Tag: Inference

December 21, 2024

Grammatical Inference Algorithms and Applications 8th International Colloquium, ICGI 2006, Tokyo, Japan, September 20-22, 200

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Free Download Grammatical Inference: Algorithms and Applications: 8th International Colloquium, ICGI 2006, Tokyo, Japan, September 20-22, 2006. Proceedings By Yuji Matsumoto (auth.), Yasubumi Sakakibara, Satoshi Kobayashi, Kengo Sato, Tetsuro Nishino, Etsuji Tomita (eds.)
2006 | 359 Pages | ISBN: 3540452648 | PDF | 3 MB
This book constitutes the refereed proceedings of the 8th International Colloquium on Grammatical Inference, ICGI 2006, held in Tokyo, Japan in September 2006.The 25 revised full papers and 8 revised short papers presented together with 2 invited contributions were carefully reviewed and selected from 44 submissions. The topics of the papers presented range from theoretical results of learning algorithms to innovative applications of grammatical inference and from learning several interesting classes of formal grammars to applications to natural language processing.

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December 11, 2024

Artificial Intelligence and Causal Inference (Chapman & HallCRC Machine Learning & Pattern Recognition)

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Free Download Artificial Intelligence and Causal Inference (Chapman & Hall/CRC Machine Learning & Pattern Recognition) by Momiao Xiong
English | March 8, 2022 | ISBN: 0367859408 | 394 pages | MOBI | 4.83 Mb
Artificial Intelligence and Causal Inference address the recent development of relationships between artificial intelligence (AI) and causal inference. Despite significant progress in AI, a great challenge in AI development we are still facing is to understand mechanism underlying intelligence, including reasoning, planning and imagination. Understanding, transfer and generalization are major principles that give rise intelligence. One of a key component for understanding is causal inference. Causal inference includes intervention, domain shift learning, temporal structure and counterfactual thinking as major concepts to understand causation and reasoning. Unfortunately, these essential components of the causality are often overlooked by machine learning, which leads to some failure of the deep learning. AI and causal inference involve (1) using AI techniques as major tools for causal analysis and (2) applying the causal concepts and causal analysis methods to solving AI problems. The purpose of this book is to fill the gap between the AI and modern causal analysis for further facilitating the AI revolution. This book is ideal for graduate students and researchers in AI, data science, causal inference, statistics, genomics, bioinformatics and precision medicine.

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November 30, 2024

Causal Inference in R

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Free Download Causal Inference in R:
Decipher complex relationships with advanced R techniques for data-driven decision-making
English | 2024 | ISBN: 1837639027 | 665 Pages | EPUB (True) | 10 MB

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September 27, 2024

The Design Inference Eliminating Chance through Small Probabilities

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Free Download The Design Inference: Eliminating Chance through Small Probabilities by William A Dembski, Winston Ewert
English | November 16, 2023 | ISBN: 1637120346 | 583 pages | PDF | 16 Mb
A landmark of the intelligent design movement, The Design Inference revolutionized our understanding of how we detect intelligent causation. Originally published twenty-five years ago, it has now been revised and expanded into a second edition that greatly sharpens its exploration of design inferences. This new edition tackles questions about design left unanswered by David Hume and Charles Darwin, navigating the intricate nexus of chance, probability, and design, and thereby offering a novel lens for understanding the world. Using modern concepts of probability and information, it exposes the inadequacy of undirected causes in scientific inquiry. It lays out how we infer design via events that are both improbable and specified. Amid controversial applications to biology, it makes a compelling case for intelligent design, challenging the prevalent neo-Darwinian evolutionary narrative. Dembski and Ewert have written a groundbreaking work that doesn’t merely comment on contemporary scientific discourse but fundamentally transforms it.

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September 16, 2024

Selected Topics in Statistical Inference Theory and Applications

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Free Download Selected Topics in Statistical Inference: Theory and Applications by Manisha Pal , Bikas K. Sinha
English | PDF EPUB (True) | 2024 | 153 Pages | ISBN : 9819725917 | 16.5 MB
This book focuses exclusively on the domain of parametric inference and that, too, from a reader’s perspective, i.e., covering only point estimation of parameter(s). It covers those topics in parametric inference which need clarity of exposure to students, researchers, and teachers alike; mere statements of theorems and proofs may not always reveal the inner beauty and significance of some aspects of inference. To ensure clarity, the book discusses the following topics at an advanced level-(1) sequential (unbiased) point estimation of ‘p’ and its functions; generalization to trinomial and tetranomial populations; (2) some aspects of the use of additional resources in finite population inference; (3) the concept of sufficiency vis-à-vis the notion of sufficient experiments and comparison of experiments; (4) estimation of the size of a finite population with special features; and (5) unbiased estimation of reliability in exponential samples and other settings. This book provides a platform for thought-provoking, creative, and challenging discussions on a variety of topics in statistical estimation theory, it is also ideal for research methodology course for statistics research scholars, and for clarification of basic ideas in topics discussed at basic/advanced levels.

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