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Algorithms for non-negative matrix factorization

D Seung, +1 more
- Vol. 13, pp 556-562
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The article was published on 2001-01-01 and is currently open access. It has received 5015 citations till now. The article focuses on the topics: Non-negative matrix factorization.

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Journal ArticleDOI

Constrained Concept Factorization for Image Representation

TL;DR: A novel semi-supervised matrix decomposition method for extracting the image concepts that are consistent with the known label information by requiring that the data points sharing the same label have the same coordinate in the new representation space.
Journal ArticleDOI

Temporal Psychovisual Modulation: A New Paradigm of Information Display [Exploratory DSP]

TL;DR: The TPVM display paradigm, differs fundamentally in design principle, user experience, and cost effectiveness, from the head-mounted display (HMD) technology and all others while offering richer functionalities.
Patent

Multi-line addressing methods and apparatus

TL;DR: In this paper, a multi-line addressing (MLA) based method was proposed to drive organic light emitting diodes (OLED) displays using a plurality of pixels each addressable by a row electrode and a column electrode.
Journal ArticleDOI

Exploring Hierarchical Structures for Recommender Systems

TL;DR: This paper proposes a novel recommendation framework, which enables us to explore the implicit hierarchies of users and items simultaneously and extends the framework to integrate explicit hierarchies when they are available, which gives a unified framework for both explicit and implicit hierarchical structures.
Book ChapterDOI

Deep Feature Factorization For Concept Discovery

TL;DR: Deep Feature Factorization is used to gain insight into a deep convolutional neural network's learned features, where it detects hierarchical cluster structures in feature space as heat maps.
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