Inductive Logic Programming : 30th International Conference, ILP 2021, Virtual Event, October 25-27, 2021, Proceedings (Lecture Notes in Computer Science)

個数:

Inductive Logic Programming : 30th International Conference, ILP 2021, Virtual Event, October 25-27, 2021, Proceedings (Lecture Notes in Computer Science)

  • 提携先の海外書籍取次会社に在庫がございます。通常3週間で発送いたします。
    重要ご説明事項
    1. 納期遅延や、ご入手不能となる場合が若干ございます。
    2. 複数冊ご注文の場合、分割発送となる場合がございます。
    3. 美品のご指定は承りかねます。

    ●3Dセキュア導入とクレジットカードによるお支払いについて
  • 【入荷遅延について】
    世界情勢の影響により、海外からお取り寄せとなる洋書・洋古書の入荷が、表示している標準的な納期よりも遅延する場合がございます。
    おそれいりますが、あらかじめご了承くださいますようお願い申し上げます。
  • ◆画像の表紙や帯等は実物とは異なる場合があります。
  • ◆ウェブストアでの洋書販売価格は、弊社店舗等での販売価格とは異なります。
    また、洋書販売価格は、ご注文確定時点での日本円価格となります。
    ご注文確定後に、同じ洋書の販売価格が変動しても、それは反映されません。
  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 283 p.
  • 商品コード 9783030974534

Full Description

This book constitutes the refereed conference proceedings of the 30th International Conference on Inductive Logic Programming, ILP 2021, held in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 16 papers and 3 short papers presented were carefully reviewed and selected from 19 submissions. Inductive Logic Programming (ILP) is a subfield of machine learning, which originally relied on logic programming as a uniform representation language for expressing examples, background knowledge and hypotheses. Due to its strong representation formalism, based on first-order logic, ILP provides an excellent means for multi-relational learning and data mining, and more generally for learning from structured data.

Contents

Embedding Models for Knowledge Graphs Induced by Clusters of Relations and Background Knowledge.- Fanizzi Automatic Conjecturing of P-Recursions Using Lifted Inference.- Machine learning of microbial interactions using Abductive ILP and Hypothesis Frequency/Compression Estimation.- Answer-Set Programs for Reasoning about Counterfactual Interventions and Responsibility Scores for Classification.- Reyes Synthetic Datasets and Evaluation Tools for Inductive Neural Reasoning.- Using Domain-Knowledge to Assist Lead Discovery in Early-Stage Drug Design.- Non-Parametric Learning of Embeddings for Relational Data using Gaifman Locality Theorem.- Ontology Graph Embeddings and ILP for Financial Forecasting.- Transfer learning for boosted relational dependency networks through genetic algorithm.- Online Learning of Logic Based Neural Network Structures.- Programmatic policy extraction by iterative local search.- Mapping across relational domains for transfer learning with word embeddings-based similarity.- A First Step Towards Even More Sparse Encodings of Probability Distributions.- Feature Learning by Least Generalization.- Learning Logic Programs Using Neural Networks by Exploiting Symbolic Invariance.- Learning and revising dynamic temporal theories in the full Discrete Event Calculus.- Human-like rule learning from images using one-shot hypothesis derivation.- Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits.- A Simulated Annealing Meta-heuristic for Concept Learning in Description Logics. 

最近チェックした商品