1.

Record Nr.

UNINA9910973136403321

Autore

Rescher Nicholas

Titolo

Epistemological studies / / Nicholas Rescher

Pubbl/distr/stampa

Frankfurt, : Ontos Verlag, 2009

ISBN

3-86838-048-5

3-11-031949-7

Descrizione fisica

1 online resource (121 p.)

Disciplina

121

Soggetti

Knowledge, Theory of

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Frontmatter -- Contents -- Preface -- Chapter 1: INTELLIGENCE AND EVOLUTIONARY INNOVATION -- Chapter 2: ON OVERSIMPLIFICATION AND THE GROWTH OF KNOWLEDGE -- Chapter 3: VAGUENESS: SOME VARIANT APPROACHES -- Chapter 4: UNDERDETERMINATION -- Chapter 5: COGNITIVE COMPROMISE: On Managing Cognitive Risk in the Face of Imperfect/Flawed Information -- Chapter 6: AUTHORITY -- Chapter 7: AN EXPLANATORY CONUNDRUM -- Chapter 8: THE MUSICAL CHAIRS PARADOX -- Chapter 9: TRANSCENDENTAL ARGUMENTATION AND HUMAN NATURE -- Chapter 10: A MULTITUDE OF WORLDS? -- Name Index -- Backmatter

Sommario/riassunto

The present book continues Rescher's longstanding practice of publishing occasional studies written for formal presentation and informal discussion with colleagues. They form part of a wider program of investigation of the scope and limits of rational inquiry in the pursuit of knowledge.



2.

Record Nr.

UNISA996647969703316

Autore

Nicosia Giuseppe

Titolo

Machine Learning, Optimization, and Data Science : 10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22–25, 2024, Revised Selected Papers, Part II / / edited by Giuseppe Nicosia, Varun Ojha, Sven Giesselbach, M. Panos Pardalos, Renato Umeton

Pubbl/distr/stampa

Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025

ISBN

9783031824845

9783031824838

Edizione

[1st ed. 2025.]

Descrizione fisica

1 online resource (606 pages)

Collana

Lecture Notes in Computer Science, , 1611-3349 ; ; 15509

Altri autori (Persone)

OjhaVarun

GiesselbachSven

PardalosM. Panos

UmetonRenato

Disciplina

006.3

Soggetti

Artificial intelligence

Artificial Intelligence

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

-- Exploring Explainable Machine Learning for Enhanced Ship Performance Monitoring.  -- Identifying Potential Key Point of Sale Customers Using Network Centrality.  -- Hyperparameter Optimization for Driving Strategies Based on Reinforcement Learning.  -- Predicting Multiple Sclerosis Worsening Using Stratification Based and Time Dependent Variables Extracted from Routine Visits Data.  -- Predicting University Dropout Rates Using Machine Learning: UniCt case.  -- Investigating on Gradient Regularization for Testing Neural Networks.  -- SKIE SRL: Structured Key Information Extraction from Business Documents using Statistical Relational Learning.  -- Leveraging LLM powered Systems to Accelerate Mycobacterium tuberculosis Research Step One: From Documents to the Vectorstore.  -- Vegvisir: Probabilistic model (VAE) for viral T cell epitope prediction.  -- Tiny Long Short Term Memory Model for Resource Constrained Prediction of Battery Cycle Life.  -- Compact Artificial Neural Network Models for



Predicting Protein Residue RNA Base Binding.  -- FWin transformer for dengue prediction under climate and ocean influence.  -- ENGinnSAND: A Reference Dataset for Monocular Depth Prediction of Line Structures.  -- Topological Layering of Mouse Brain Activity in Light Sheet Microscopy Datasets.  -- A Constraint Based Savings Algorithm for the Traveling Salesman Problem.  -- Gaussian process interpolation with conformal prediction: methods and comparative analysis.  -- Using embeddings of pre trained models for cross database dysarthria detection: supervised vs. self supervised approach.  -- Personality Profiling for Literary Character Dialogue Agents with Human Level Attributes.  -- Integrating Logit Space Embeddings for Reliable Out of Distribution Detection.  -- A Computational Framework for Identifying Salient Moments in Motion Capture Data.  -- Machine Learning for the Evaluation of the Nephrops Norvegicus Population.  -- Enhancing Cluster Based Topic Models through Parametric Dimensionality Reduction with Transformer Encoders.  -- Enhancing Arrhythmia Detection Using an Ensemble of Transformer Models for Heartbeat Classification.  -- Rapidly Computing Approximate Graph Convex Hulls via FastMap.  -- Deep Gaussian mixture model for unsupervised image segmentation.  -- Address Classification in E commerce Logistics Using Federated Learning.

Sommario/riassunto

The three-volume set LNAI 15508-15510 constitutes the refereed proceedings of the 10th International Conference on Machine Learning, Optimization, and Data Science, LOD 2024, held in Castiglione della Pescaia, Italy, during September 22–25, 2024. This year, in the LOD Proceedings decided to also include the papers of the fourth edition of the Symposium on Artificial Intelligence and Neuroscience (ACAIN 2024). The 79 full papers included in this book were carefully reviewed and selected from 127 submissions. The LOD 2024 proceedings focus on machine learning, deep learning, AI, computational optimization, neuroscience and big data that includes invited talks, tutorial talks, special sessions, industrial tracks, demonstrations and oral and poster presentations of refereed papers.