関係データ学習

アルゴリズム:Algorithms

Protected: Regression Analysis with Support Vector Machines (2) Approach to Nonlinear Regression Problems

Approaches to nonlinear regression problems with support vector machines (quantile regression, kernel quantile regression, heterogeneous distribution models, ε-insensitive loss functions) utilized in digital transformation, artificial intelligence, and machine learning tasks.
2022.05.27
アルゴリズム:Algorithms幾何学:Geometry微分積分:Calculus最適化:Optimization機械学習:Machine Learning画像認識技術自然言語処理:Natural Language Processing関係データ学習音声信号認識技術
アルゴリズム:Algorithms

Protected: Structural Regularization Learning with Submodular Optimization (3)Formulation of the structural regularization problem with submodular optimization

Application of submodular function optimization, an optimization method for discrete information, to structural regularization problems and formulations using submodular optimization (linear approximation and steepest effect methods, accelerated proximity gradient method, FISTA, parametric submodular minimization, and splitting algorithms)
2022.05.12
アルゴリズム:Algorithmsグラフ理論スパースモデリング微分積分:Calculus推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics関係データ学習
アルゴリズム:Algorithms

Protected: Structural regularization learning using submodular optimization (2) Structural sparsity obtained from submodular functions

Structural regularization learning (coupled Lasso and Lovász extensions) by structural sparsity obtained from submodular functions in submodular optimization, an optimization method for discrete information used in digital transformation, artificial intelligence, and machine learning tasks.
2022.05.11
アルゴリズム:Algorithmsグラフ理論スパースモデリング微分積分:Calculus数理論理学:Mathematical logic最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics関係データ学習
Symbolic Logic

Reasoning Web 2007 Papers

Machine Learning Technology  Artificial Intelligence Technology  Natural Language Processing Technology  Semantic Web Te...
2022.05.07
Symbolic Logicweb技術:web technologyエキスパートシステム:expertsystemセマンテックウェブ技術:Semantic web Technologyユーザーインターフェース/データビジュアライゼーション推論技術:inference Technology機械学習:Machine Learning関係データ学習
Symbolic Logic

Protected: Maximum Flow and Graph Cut (3) Inference and Graph Cut in Markov Stochastic Fields

Inference and graph cuts in Markov stochastic fields for graph maximal flow extraction by undermodular optimization, a discrete information optimization method for digital transformation, artificial intelligence, and machine learning tasks
2022.05.04
Symbolic Logicアルゴリズム:Algorithmsグラフ理論幾何学:Geometry微分積分:Calculus推論技術:inference Technology数理論理学:Mathematical logic最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics関係データ学習
Symbolic Logic

Inductive logic programming 2020-2021 Papers

Machine Learning Technology  Artificial Intelligence Technology  Natural Language Processing Technology  Semantic Web Te...
2022.04.30
Symbolic Logicグラフ理論推論技術:inference Technology数理論理学数理論理学:Mathematical logic最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics関係データ学習
アルゴリズム:Algorithms

Protected: Maximum Flow and Graph Cutting (2)Maximum Flow Algorithm

Ford-Fulkerson's algorithm and Goldberg-Tarjan's algorithm for the maximum flow problem for directed graphs used in digital transformation, artificial intelligence, and machine learning tasks, pre-flow and push methods, increasing path algorithms, and residual networks
2022.04.29
アルゴリズム:Algorithmsグラフ理論スパースモデリング微分積分:Calculus推論技術:inference Technology数理論理学:Mathematical logic最適化:Optimization機械学習:Machine Learning関係データ学習
Symbolic Logic

Protected: Maximum flow and graph cut (1) Maximum volume and minimum s-t cut

Application of undermodular optimization, an optimization method for discrete information used in digital transformation, artificial intelligence, and machine learning tasks, to minimum cut and maximum flow problems for directed graphs
2022.04.28
Symbolic Logicグラフ理論スパースモデリング幾何学:Geometry推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics関係データ学習
Symbolic Logic

Protected: Maximization of submodular functions and application of the greedy method (2) Sensor placement problem and active learning problem

Application of submodular function maximization and greedy methods to sensor placement and active learning problems in submodular optimization, a method of optimization of discrete information used in digital transformation, artificial intelligence, and machine learning tasks.
2022.04.27
Symbolic Logicグラフ理論スパースモデリング幾何学:Geometry推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics関係データ学習
Symbolic Logic

Inductive logic Programming 2019

Machine Learning Technology  Artificial Intelligence Technology  Natural Language Processing Technology  Semantic Web Te...
2022.04.23
Symbolic Logicグラフ理論推論技術:inference Technology数理論理学最適化:Optimization機械学習:Machine Learning確率・統計:Probability and Statistics関係データ学習
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