparse binary code"

Learning Sparse Binary Code for Maximum Inner Product Search

Authors: Fangchen Yu Changyi Ma Yueyao Yu et al.

Source: Proceedings of the 30th ACM International Conference on Information & Knowledge Management. :3308-3312

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://dl.acm.org/doi/pdf/10.1145/3459637.3482132
https://dblp.uni-trier.de/db/conf/cikm/cikm2021.html#MaYY021

SUCCINCT REPRESENTATION OF CODES WITH APPLICATIONS TO TESTING.

Authors: GRIGORESCU, ELENA KAUFMAN, TALI SUDAN, MADHU

Source: SIAM Journal on Discrete Mathematics; 2012, Vol. 26 Issue 4, p1618-1634, 17p

Subject Terms: AFFINE geometry, ERROR-correcting codes, MATHEMATICAL symmetry, POLYNOMIALS, PROBABILITY theory

On a More General Characterisation of Steiner Systems.

Authors: J. De Kaey

Source: Designs, Codes & Cryptography; Sep2005, Vol. 36 Issue 2, p117-129, 13p

Bridging Dense and Sparse Maximum Inner Product Search.

Authors: Bruch, Sebastian Nardini, Franco Maria Ingber, Amir et al.

Source: ACM Transactions on Information Systems; Nov2024, Vol. 42 Issue 6, p1-38, 38p

Succinct Representation of Codes with Applications to Testing.

Authors: Grigorescu, Elena Kaufman, Tali Sudan, Madhu

Source: Approximation, Randomization & Combinatorial Optimization. Algorithms & Techniques (9783642036842); 2009, p534-547, 14p

Succinct Representation of Codes with Applications to Testing

Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Sudan, Madhu et al.

Source: Joanne Hanley

Index Terms: Article, http://purl.org/eprint/type/SubmittedJournalArticle

URL: http://hdl.handle.net/1721.1/55959
http://dx.doi.org/10.1007/978-3-642-03685-9_40
Lecture Notes in Computer Science

Discrete Infomax Codes for Supervised Representation Learning.

Authors: Lee, Yoonho Kim, Wonjae Park, Wonpyo et al.

Source: Entropy; Apr2022, Vol. 24 Issue 4, p501-501, 21p

Subject Terms: SUPERVISED learning, ELECTRONIC data processing, SHOT peening, COMPUTER programming education

Robot target recognition using deep federated learning.

Authors: Xue, Bin He, Yi Jing, Feng et al.

Source: International Journal of Intelligent Systems; Dec2021, Vol. 36 Issue 12, p7754-7769, 16p

Subject Terms: DEEP learning, CONVOLUTIONAL neural networks, COMPUTER vision, ROBOT vision, SIGNAL convolution, OBJECT recognition (Computer vision), ROBOTS

Joint Discriminative Sparse Coding for Robust Hand-Based Multimodal Recognition.

Authors: Li, Shuyi Zhang, Bob

Source: IEEE Transactions on Information Forensics & Security; 2021, Vol. 16, p3186-3198, 13p

Aggregating Sparse Binarized Local Features by Summing for Efficient 3D Model Retrieval

Authors: Ryutarou Ohbuchi Takahiko Furuya

Source: 2016 IEEE Second International Conference on Multimedia Big Data (BigMM). :314-321

Subject Terms: 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 14. Life underwater

LEARNING DEEP REPRESENTATIONS, EMBEDDINGS AND CODES FROM THE PIXEL LEVEL OF NATURAL AND MEDICAL IMAGES

Authors: Ryan Kiros The Pennsylvania State University CiteSeerX Archives

Contributors: Ryan Kiros The Pennsylvania State University CiteSeerX Archives

Source: http://www.ualberta.ca/~rkiros/kiros_thesis_jun5.pdf.

File Description: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.375.671; http://www.ualberta.ca/~rkiros/kiros_thesis_jun5.pdf

Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.375.671
http://www.ualberta.ca/~rkiros/kiros_thesis_jun5.pdf

Succinct Representation of Codes with Applications to Testing

Authors: Sudan, Madhu Kaufman-Halman, Tali Grigorescu, Elena et al.

Contributors: Sudan, Madhu Kaufman-Halman, Tali Grigorescu, Elena et al.

Source: Joanne Hanley

File Description: application/pdf

Relation: http://dx.doi.org/10.1007/978-3-642-03685-9_40; Lecture Notes in Computer Science; http://hdl.handle.net/1721.1/55959

Availability: http://hdl.handle.net/1721.1/55959

Succinct representation of codes with applications to testing

Authors: Elena Grigorescu Tali Kaufman The Pennsylvania State University CiteSeerX Archives

Contributors: Elena Grigorescu Tali Kaufman The Pennsylvania State University CiteSeerX Archives

Source: http://people.csail.mit.edu/madhu/papers/2009/oneorbit-full.pdf.

File Description: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.303.8462

Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.303.8462
http://people.csail.mit.edu/madhu/papers/2009/oneorbit-full.pdf

Visual Recognition and Inference Using Dynamic Overcomplete Sparse Learning.

Authors: Murray, Joseph F. Kreutz-Delgado, Kenneth

Source: Neural Computation; Sep2007, Vol. 19 Issue 9, p2301-2352, 52p, 4 Black and White Photographs, 8 Diagrams, 4 Charts, 3 Graphs

Subject Terms: VISUAL perception, INFERENCE (Logic), IMAGINATION, BACK propagation, COMPUTER vision, IMAGE processing, ALGORITHMS

A Binding Procedure for Distributed Binary Data Representations.

Authors: D. Rachkovskii S. Slipchenko E. Kussul' et al.

Source: Cybernetics & Systems Analysis; May2005, Vol. 41 Issue 3, p319-331, 13p

CHAPTER 10: Neural and Perceptual Modeling: 10.6 SCHEMA-DRIVEN GROUPING.

Authors: BROWN, GUY J. DELIANG WANG

Source: Computational Auditory Scene Analysis; 2006, p376-378, 3p

Biological Brain and Binary Code: Quality of Coding for Face Recognition

Authors: João da Silva Gomes Roman Borisyuk

Source: Lecture Notes in Computer Science ISBN: 9783642332685

Access URL: https://link.springer.com/content/pdf/10.1007%2F978-3-642-33269-2_54.pdf
https://link.springer.com/chapter/10.1007%2F978-3-642-33269-2_54
https://dblp.uni-trier.de/db/conf/icann/icann2012-1.html#GomesB12
https://rd.springer.com/chapter/10.1007/978-3-642-33269-2_54

Multivariate-Time-Series-Driven Real-time Anomaly Detection Based on Bayesian Network.

Authors: Ding, Nan Gao, Huanbo Bu, Hongyu et al.

Source: Sensors (14248220); Oct2018, Vol. 18 Issue 10, p3367, 1p

Subject Terms: ANOMALY detection (Computer security), CLOUD storage, INTRUSION detection systems (Computer security), INFORMATION resources, INFORMATION storage & retrieval systems

Succinct Representation of Codes with Applications to Testing

Authors: Elena Grigorescu Tali Kaufman Madhu Sudan et al.

Contributors: Elena Grigorescu Tali Kaufman Madhu Sudan et al.

Source: http://people.csail.mit.edu/madhu/papers/2009/oneorbit-conf.pdf.

File Description: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.174.9001

Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.174.9001
http://people.csail.mit.edu/madhu/papers/2009/oneorbit-conf.pdf

Learning Deep Representations, Embeddings and Codes from the Pixel Level of Natural and Medical Images

Authors: Ryan J Kiros

Subject Terms: Machine Learning, Deep Learning, Computer Vision, Representation Learning

Access URL: https://era.library.ualberta.ca/items/10e22854-5947-4b73-8aae-bd9a4f01ef1d
https://era.library.ualberta.ca/items/10e22854-5947-4b73-8aae-bd9a4f01ef1d/view/ef2f60d7-3ca1-4f57-8151-cf688cddc667/kiros_thesis_jun5.pdf