自然言語処理:Natural Language Processing

Clojure

Chatbot implementation using Clojure and Javascript and integration of AI functionality

Building a chatbot framework in Clojure and Javascript for use in digital transformation , artificial intelligence , and machine learning tasks and integrating various AI functions natural language processing, SVM, BERT, Transformer, Knowledge Graph, database, expert systems
アルゴリズム:Algorithms

Protected: Support Vector Machines for Weak Label Learning (2) Multi-Instance Learning

Extension of support vector machines utilized for digital transformation, artificial intelligence, and machine learning tasks; multi-instance learning approach with SVMs for weak-label learning problems (mi-SVM, MI-SVM)
アルゴリズム:Algorithms

Protected: Support Vector Machines for Weak Label Learning (1) Semi-supervised Learning

Weak label learning (semi-supervised learning where label information is given only for a subset of training cases) as an application of support vector machines utilized in digital transformation, artificial intelligence, and machine learning tasks
R

Protected: Structured Support Vector Machines

SVM structure learning and parsing using the deletion plane method algorithm on support vector machines utilized for digital transformation, artificial intelligence, and machine learning tasks, and protein similarity sequence search
アルゴリズム:Algorithms

Protected: Support vector machine software and implementation

Classification and regression with SVM using R kernlab in support vector machines used for digital transformation, artificial intelligence and machine learning tasks and LIBSVM algorithms SMO algorithm, shrinking
アルゴリズム:Algorithms

Protected: Partitioning Methods in Support Vector Machines (2) DCDM Algorithm for Linear SVM

DCDM algorithm (dual coordinate descent method algorithm), an efficient algorithm for processing large amounts of (sparse) data on support vector machines (algorithm for linear SVM used in LIBLINEAR) used in digital transformation (DX), artificial intelligence (AI) and machine learning (ML) tasks.
アルゴリズム:Algorithms

Protected: Partitioning Method on Support Vector Machines (1) SMO Algorithm

Efficiency using the partitioning method (SMO algorithm) on support vector machines utilized for digital transformation (DX), artificial intelligence (AI), and machine learning (ML) tasks
Symbolic Logic

Protected: Introduction to Optimization with Support Vector Machines: Optimality Conditions and Generic Solution Methods

Optimality conditions (strong duality and KKT) and generic solution methods (active set and interior point method) in support vector machines used for digital transformation, artificial intelligence and machine learning tasks
アルゴリズム:Algorithms

Protected: Support vector machines for unsupervised learning

Application of support vector machines for digital transformation, artificial intelligence, and machine learning tasks (1-class SVM with nu-SV classification algorithm for unsupervised classification used for anomaly detection)
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.
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