Description

Book Synopsis

.- Solving Two-Stage Stochastic Programming problems via Machine Learning.
.- Weight-varying Model Predictive Control for Coupled Cyber-Physical Systems: Aerial Grasping Study.
.- Assessing the Impact of Government Policies on Covid-19 Spread: A Machine Learning Approach.
.- Optimal Design and Implementation of an Open-source Emulation Platform for User-Centric Shared E-mobility Services.
.- Protein Sequence Generation using Denoising Probabilistic Diffusion Model.
.- Individual Fairness in Generative Text Models.
.- Refined Direct Preference Optimization with Synthetic Data for Behavioral Alignment of LLMs.
.- Artificial Intelligence and Cyber Security.
.- Exploring Digital Health Trends in the Headlines via Knowledge Graph Analysis.
.- Robust Infidelity: When Faithfulness Measures on Masked Language Models Are Misleading.
.- Optimal risk scores for continuous predictors.
.- Post-Treatment Gait Prediction after Botulinum Toxin Injections Using Deep Learning with an Attention Mechanism.
.- Leveraging Graph Networks and Generative Adversarial Networks for Controllable Trajectory Prediction.
.- Nearest Neighbors Counterfactuals.
.- An Attention-based Representation Distillation Baseline for Multi-Label Continual Learning.
.- Pattern detection in abnormal district heating data.
.- Harnessing Graph Neural Networks for Pattern Classification in Heterogeneous Event Graphs.
.- Learn to Create Neighborhoods in Real-World Vehicle Routing Problem.
.- PointerKex: A Pointer-based SSH Key Extraction method.
.- Addressing The Permutation Flowshop Scheduling with Grey Wolf Optimizer.
.- MCGRAN: Multi-Conditional Graph Generation for Neural Architecture Search.
.- Generative reward machine for Reinforcement learning for Physical Internet Distribution Centre.
.- Between accurate prediction and poor decision making: the AI/ML gap.
.- Cross-Metapath based Hashing for Recommendation Systems.
.- Beyond Iterative Tuning: Zero-Shot Hyperparameter Optimisation for Decision Trees.
.- Augmented Human-AI Forecasting for Ship Refit Project Scheduling: A Predict-then-Optimize Approach.
.- Evaluation of Document Deduplication Algorithms for Large Text Corpora.
.- Hicks Traverse meets One-Factor SVM: Belief Incoherence Attractors.
.- Synthetic Time Series for Anomaly Detection in Cloud Microservices.
.- Radiotherapy Treatment Planning: An Integrated Optimization and Reinforcement
Learning Approach.
.- Leap: Inductive Link Prediction via Learnable Topology Augmentation.
.- Estimating Completeness of Consensus Models: Geometrical and Distributional Approaches.
.- Active Inference Meeting Energy-Efficient Control of Parallel and Identical Machines.
.- Clarifying the Fog: Evaluating and Enhancing User Comprehension of Android Data Safety Documents.

Machine Learning Optimization and Data Science

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    A Paperback by Giuseppe Nicosia

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      Publisher: Springer
      Publication Date: Publication Date: 07/03/2025
      ISBN13: 9783031824807, 978-3031824807
      ISBN10:
      Also in:
      Computing Artificial intelligence (AI)

      Description

      Book Synopsis

      .- Solving Two-Stage Stochastic Programming problems via Machine Learning.
      .- Weight-varying Model Predictive Control for Coupled Cyber-Physical Systems: Aerial Grasping Study.
      .- Assessing the Impact of Government Policies on Covid-19 Spread: A Machine Learning Approach.
      .- Optimal Design and Implementation of an Open-source Emulation Platform for User-Centric Shared E-mobility Services.
      .- Protein Sequence Generation using Denoising Probabilistic Diffusion Model.
      .- Individual Fairness in Generative Text Models.
      .- Refined Direct Preference Optimization with Synthetic Data for Behavioral Alignment of LLMs.
      .- Artificial Intelligence and Cyber Security.
      .- Exploring Digital Health Trends in the Headlines via Knowledge Graph Analysis.
      .- Robust Infidelity: When Faithfulness Measures on Masked Language Models Are Misleading.
      .- Optimal risk scores for continuous predictors.
      .- Post-Treatment Gait Prediction after Botulinum Toxin Injections Using Deep Learning with an Attention Mechanism.
      .- Leveraging Graph Networks and Generative Adversarial Networks for Controllable Trajectory Prediction.
      .- Nearest Neighbors Counterfactuals.
      .- An Attention-based Representation Distillation Baseline for Multi-Label Continual Learning.
      .- Pattern detection in abnormal district heating data.
      .- Harnessing Graph Neural Networks for Pattern Classification in Heterogeneous Event Graphs.
      .- Learn to Create Neighborhoods in Real-World Vehicle Routing Problem.
      .- PointerKex: A Pointer-based SSH Key Extraction method.
      .- Addressing The Permutation Flowshop Scheduling with Grey Wolf Optimizer.
      .- MCGRAN: Multi-Conditional Graph Generation for Neural Architecture Search.
      .- Generative reward machine for Reinforcement learning for Physical Internet Distribution Centre.
      .- Between accurate prediction and poor decision making: the AI/ML gap.
      .- Cross-Metapath based Hashing for Recommendation Systems.
      .- Beyond Iterative Tuning: Zero-Shot Hyperparameter Optimisation for Decision Trees.
      .- Augmented Human-AI Forecasting for Ship Refit Project Scheduling: A Predict-then-Optimize Approach.
      .- Evaluation of Document Deduplication Algorithms for Large Text Corpora.
      .- Hicks Traverse meets One-Factor SVM: Belief Incoherence Attractors.
      .- Synthetic Time Series for Anomaly Detection in Cloud Microservices.
      .- Radiotherapy Treatment Planning: An Integrated Optimization and Reinforcement
      Learning Approach.
      .- Leap: Inductive Link Prediction via Learnable Topology Augmentation.
      .- Estimating Completeness of Consensus Models: Geometrical and Distributional Approaches.
      .- Active Inference Meeting Energy-Efficient Control of Parallel and Identical Machines.
      .- Clarifying the Fog: Evaluating and Enhancing User Comprehension of Android Data Safety Documents.

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