Results 71 to 80 of about 343,485 (273)
Structure Extension of Tree-Augmented Naive Bayes
Entropy, 2019 Due to the simplicity and competitive classification performance of the naive Bayes (NB), researchers have proposed many approaches to improve NB by weakening its attribute independence assumption.
Yuguang Long, Limin Wang, Minghui Sun
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Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information [PDF]
, 2017 Conditional independence testing is a fundamental problem underlying causal discovery and a particularly challenging task in the presence of nonlinear and high-dimensional dependencies.
Runge, Jakob
core +1 more source
Conditional independence, conditional mixing and conditional association [PDF]
Annals of the Institute of Statistical Mathematics, 2007 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback
Advanced Robotics Research, EarlyView.BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat +4 more
wiley +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Advanced Robotics Research, EarlyView.Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
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Conditional and unconditional statistical independence [PDF]
Journal of Econometrics, 1988 Conditional independence almost everywhere in the space of the conditioning variates does not imply unconditional independence, although it may well imply unconditional independence of certain functions of the variables. An example that is important in linear regression theory is discused in detail. This involves orthogonal projections on random linear
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Advanced Robotics Research, EarlyView.Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar +8 more
wiley +1 more source
Cross‐Scale Hierarchical Targeted Delivery System Based on Small‐Scale Magnetic Robots
Advanced Robotics Research, EarlyView.This article reviews a cross‐scale hierarchical targeted delivery system that integrates magnetic continuum robots and magnetic microrobots. By combining rapid long‐range navigation with precise microscale targeting, the system overcomes key limitations of single‐scale approaches.
Junjian Zhou +4 more
wiley +1 more source
Review of Causal Discovery Methods Based on Graphical Models
Frontiers in Genetics, 2019 A fundamental task in various disciplines of science, including biology, is to find underlying causal relations and make use of them. Causal relations can be seen if interventions are properly applied; however, in many cases they are difficult or even ...
Clark Glymour, Kun Zhang, Peter Spirtes
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Evaluating Independence and Conditional Independence Measures
, 2022 Independence and Conditional Independence (CI) are two fundamental concepts in probability and statistics, which can be applied to solve many central problems of statistical inference. There are many existing independence and CI measures defined from diverse principles and concepts.
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