Human Computation by Edith Law
Introduction.- Human Computation Algorithms.- Aggregating Outputs.- Task Routing.- Understanding Workers and Requesters.- The Art of Asking Questions.- The Future of Human Computation.-
Graph Representation Learning
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A Concise Introduction to Models and Methods for Automated Planning
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Learning with Support Vector Machines
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A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence
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Reasoning with Probabilistic and Deterministic Graphical Models
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Action Programming Languages
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Learning and Decision-Making from Rank Data
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Explainable Human-AI Interaction
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Network Embedding
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Predicting Human Decision-Making
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Game Theory for Data Science
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Strategic Voting
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Statistical Relational Artificial Intelligence
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A Short Introduction to Preferences
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Case-Based Reasoning
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Representing and Reasoning with Qualitative Preferences
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Robot Learning from Human Teachers
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Visual Object Recognition
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General Game Playing
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Essential Principles for Autonomous Robotics
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Federated Learning
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Graph-Based Semi-Supervised Learning
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An Introduction to Constraint-Based Temporal Reasoning
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Intelligent Autonomous Robotics
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Answer Set Solving in Practice
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Representation Discovery using Harmonic Analysis
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Representations and Techniques for 3D Object Recognition and Scene Interpretation
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Introduction to Intelligent Systems in Traffic and Transportation
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Introduction to Symbolic Plan and Goal Recognition
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Judgment Aggregation
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Metric Learning
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Data Integration
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Trading Agents
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Introduction to Semi-Supervised Learning
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Transfer Learning for Multiagent Reinforcement Learning Systems
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Introduction to Graph Neural Networks
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Introduction to Logic Programming
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An Introduction to the Planning Domain Definition Language
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Lifelong Machine Learning, Second Edition
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Adversarial Machine Learning
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Multi-Objective Decision Making
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Active Learning
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Planning with Markov Decision Processes
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Computational Aspects of Cooperative Game Theory
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Algorithms for Reinforcement Learning
Edith Law is a Ph.D. candidate at Carnegie Mellon University, who is doing research on human computation systems that harness the joint efforts of machines and humans, with a focus on games with a purpose and citizen science. She is the co-organizers of the 1st and 3rd human computation workshops (HCOMP2009 andHCOMP2011), and the recipient of Microsoft Graduate Research Fellowship 2009-2011. Her work on TagATune has received a best paper nomination at CHI 2009.
Luis von Ahn is the A. Nico Habermann Associate Professor in the Computer Science Department at Carnegie Mellon University. His current research interests include building systems that combine the intelligence of humans and computers to solve large-scale problems that neither can solve alone. An example of his work is reCAPTCHA, in which over 750 million people—more than 10% of humanity—have helped digitize books and newspapers. He is the recipient of a MacArthur Fellowship, a Packard Fellowship, a Microsoft New Faculty Fellowship, and a Sloan Research Fellowship. He has been named one of the 50 Best Minds in Science by Discover Magazine, one of the 100 Most Creative People in Business of 2010 by Fast Company Magazine, and one of the “Brilliant 10" scientists of 2006 by Popular Science Magazine.
Luis von Ahn is the A. Nico Habermann Associate Professor in the Computer Science Department at Carnegie Mellon University. His current research interests include building systems that combine the intelligence of humans and computers to solve large-scale problems that neither can solve alone. An example of his work is reCAPTCHA, in which over 750 million people—more than 10% of humanity—have helped digitize books and newspapers. He is the recipient of a MacArthur Fellowship, a Packard Fellowship, a Microsoft New Faculty Fellowship, and a Sloan Research Fellowship. He has been named one of the 50 Best Minds in Science by Discover Magazine, one of the 100 Most Creative People in Business of 2010 by Fast Company Magazine, and one of the “Brilliant 10" scientists of 2006 by Popular Science Magazine.
| SKU | Unavailable |
| ISBN 13 | 9783031004278 |
| ISBN 10 | 3031004272 |
| Title | Human Computation |
| Author | Edith Law |
| Series | Synthesis Lectures On Artificial Intelligence And Machine Learning |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer International Publishing AG |
| Year published | 2011-06-30 |
| Number of pages | 105 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |