hummingbird

スパースモデリング

Protected: Sparse Modeling and Multivariate Analysis (10) Use of matrix data decomposition

Machine learning for use in digital transformation (DX) and artificial intelligence (AI), application of matrix data analysis to sparse machine learning, SVD, PMD, NMF, LSA, LSI, PCA, LDA
2021.09.04
スパースモデリング機械学習:Machine Learning
スパースモデリング

Protected: Sparse Modeling and Multivariate Analysis (9) Basics of Matrix Data Decomposition

Machine learning techniques that can be used for digital transformation (DX) and artificial intelligence (AI), fundamentals of applying matrix data to machine learning, singularity decomposition, low-rank matrix approximation
2021.09.03
スパースモデリング機械学習:Machine Learning
検索技術:Search Technology

Image Processing Technology

Overview of image recognition technology used in artificial intelligence (AI) and digital transformation (DX)
2021.09.02
検索技術:Search Technology機械学習:Machine Learning深層学習:Deep Learning画像認識技術
スパースモデリング

Protected: Sparse Modeling and Multivariate Analysis (8) Sparsity of Time Transitions

Application of machine learning techniques and sparse modeling to time-varying information (changes in customers' purchasing interests)
2021.09.02
スパースモデリング機械学習:Machine Learning
スパースモデリング

Protected: Sparse Modeling and Multivariate Analysis (7) Image Processing and Sparsity (Application of Sparse Land Model)

Application of sparse models, one of the machine learning techniques applicable to artificial intelligence (AI) and digital transformation (DX), to image processing (denoising, object extraction, homography transformation, etc.)
2021.09.01
スパースモデリング機械学習:Machine Learning
スパースモデリング

Protected: Sparse Modeling and Multivariate Analysis (6) Image Processing and Sparsity (Overview of Machine Learning for Signal Processing)

Overview of Sparse Models for Machine Learning of Image Information for Artificial Intelligence (AI) and Digital Transformation (DX), JPEG, DCT, Sparse Land Model
2021.08.31
スパースモデリング機械学習:Machine Learning
スパースモデリング

Protected: Sparse modeling and multivariate analysis (5) Graphical lasso and its application (anomaly detection, etc.)

Graph sparse models used for dimensionality reduction of graph data and explanation of machine learning models, introduction of sparsity to relations and its application to graphical lasso and anomaly detection etc.
2021.08.30
スパースモデリング機械学習:Machine Learning
スパースモデリング

Protected: Sparse Modeling and Multivariate Analysis (4) Introducing Sparsity into Relationships

The graph sparsity model, which is used to reduce the dimensionality of graph data and to explain machine learning models, is discussed in terms of introducing sparsity into relationships and graph lasso.
2021.08.29
スパースモデリング機械学習:Machine Learning
機械学習:Machine Learning

Protected: Two approaches to language meaning (fusion of symbolic and distributed representations)

Symbolic and vector representation approaches to natural language meaning that can be used for artificial intelligence (AI) and digital transformation (DX) tasks and their integration, content relation recognition, paraphrase recognition, semantic similarity recognition, datasets (RTE, RITE, STS)
2021.08.28
機械学習:Machine Learning自然言語処理:Natural Language Processing
機械学習:Machine Learning

Protected: Teaching the meaning of words to a computer (on various language models)

Meaning of Natural Language by WordNet (Dictionary), Distributed Hypothesis, PPMI, Singularity Decomposition (SVD), Word2Vec (Distributed Representation) in Natural Language Processing
2021.08.27
機械学習:Machine Learning自然言語処理:Natural Language Processing
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