機械学習:Machine Learning

web技術:web technology

ISWC2022Papers

ISWC2022Papers From ISWC2022, an international conference on Semantic Web technologies, one of the artificial ...
推論技術:inference Technology

Protected: Explainable Artificial Intelligence (12) Model-Independent Interpretation (Global Surrogate)

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アルゴリズム:Algorithms

Protected: Application of Neural Networks to Reinforcement Learning Value Function Approximation, which implements value evaluation as a function with parameters.

Application of Neural Networks to Reinforcement Learning used for Digital Transformation, Artificial Intelligence, and Machine Learning tasks Examples of implementing value evaluation with functions with parameters (CartPole, Q-table, TD error, parameter update, Q-Learning, MLPRegressor, Python)
Clojure

Protected: Network Analysis Using Clojure (2)Computing Triangles in a Graph Using Glittering

Network analysis using triangle computation in graphs using Clojure/Glittering for digital transformation, artificial intelligence, and machine learning tasks (GraphX, Pregel API, Twitter dataset, custom triangle count algorithm, message send function, message merge function, outer join, RDD, vertex attributes, Apache Spark, Sparkling, MLlib, Glittering, triangle counting, edge-cut strategy, random-vertex-cut strategy, and social networks, graph parallel computing functions, Hadoop, data parallel systems, RDG, Resilient Distributed Graph, Hama, Giraph)
アルゴリズム:Algorithms

Protected: Regret Analysis for Stochastic Banded Problems

Regret analysis for stochastic banded problems utilized in digital transformation, artificial intelligence, and machine learning tasks (sum of equal sequences, gamma function, Thompson extraction, beta distribution, hem probability, Mills ratio, partial integration, posterior sample, conjugate prior distribution, Bernoulli distribution, cumulative distribution function, expected value, DMED measure, UCB measure, Chernoff-Hefding inequality, likelihood, upper bound, lower bound, UCB score, arms)
アルゴリズム:Algorithms

Protected: Regenerate nuclear Hilbert spaces as a basis for kernel methods in statistical mathematics theory.

Regenerate kernel Hilbert spaces as a basis for kernel methods in statistical mathematics theory used in digital transformation, artificial intelligence, and machine learning tasks orthonormal basis, Hilbert spaces, Gaussian kernels, continuous functions, kernel functions, complete spaces, inner product spaces, equivalence classes, equivalence relations, Cauchy sequences, linear spaces, norms, complete inner products
アルゴリズム:Algorithms

Protected: Batch Stochastic Optimization – Stochastic Dual Coordinate Descent

Stochastic dual coordinate descent algorithms as batch-type stochastic optimization utilized in digital transformation, artificial intelligence, and machine learning tasks Nesterov's measurable method, SDCA, mini-batch, computation time, batch proximity gradient method, optimal solution, operator norm, maximum eigenvalue , Fenchel's dual theorem, principal problem, dual problem, proximity mapping, smoothing hinge loss, on-line type stochastic optimization, elastic net regularization, ridge regularization, logistic loss, block coordinate descent method, batch type stochastic optimization
アルゴリズム:Algorithms

Protected: Newtonian and Modified Newtonian Methods as Sequential Optimization in Machine Learning

Newton and modified Newton methods (Cholesky decomposition, positive definite matrix, Hesse matrix, Newtonian direction, search direction, Taylor expansion) as continuous machine learning optimization for digital transformation, artificial intelligence and machine learning tasks
アルゴリズム:Algorithms

Protected: What triggers sparsity and for what kinds of problems is sparsity appropriate?

What triggers sparsity and for what kinds of problems is sparsity suitable for sparse learning as it is utilized in digital transformation, artificial intelligence, and machine learning tasks? About alternating direction multiplier method, sparse regularization, main problem, dual problem, dual extended Lagrangian method, DAL method, SPAMS, sparse modeling software, bioinformatics, image denoising, atomic norm, L1 norm, trace norm, number of nonzero elements
アルゴリズム:Algorithms

Overview of meta-heuristics and reference books

  Overviews Meta-heuristics can be algorithms used to solve optimization problems. An optimization problem is on...
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