Learning One More Thing

Learning One More Thing (1994)

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by Sebastian Thrun , Tom M. Mitchell

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@TECHREPORT{Thrun94learningone,
    author = {Sebastian Thrun and Tom M. Mitchell},
    title = {Learning One More Thing},
    institution = {},
    year = {1994}
}

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Abstract

Most research on machine learning has focused on scenarios in which a learner faces a single, isolated learning task. The lifelong learning frameworkassumes instead that the learner encounters a multitude of related learning tasks over its lifetime, providing the opportunity for the transfer of knowledge. This paper studies lifelong learning in the context of binary classification. It presents the invariance approach, in which knowledge is transferred via a learned model of the invariances of the domain. Results on learning to recognize objects from color images demonstrate superior generalization capabilities if invariances are learned and used to bias subsequent learning. This research is sponsored in part by the National Science Foundation under award IRI-9313367, and by the Wright Laboratory, Aeronautical Systems Center, Air Force Materiel Command, USAF, and the Advanced Research Projects Agency (ARPA) under grant number F33615-93-1-1330. Views and conclusions contained in this doc...

Citations

2888	Induction of Decision Trees - Quinlan - 1986
2304	Learning Internal Representations by Error Propagation - Rumelhart, Hinton, et al. - 1986
605	Learning quickly when irrelevant attributes abound: A new linear-threshold algorithm - Littlestone - 1988
472	Learning to act using real-time dynamic programming - Barto, Bradtke, et al. - 1995
427	Integrated architectures for learning, planning, and reacting based on approximating integrated architectures for learning, planning, and reacting based on approximating dynamic programming - Sutton - 1990
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100	Alvinn: An autonomous land vehicle in a neural network - Pomerleau - 1989
94	Explanation-Based Neural Network Learning: A Lifelong Learning Approach - Thrun - 1996
71	Hoeffding races: Accelerating model selection search for classification and function approximation - Maron, Moore - 1993
63	Tangent prop - A formalism for specifying selected invariances in an adaptive network - Simard, Victorri, et al. - 1992
62	Adapting bias by gradient descent: An incremental version of deltabar-delta - Sutton - 1992
56	Multitask learning: A knowledge-based source of inductive bias - Caruana - 1997
42	An empirical investigation of brute force to choose features, smoothers, and function approximators - Moore, Hill, et al. - 1992
38	Discriminability-Based Transfer between Neural Networks - Pratt - 1993
31	Using locally weighted regression for robot learning - Atkeson - 1991
28	Generalization from a single view in face recognition - Lando, Edelman - 1995
22	Rule-injection Hints as a Means of Improving Network Performance and Learning Time - Suddarth, Kergosien - 1990
19	Layered concept-learning and dynamically-variable bias management - Rendell, Seshu, et al. - 1987
12	Lifelong robot learning. Robotics and Autonomous Systems - Thrun, Mitchell - 1993
11	Adaptive generalization and the transfer of knowledge - Sharkey, Sharkey - 1992
10	Multi-speaker/speaker-independent architectures for the multi-state time delay neural network - Hild, Waibel - 1993
8	A lifelong learning perspective for mobile robot control - Thrun - 1994
5	Explanationbased learning for mobile robot perception - Mitchell, Thrun - 1994
1	The canonical metric for vector quantization. submitted for publication - Baxter - 1995
1	Explanation-basedneural network learning from mobile robot perception - O’Sullivan, Mitchell, et al. - 1995