Challenges in machine generation of analytic products from multi-source data proceedings of a workshop / Linda Casola, rapporteur ; Intelligence Community Studies Board, Division on Engineering and Physical Sciences, The National Academies of Science, Engineering, Medicine.
| Author/creator | Challenges in machine generation of analytic products from multi-source data (Workshop) |
| Format | Electronic |
| Publication Info | Washington, DC : National Academies Press, [2017] |
| Description | x, 59 pages : illustrations (chiefly color) ; 28 cm |
| Supplemental Content | Full text available from Ebook Central - Academic Complete |
| Subjects |
| Other author/creator | Casola, Linda Clare, 1982- |
| Other author/creator | National Academies of Sciences, Engineering, and Medicine (U.S.) |
| Other author/creator | National Academies of Sciences, Engineering, and Medicine (U.S.), Intelligence Community Studies Board. |
| Other author/creator | National Academies of Sciences, Engineering, and Medicine (U.S.). Division on Engineering and Physical Sciences. |
| Contents | Session I. Plenary -- Session 2. Machine learning from image, video, and map data -- Session 3. Machine learning from natural languages -- Session 4. Learning from multi-source data -- Session 5. Learning from noisy, adversarial inputs -- Session 6. Learning from social media -- Session 7. Humans and machines working together with big data -- Session 8. Use of machine learning for privacy ethics -- Session 9. Evaluation of machine-generated products -- Session 10. Capability technology matrix. |
| Abstract | The Intelligence Community Studies Board of the National Academies of Sciences, Engineering, and Medicine convened a workshop on August 9-10, 2017 to examine challenges in machine generation of analytic products from multi-source data. Workshop speakers and participants discussed research challenges related to machine-based methods for generating analytic products and for automating the evaluation of these products, with special attention to learning from small data, using multi-source data, adversarial learning, and understanding the human-machine relationship. This publication summarizes the presentations and discussions from the workshop. |
| Bibliography note | Includes bibliographical references. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| LCCN | 2018302157 |
| ISBN | 0309465737 paperback |
| ISBN | 9780309465731 paperback |