Reinforcement Learning
Concepts of reinforcement learning in the context of applied machine learning, with a focus on Markov Decision Processes, Q-Learning, and example applications.
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Deep Reinforcement Learning for Mobile App Prediction
This research focuses on a system, known as ATPP, based on deep marked temporal point processes, designed for predicting mobile app usage patterns. By leveraging deep reinforcement learning frameworks and context-aware modules, the system aims to predict the next app a user will open, along with its
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Artificial Intelligence and Computer-Related Inventions
Explore the key concepts and techniques in the field of artificial intelligence (AI), including supervised learning, unsupervised learning, reinforcement learning, deep learning, and generative adversarial networks. Gain insights into the evolving definitions of intelligence in machines and the pote
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Understanding Composite Materials: Reinforcement and Matrix in Composites
Composite materials consist of reinforcement and matrix components, each serving a specific purpose to enhance the properties of the composite. The reinforcement phase provides strength and stiffness, while the matrix transfers loads and protects the fibers. Different types of reinforcements and mat
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INTRO TO FBA
Explore the foundational principles of Applied Behavior Analysis (ABA) through the lens of behaviorism, beginning with B.F. Skinner's theories on observable behavior. Learn about positive reinforcement, negative reinforcement, positive punishment, and negative punishment, and how these concepts shap
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Basic Learning Processes
Explore the essential vocabulary related to operant learning and reinforcement, including terms like automatic reinforcer, conditioned reinforcer, and positive reinforcement. Gain insights into theories such as drive-reduction theory and response-deprivation theory. Enhance your knowledge of behavio
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Adventure Awaits- Find Your Deep Creek Rental for All-Season Fun
Unleash your inner child at Deep Creek Lake! Beyond the serenity of nature and outdoor thrills, Deep Creek Lake offers a haven for family fun. Deep Creek Lake rentals with spacious living areas and game rooms provide the perfect space for creating lasting memories. Splash together at the lake's sand
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Exploring Symbolic Equations with Deep Learning by Shirley Ho at ACM Learning Event
Join Shirley Ho at the ACM Learning event to delve into the world of symbolic equations with deep learning. Discover insights on leveraging deep learning for symbolic equations and engage in a knowledge-packed session tailored for scientists, programmers, designers, and managers.
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Advanced Reinforcement Learning for Autonomous Robots
Cutting-edge research in the field of reinforcement learning for autonomous robots, focusing on Proximal Policy Optimization Algorithms, motivation for autonomous learning, scalability challenges, and policy gradient methods. The discussion delves into Markov Decision Processes, Actor-Critic Algorit
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Precision Oncology Research using Deep Learning Models
Lujia Chen, a Postdoc Associate at the University of Pittsburgh, focuses on developing deep learning models for precision oncology. By utilizing machine learning, especially deep learning models, Chen aims to identify cancer signaling pathways, predict drug sensitivities, and personalize cancer trea
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Deep Reinforcement Learning Overview and Applications
Delve into the world of deep reinforcement learning on the road to advanced AI systems like Skynet. Explore topics ranging from Markov Decision Processes to solving MDPs, value functions, and tabular solutions. Discover the paradigm of supervised, unsupervised, and reinforcement learning in various
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Exploring Machine Learning Applications in Enhancing 802.11 Performance
This document delves into recent research on utilizing machine learning (ML) to enhance 802.11 performance, focusing on emerging use cases and the increased interest in ML applications in the field since 2019. It outlines the ML areas frequently used, such as supervised learning (SL) and reinforceme
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Theories of Reinforcement in Behavioral Economics
Explore key theories of reinforcement including Thorndike's Law of Effect, Hull's Drive Reduction Theory, the Premack Principle, Response-Deprivation Hypothesis, and Behavioral Economics concepts such as Response Allocation. Learn about reinforcers as stimuli, primary and secondary reinforcers, the
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Batch Reinforcement Learning: Overview and Applications
Batch reinforcement learning decouples data collection and optimization, making it data-efficient and stable. It is contrasted with online reinforcement learning, highlighting the benefits of using a fixed set of experience to optimize policies. Applications of batch RL include medical treatment opt
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Token Economies and Behaviour Modification in Custody: Evaluating Efficacy
This article explores the application of token economies in prisons as a behaviour modification technique based on operant conditioning. Token economies involve exchanging tokens for desired behaviours, aiming to replace undesirable actions with positive reinforcement. The use of increments, consist
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Understanding Upper Limb Deep Tendon Reflexes Examination
Exploring the intricacies of upper limb deep tendon reflexes (DTR) examination, this comprehensive guide elaborates on the monosynaptic stretch reflex mechanism, protective role of stretch reflexes, grading of reflexes, factors influencing reflex activity, and reinforcement techniques like the Jendr
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Overview of Unsupervised Learning in Machine Learning
This presentation covers various topics in unsupervised learning, including clustering, expectation maximization, Gaussian mixture models, dimensionality reduction, anomaly detection, and recommender systems. It also delves into advanced supervised learning techniques, ensemble methods, structured p
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Seminar on Machine Learning with IoT Explained
Explore the intersection of Machine Learning and Internet of Things (IoT) in this informative seminar. Discover the principles, advantages, and applications of Machine Learning algorithms in the context of IoT technology. Learn about the evolution of Machine Learning, the concept of Internet of Thin
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Understanding Reinforcement and Association in Behavioral Psychology
This content delves into the concepts of reinforcement, association, and operant conditioning in behavioral psychology. It discusses how actions are influenced by rewards and consequences, the differences between association and reinforcement, and classical conditioning models like the Rescorla-Wagn
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Strategies for Effective Reinforcement in Training
Strategic reinforcement plays a crucial role in successful behavior training for animals. It involves planning each reward delivery to avoid additional behaviors and ensure smooth progress. Components like reward location and delivery method are essential for effective training. Safety consideration
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Results of Onshore and Offshore Composite Repair Studies Workshop Presentation
This presentation discusses the results of a recent study on the suitability of composite repair systems for structural reinforcement in onshore and offshore applications. The study investigated the impact of installation pressure and replication of offshore environments on the performance of these
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Improving Spelling Skills for Better Learning
Enhancing spelling skills is crucial for academic success. The program highlights the evolution of spelling education, emphasizing the progression from limited reinforcement to daily, multi-sensory teaching methods. Structured stages, such as Stage 1 focusing on initial sounds and phonemes, facilita
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Research on Producing Bio-Composite Materials from Wastewater Using Filamentous Bacteria and Polyhydroxyalkanoates
This project conducted at the University of Delaware aimed to evaluate the potential of using filamentous wastewater microorganisms as reinforcement and polyhydroxyalkanoates (PHA)-accumulating microorganisms as a biorenewable matrix for bio-composite materials. Filamentous bacteria were analyzed fo
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Supporting Positive Behavior in Alberta Schools: Key Elements and Strategies
This content discusses strategies for supporting positive behavior in schools, focusing on key elements such as positive relationships, learning environment, differentiated instruction, understanding student behavior, and social skills instruction. It emphasizes the importance of positive reinforcem
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Understanding Behavioral Intervention Strategies for Children
Exploring the concepts of behavior, reinforcement, punishment, and challenging behaviors in children, along with examples of behavior change strategies used in school settings such as activity schedules and reinforcement systems. Additionally, guidance on how to generalize these strategies in home a
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Exam Preparation Insights for Cumulative Material on Neural Networks and Machine Learning
Insights from various lectures and discussions focusing on deep learning, reinforcement learning, and advancements in AI. Emphasis on moving beyond input-output views to richer internal representations and the integration of deep learning with symbolic reasoning. Highlighting the success in sensory
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Introduction to Reinforcement Learning in Artificial Intelligence
Reinforcement learning offers a different approach to problem-solving by learning the right moves in various states rather than through exhaustive searching. This concept, dating back to the 1960s, involves mimicking successful behaviors observed in agents, humans, or programs. The basic implementat
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Understanding Machine Learning: A Comprehensive Overview
Machine learning has evolved significantly over the decades, driven by concepts like Neural Networks, Reinforcement Learning, and Deep Learning. This technology enables machines to learn from past data to make predictions. Activities in machine learning involve data exploration, preparation, model t
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Introduction to Machine Learning in BMTRY790 Course
The BMTRY790 course on Machine Learning covers a wide range of topics including supervised, unsupervised, and reinforcement learning. The course includes homework assignments, exams, and a real-world project to apply learned methods in developing prediction models. Machine learning involves making c
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Introduction to Keras for Deep Learning
Introduction to the world of deep learning with Keras, a popular deep learning library developed by François Chollet. Learn about Keras, Theano, TensorFlow, and how to train neural networks for tasks like handwriting digit recognition using the MNIST dataset. Explore different activation functions,
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Understanding Avoidance Behavior and Its Theories
Avoidance behavior involves negative reinforcement to increase the frequency of operant responses, not punishment. Different types of avoidance tests, such as discriminated avoidance and shuttle avoidance, are used to study negative reinforcement. The Two-Factor Theory of avoidance conditioning expl
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Denoising-Oriented Deep Hierarchical Reinforcement Learning for Next-basket Recommendation
This research paper presents a novel approach, HRL4Ba, for Next-basket Recommendation (NBR) by addressing the challenge of guiding recommendations based on historical baskets that may contain noise products. The proposed Hierarchical Reinforcement Learning framework incorporates dynamic context mode
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Understanding Behavior Establishment and Extinction in Inclusive Education
Behavior establishment and extinction are crucial concepts in the field of inclusive education. Behaviors are reinforced based on antecedents and consequences, with extinction occurring when reinforcement is discontinued. Different types of extinction target behaviors maintained by positive or negat
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Understanding Online Learning in Machine Learning
Explore the world of online learning in machine learning through topics like supervised learning, unsupervised learning, and more. Dive into concepts such as active learning, reinforcement learning, and the challenges of changing data distributions over time.
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Understanding Plain & Reinforced Concrete Structures
Concrete is a vital construction material, with Plain Cement Concrete (PCC) and Reinforced Cement Concrete (RCC) being common types. PCC lacks reinforcement and is strong in compression but weak in tension. On the other hand, RCC combines concrete with steel reinforcement for improved tensile streng
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Denoising-Guided Deep Reinforcement Learning for Social Recommendation
This research introduces a Denoising-Guided Deep Reinforcement Learning framework, DRL4So, for enhancing social recommendation systems. By automatically masking noise from social friends to improve recommendation performance, this framework focuses on maximizing the positive utility of social denois
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Evolution of Machine Learning and Deep Learning in AI
Exploring the evolution of machine learning and deep learning in artificial intelligence through neural networks, with insights on supervised, unsupervised, and reinforcement learning. Learn about recommended resources like Java Weka and Python scikit-learn for data mining tasks. Delve into advancem
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Exploring Sports and Deep Tissue Massage Techniques
In this lesson plan, students will delve into the world of sports and deep tissue massage, learning about the theoretical aspects, hands-on techniques, and graded events involved. The content covers classroom rules, the introduction to sports and deep tissue massage, an overview of the segment class
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Quantum Deep Learning: Challenges and Opportunities in Artificial Intelligence
Quantum deep learning explores the potential of using quantum computing to address challenges in artificial intelligence, focusing on learning complex representations for tough AI problems. The quest is to automatically learn representations at both low and high levels, leveraging terabytes of web d
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Drone Collision Avoidance Simulator for Autonomous Maneuvering
Our project focuses on developing a drone collision avoidance simulator using NEAT and Deep Reinforcement Learning techniques. We aim to create a model that can maneuver obstacles in a 2D environment, enhancing performance and survivability. Previous attempts utilizing non-machine learning solutions
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