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Multilayer neural networks set the current state of the art for many technical classification problems.
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Holographic Reduced Representations: Distributed Representation for Cognitive Structures
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Some Approaches to Analogical Mapping with Structure Sensitive Distributed Representations
D. A. Rachkovskij · 2004
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Sparse Binary Distributed Encoding of Scalars
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Combination of the Assembly Neural Network with a Perceptron for Recognition of Handwritten Digits Arranged in Numeral Strings
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Hyperdimensional Computing: An Introduction to Computing in Distributed Representation with High-Dimensional Random Vectors
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Reservoir computing approaches to recurrent neural network training
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Long Short-Term Memory in Echo State Networks: Details of a Simulation Study
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A Practical Guide to Applying Echo State Networks
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ImageNet Classification with Deep Convolutional Neural Networks
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Similarity-based Retrieval with Structure-Sensitive Sparse Binary Distributed Representations
D. A. Rachkovskij and S. V. Slipchenko · 2012
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Dependable MAC Layer Architecture based on Holographic Data Representation using Hyper-Dimensional Binary Spatter Codes
D. Kleyko, N. Lyamin, E. Osipov, and L. Riliskis · 2012
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Recent Advances in Physical Reservoir Computing: A review
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Representing Objects, Relations, and Sequences
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FitNets: Hints for Thin Deep Nets
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Visualizing and Understanding Convolutional Networks
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Sparseness and Expansion in Sensory Representations
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Do we Need Hundreds of Classifiers to Solve Real World Classification Problems?
M. Fernandez-Delgado, E. Cernadas, S. Barro, and D. Amorim · 2014
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Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan and A. Zisserman · 2014
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ImageNet Large Scale Visual Recognition Challenge
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Going Deeper with Convolutions
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Machine Learning Using Cellular Automata Based Feature Expansion and Reservoir Computing
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Symbolic Computation Using Cellular Automata-Based Hyperdimensional Computing
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Preparing for the Future of Artificial Intelligence
Executive Office of the President National Science and Technology Council Committee on Technology · 2016
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Sequence Prediction with Sparse Distributed Hyperdimensional Coding Applied to the Analysis of Mobile Phone Use Patterns
O. Rasanen and J. Saarinen · 2016
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Modification of Holographic Graph Neuron using Sparse Distributed Representations
Neural Architecture Search: A Survey
T. Elsken, J. H. Metzen, and F. Hutter · 2019
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SNIP: Single-shot Network Pruning based on Connection Sensitivity
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Efficient Biosignal Processing Using Hyperdimensional Computing: Network Templates for Combined Learning and Classification of ExG Signals
A. Rahimi, P. Kanerva, L. Benini, and J. M. Rabaey · 2019
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UCI Machine Learning Repository, 2019
D. Dua and C. Graff · 2019
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Hardware optimizations of dense binary hyperdimensional computing: Rematerialization of hypervectors, binarized bundling, and combinational associative memory
M. Schmuck, L. Benini, and A. Rahimi · 2019
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D. Kleyko, E. Osipov, and D.A. Rachkovskij · 2016
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Deep Residual Learning for Image Recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Rethinking the Inception Architecture for Computer Vision
C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, and W. Zbigniew · 2016
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Recognizing Permuted Words with Vector Symbolic Architectures: A Cambridge Test for Machines
D. Kleyko, E. Osipov, and R. W. Gayler · 2016
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Language Geometry Using Random Indexing
A. Joshi, J. T. Halseth, and P. Kanerva · 2016
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Opening the Black Box of Deep Neural Networks via Information
R. Shwartz-Ziv and N. Tishby · 2017
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Peephole: Predicting Network Performance before Training
B. Deng, J. Yan, and D. Lin · 2017
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Pruning Neural Networks without Any Data by Iteratively Conserving Synaptic Flow
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Search for a Substring of Characters using the Theory of Non-deterministic Finite Automata and Vector-Character Architecture
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