메뉴 건너뛰기




Volumn 27, Issue 1, 2014, Pages 11-23

A tour of machine learning: An AI perspective

Author keywords

Change of representation; Machine Learning; Machine reasoning; Reinforcement learning; Statistical learning; Unsupervised learning

Indexed keywords

CHANGE OF REPRESENTATION; HISTORICAL PERSPECTIVE; STATISTICAL LEARNING;

EID: 84889678199     PISSN: 09217126     EISSN: None     Source Type: Journal    
DOI: 10.3233/AIC-130580     Document Type: Review
Times cited : (11)

References (103)
  • 1
    • 14344251217 scopus 로고    scopus 로고
    • Apprenticeship learning via inverse reinforcement learning
    • C.E. Brodley, ed., ACM International Conf. Proc. Series, ACM
    • P. Abbeel and A.Y. Ng, Apprenticeship learning via inverse reinforcement learning, in: Proc. of Int. Conf. on Machine Learning, C.E. Brodley, ed., ACM International Conf. Proc. Series, Vol. 69, ACM, 2004.
    • (2004) Proc. of Int. Conf. on Machine Learning , vol.69
    • Abbeel, P.1    Ng, A.Y.2
  • 3
    • 0017392285 scopus 로고
    • Neural theory of association and concept formation
    • S.-I. Amari, Neural theory of association and concept formation, Biological Cybernetics 26 (1977), 175-185.
    • (1977) Biological Cybernetics , vol.26 , pp. 175-185
    • Amari, S.-I.1
  • 4
    • 0001492549 scopus 로고    scopus 로고
    • Shape quantization and recognition with randomized trees
    • Y. Amit and D. Geman, Shape quantization and recognition with randomized trees, Neural Computation 9 (1997), 1545-1588.
    • (1997) Neural Computation , vol.9 , pp. 1545-1588
    • Amit, Y.1    Geman, D.2
  • 5
    • 0036568025 scopus 로고    scopus 로고
    • Finite-time analysis of the multiarmed bandit problem
    • P. Auer, N. Cesa-Bianchi and P. Fischer, Finite-time analysis of the multiarmed bandit problem, Machine Learning 47(2) (2002), 235-256.
    • (2002) Machine Learning , vol.47 , Issue.2 , pp. 235-256
    • Auer, P.1    Cesa-Bianchi, N.2    Fischer, P.3
  • 14
    • 84896288278 scopus 로고    scopus 로고
    • Embracing uncertainty: Applied machine learning comes of age
    • Part I, D. Gunopulos, T. Hofmann, D. Malerba and M. Vazirgiannis, eds, Lecture Notes in Computer Science, Springer
    • C.M. Bishop, Embracing uncertainty: Applied machine learning comes of age, in: Machine Learning and Knowledge Discovery in Databases, Part I, D. Gunopulos, T. Hofmann, D. Malerba and M. Vazirgiannis, eds, Lecture Notes in Computer Science, Vol. 6911, Springer, 2011.
    • (2011) Machine Learning and Knowledge Discovery in Databases , vol.6911
    • Bishop, C.M.1
  • 17
    • 84861473762 scopus 로고    scopus 로고
    • The promise and peril of big data
    • The Aspen Institute
    • D. Bollier, The promise and peril of big data, Technical report, The Aspen Institute, 2010.
    • (2010) Technical Report
    • Bollier, D.1
  • 19
    • 84860616509 scopus 로고    scopus 로고
    • From machine learning to machine reasoning
    • L. Bottou, From machine learning to machine reasoning, CoRR (2011), available at: abs/1102.1808.
    • (2011) CoRR
    • Bottou, L.1
  • 20
    • 85162035281 scopus 로고    scopus 로고
    • The tradeoffs of large scale learning
    • C. Platt, D. Koller, Y. Singer and S.T. Roweis, eds
    • L. Bottou and O. Bousquet, The tradeoffs of large scale learning, in: Advances in Neural Information Processing Systems, C. Platt, D. Koller, Y. Singer and S.T. Roweis, eds, 2007.
    • (2007) Advances in Neural Information Processing Systems
    • Bottou, L.1    Bousquet, O.2
  • 21
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • L. Breiman, Random forests, Machine Learning 45(1) (2001), 5-32.
    • (2001) Machine Learning , vol.45 , Issue.1 , pp. 5-32
    • Breiman, L.1
  • 24
    • 34047173490 scopus 로고    scopus 로고
    • On learning, representing and generalizing a task in a humanoid robot
    • Part B, (Special issue on robot learning by observation, demonstration and imitation.)
    • S. Calinon, F. Guenter and A. Billard, On learning, representing and generalizing a task in a humanoid robot, IEEE Transactions on Systems, Man and Cybernetics, Part B 37(2) (2007), 286-298. (Special issue on robot learning by observation, demonstration and imitation.)
    • (2007) IEEE Transactions on Systems, Man and Cybernetics , vol.37 , Issue.2 , pp. 286-298
    • Calinon, S.1    Guenter, F.2    Billard, A.3
  • 25
    • 33745604236 scopus 로고    scopus 로고
    • Stable signal recovery from incomplete and inaccurate measurements
    • E.J. Candès, J. Romberg and T. Tao, Stable signal recovery from incomplete and inaccurate measurements, Comm. Pure Appl. Math. 59 (2006), 1207-1223.
    • (2006) Comm. Pure Appl. Math. , vol.59 , pp. 1207-1223
    • Candès, E.J.1    Romberg, J.2    Tao, T.3
  • 28
    • 43949172137 scopus 로고
    • Situated action: A neuropsychological interpretation response to Vera and Simon
    • W.J. Clancey, Situated action: A neuropsychological interpretation response to Vera and Simon, Cognitive Science 17 (1993), 87-116.
    • (1993) Cognitive Science , vol.17 , pp. 87-116
    • Clancey, W.J.1
  • 29
    • 56449095373 scopus 로고    scopus 로고
    • A unified architecture for natural language processing: Deep neural networks with multitask learning
    • W.W. Cohen, A. McCallum and S.T. Roweis, eds, ACM International Conference Proceeding Series, ACM
    • R. Collobert and J. Weston, A unified architecture for natural language processing: deep neural networks with multitask learning, in: Proc. of Int. Conf. on Machine Learning, W.W. Cohen, A. McCallum and S.T. Roweis, eds, ACM International Conference Proceeding Series, Vol. 307, ACM, 2008, pp. 160-167.
    • (2008) Proc. of Int. Conf. on Machine Learning , vol.307 , pp. 160-167
    • Collobert, R.1    Weston, J.2
  • 30
    • 84889673105 scopus 로고    scopus 로고
    • Are we there yet?
    • W.L. Buntine, M. Grobelnik, D. Mladenic and J. Shawe-Taylor, eds, Lecture Notes in Computer Science, Springer
    • N. Cristianini, Are we there yet?, in: Eur. Conf. on Machine Learning and Knowledge Discovery in Databases, W.L.Buntine, M. Grobelnik, D. Mladenic and J. Shawe-Taylor, eds, Lecture Notes in Computer Science, Vol. 5781, Springer,2009.
    • (2009) Eur. Conf. on Machine Learning and Knowledge Discovery in Databases , vol.5781
    • Cristianini, N.1
  • 32
    • 84899009769 scopus 로고    scopus 로고
    • Global versus local methods in nonlinear dimensionality reduction
    • S. Becker, S. Thrun and K. Obermayer, eds
    • V. de Silva and J. Tenenbaum, Global versus local methods in nonlinear dimensionality reduction, in: Advances in Neural Information Processing Systems, S. Becker, S. Thrun and K. Obermayer, eds, 2003, pp. 721-728.
    • (2003) Advances in Neural Information Processing Systems , pp. 721-728
    • De Silva, V.1    Tenenbaum, J.2
  • 33
    • 0000259511 scopus 로고    scopus 로고
    • Approximate statistical tests for comparing supervised classification learning algorithms
    • T.G. Dietterich, Approximate statistical tests for comparing supervised classification learning algorithms, Neural Computation 10(7) (1998), 1895-1923.
    • (1998) Neural Computation , vol.10 , Issue.7 , pp. 1895-1923
    • Dietterich, T.G.1
  • 34
    • 48349140736 scopus 로고    scopus 로고
    • Rollout sampling approximate policy iteration
    • C. Dimitrakakis and M.G. Lagoudakis, Rollout sampling approximate policy iteration, Machine Learning 72(3) (2008), 157-171.
    • (2008) Machine Learning , vol.72 , Issue.3 , pp. 157-171
    • Dimitrakakis, C.1    Lagoudakis, M.G.2
  • 36
    • 0002978642 scopus 로고    scopus 로고
    • Experiments with a new boosting algorithm
    • L. Saitta, ed., Morgan Kaufmann
    • Y. Freund and R.E. Shapire, Experiments with a new boosting algorithm, in: Proc. of Int. Conf. on Machine Learning, L. Saitta, ed., Morgan Kaufmann, 1996, pp. 148-156.
    • (1996) Proc. of Int. Conf. on Machine Learning , pp. 148-156
    • Freund, Y.1    Shapire, R.E.2
  • 37
    • 33847172327 scopus 로고    scopus 로고
    • Clustering by passing messages between data points
    • B.J. Frey and D. Dueck, Clustering by passing messages between data points, Science 315 (2007), 972-976.
    • (2007) Science , vol.315 , pp. 972-976
    • Frey, B.J.1    Dueck, D.2
  • 39
    • 77953470265 scopus 로고    scopus 로고
    • Scaling analysis of affinity propagation
    • C. Furtlehner, M. Sebag and X. Zhang, Scaling analysis of affinity propagation, Phys. Rev. E 81(6) (2010).
    • (2010) Phys. Rev. e , vol.81 , Issue.6
    • Furtlehner, C.1    Sebag, M.2    Zhang, X.3
  • 40
    • 34547990649 scopus 로고    scopus 로고
    • Combining online and offline knowledge in UCT
    • Z. Ghahramani, ed., ACM
    • S. Gelly and D. Silver, Combining online and offline knowledge in UCT, in: Proc. of Int. Conf. on Machine Learning, Z. Ghahramani, ed., ACM, 2007, pp. 273-280.
    • (2007) Proc. of Int. Conf. on Machine Learning , pp. 273-280
    • Gelly, S.1    Silver, D.2
  • 45
    • 33745805403 scopus 로고    scopus 로고
    • A fast learning algorithm for deep belief nets
    • G.E. Hinton, S. Osindero and Y.-W. Teh, A fast learning algorithm for deep belief nets, Neural Computation 18 (2006), 1527-1554.
    • (2006) Neural Computation , vol.18 , pp. 1527-1554
    • Hinton, G.E.1    Osindero, S.2    Teh, Y.-W.3
  • 46
    • 84856827305 scopus 로고    scopus 로고
    • Programming by optimization
    • H.H. Hoos, Programming by optimization, Commun. ACM 55(2) (2012), 70-80.
    • (2012) Commun. ACM , vol.55 , Issue.2 , pp. 70-80
    • Hoos, H.H.1
  • 50
    • 33750293964 scopus 로고    scopus 로고
    • Bandit based Monte-Carlo planning
    • J. Fürnkranz, T. Scheffer and M. Spiliopoulou, eds, Springer
    • L. Kocsis and C. Szepesvári, Bandit based Monte-Carlo planning, in: Eur. Conf. on Machine Learning, J. Fürnkranz, T. Scheffer and M. Spiliopoulou, eds, Springer, 2006, pp. 282-293.
    • (2006) Eur. Conf. on Machine Learning , pp. 282-293
    • Kocsis, L.1    Szepesvári, C.2
  • 52
    • 85162033542 scopus 로고    scopus 로고
    • Constructing skill trees for reinforcement learning agents from demonstration trajectories
    • J.D. Lafferty, C.K.I. Williams, J. Shawe-Taylor, R.S. Zemel and A. Culotta, eds
    • G. Konidaris, S. Kuindersma, A. Barto and R. Grupen, Constructing skill trees for reinforcement learning agents from demonstration trajectories, in: Advances in Neural Information Processing Systems, J.D. Lafferty, C.K.I. Williams, J. Shawe-Taylor, R.S. Zemel and A. Culotta, eds, 2010, pp. 1162-1170.
    • (2010) Advances in Neural Information Processing Systems , pp. 1162-1170
    • Konidaris, G.1    Kuindersma, S.2    Barto, A.3    Grupen, R.4
  • 53
    • 0002899547 scopus 로고
    • Asymptotically efficient adaptive allocation rules
    • T. Lai and H. Robbins, Asymptotically efficient adaptive allocation rules, Advances in Applied Mathematics 6 (1985), 4-22.
    • (1985) Advances in Applied Mathematics , vol.6 , pp. 4-22
    • Lai, T.1    Robbins, H.2
  • 55
    • 0020191924 scopus 로고
    • The nature of heuristics
    • D.B. Lenat, The nature of heuristics, Artificial Intelligence 19(2) (1982), 189-249.
    • (1982) Artificial Intelligence , vol.19 , Issue.2 , pp. 189-249
    • Lenat, D.B.1
  • 56
    • 84871903843 scopus 로고    scopus 로고
    • Evolutionary robotics for legged machines: From simulation to physical reality
    • H. Lipson, J.C. Bongard, V. Zykov and E. Malone, Evolutionary robotics for legged machines: From simulation to physical reality, in: IAS, 2006, pp. 11-18.
    • (2006) IAS , pp. 11-18
    • Lipson, H.1    Bongard, J.C.2    Zykov, V.3    Malone, E.4
  • 57
    • 1942449765 scopus 로고    scopus 로고
    • Predictive representations of state
    • T.G. Dietterich, S. Becker and Z. Ghahramani, eds, MIT Press
    • M.L. Littman, R.S. Sutton and S.P. Singh, Predictive representations of state, in: Advances in Neural Information Processing Systems, T.G. Dietterich, S. Becker and Z. Ghahramani, eds, MIT Press, 2001, pp. 1555-1561.
    • (2001) Advances in Neural Information Processing Systems , pp. 1555-1561
    • Littman, M.L.1    Sutton, R.S.2    Singh, S.P.3
  • 59
    • 21944442464 scopus 로고    scopus 로고
    • Levelwise search and borders of theories in knowledge discovery
    • H. Mannila and H. Toivonen, Levelwise search and borders of theories in knowledge discovery, Data Mining and Knowledge Discovery 1(3) (1997), 241-258.
    • (1997) Data Mining and Knowledge Discovery , vol.1 , Issue.3 , pp. 241-258
    • Mannila, H.1    Toivonen, H.2
  • 60
    • 51249194645 scopus 로고
    • A logical calculus of the ideas immanent in nervous activity
    • W. McCulloch and W. Pitts, A logical calculus of the ideas immanent in nervous activity, Bulletin of Mathematical Biophysics 7 (1943), 115-133.
    • (1943) Bulletin of Mathematical Biophysics , vol.7 , pp. 115-133
    • McCulloch, W.1    Pitts, W.2
  • 61
    • 31844440880 scopus 로고    scopus 로고
    • Comparing clustering - An axiomatic view
    • L. De Raedt and S. Wrobel, eds
    • M. Meila, Comparing clustering - an axiomatic view, in: Proc. of Int. Conf. on Machine Learning, L. De Raedt and S. Wrobel, eds, 2005, pp. 577-584.
    • (2005) Proc. of Int. Conf. on Machine Learning , pp. 577-584
    • Meila, M.1
  • 62
    • 0003046840 scopus 로고
    • A theory and methodology of inductive learning
    • R.S. Michalski, J.G. Carbonell and T.M. Mitchell, eds, Morgan Kaufmann
    • R.S. Michalski, A theory and methodology of inductive learning, in: Machine Learning: An Artificial Intelligence Approach, R.S. Michalski, J.G. Carbonell and T.M. Mitchell, eds, Vol. 1, Morgan Kaufmann, 1983, pp. 83-134.
    • (1983) Machine Learning: An Artificial Intelligence Approach , vol.1 , pp. 83-134
    • Michalski, R.S.1
  • 65
  • 66
    • 0028429573 scopus 로고
    • Inductive logic programming: Theory and methods
    • S. Muggleton and L. De Raedt, Inductive logic programming: Theory and methods, Journal of Logic Programming 19 (1994), 629-679.
    • (1994) Journal of Logic Programming , vol.19 , pp. 629-679
    • Muggleton, S.1    De Raedt, L.2
  • 68
    • 0042547347 scopus 로고    scopus 로고
    • Algorithms for inverse reinforcement learning
    • P. Langley, ed., Morgan Kaufmann
    • A.Y. Ng and S. Russell, Algorithms for inverse reinforcement learning, in: Proc. of Int. Conf. on Machine Learning, P. Langley, ed., Morgan Kaufmann, 2000, pp. 663-670.
    • (2000) Proc. of Int. Conf. on Machine Learning , pp. 663-670
    • Ng, A.Y.1    Russell, S.2
  • 69
    • 37149013085 scopus 로고    scopus 로고
    • How to build consciousness into a robot: The sensorimotor approach
    • M. Lungarella, F. Iida, J.C. Bongard and R. Pfeifer, eds, Lecture Notes in Computer Science, Springer
    • J.K. O'Regan, How to build consciousness into a robot: The sensorimotor approach, in: 50 Years of Artificial Intelligence, M. Lungarella, F. Iida, J.C. Bongard and R. Pfeifer, eds, Lecture Notes in Computer Science, Vol. 4850, Springer, 2006, pp. 332-346.
    • (2006) 50 Years of Artificial Intelligence , vol.4850 , pp. 332-346
    • O'Regan, J.K.1
  • 72
    • 44949241322 scopus 로고    scopus 로고
    • Reinforcement learning of motor skills with policy gradients
    • J. Peters and S. Schaal, Reinforcement Learning of Motor Skills with Policy Gradients, Neural Networks 21(4) (2008), 682-697.
    • (2008) Neural Networks , vol.21 , Issue.4 , pp. 682-697
    • Peters, J.1    Schaal, S.2
  • 74
    • 33744584654 scopus 로고
    • Induction of decision trees
    • J.R. Quinlan, Induction of decision trees, Machine Learning 1 (1986), 81-106.
    • (1986) Machine Learning , vol.1 , pp. 81-106
    • Quinlan, J.R.1
  • 76
    • 0018015137 scopus 로고
    • Modeling by shortest data description
    • J. Rissanen, Modeling by shortest data description, Automatica 14 (1978), 465-471.
    • (1978) Automatica , vol.14 , pp. 465-471
    • Rissanen, J.1
  • 77
    • 11144273669 scopus 로고
    • The perceptron: A probabilistic model for information storage and organization in the brain
    • F. Rosenblatt, The perceptron: A probabilistic model for information storage and organization in the brain, Psychological Review 65(6) (1958), 386-408.
    • (1958) Psychological Review , vol.65 , Issue.6 , pp. 386-408
    • Rosenblatt, F.1
  • 78
    • 0034704222 scopus 로고    scopus 로고
    • Nonlinear dimensionality reduction by locally linear embedding
    • S. Roweis and L. Saul, Nonlinear dimensionality reduction by locally linear embedding, Science 290(5500) (2000), 2323-2326.
    • (2000) Science , vol.290 , Issue.5500 , pp. 2323-2326
    • Roweis, S.1    Saul, L.2
  • 81
    • 79958108958 scopus 로고    scopus 로고
    • Frequency-driven probabilities in quantitative causal analysis
    • F. Russo, Frequency-driven probabilities in quantitative causal analysis, Philosophical Writings 32 (2006), 32-49.
    • (2006) Philosophical Writings , vol.32 , pp. 32-49
    • Russo, F.1
  • 83
    • 0000058965 scopus 로고
    • Programming computers to play games
    • A.L. Samuel, Programming computers to play games, Advances in Computers 1 (1960), 165-192.
    • (1960) Advances in Computers , vol.1 , pp. 165-192
    • Samuel, A.L.1
  • 84
    • 0025448521 scopus 로고
    • The strength of weak learnability
    • R.E. Schapire, The strength of weak learnability, Machine Learning 5 (1990), 197.
    • (1990) Machine Learning , vol.5 , pp. 197
    • Schapire, R.E.1
  • 89
    • 0036147771 scopus 로고    scopus 로고
    • Programming backgammon using self-teaching neural nets
    • G. Tesauro, Programming backgammon using self-teaching neural nets, Artificial Intelligence 134(1,2) (2002), 181-199.
    • (2002) Artificial Intelligence , vol.134 , Issue.1-2 , pp. 181-199
    • Tesauro, G.1
  • 93
    • 0002988210 scopus 로고
    • Computing machinery and intelligence
    • A.M. Turing, Computing machinery and intelligence, Mind 49(236) (1950), 433-460.
    • (1950) Mind , vol.49 , Issue.236 , pp. 433-460
    • Turing, A.M.1
  • 94
    • 0021518106 scopus 로고
    • A theory of the learnable
    • L.G. Valiant, A theory of the learnable, Communication of the ACM 27 (1984), 1134-1142.
    • (1984) Communication of the ACM , vol.27 , pp. 1134-1142
    • Valiant, L.G.1
  • 96
    • 33646554819 scopus 로고    scopus 로고
    • Consistency and convergence rates of one-class SVMs and related algorithms
    • R. Vert and J.-P. Vert, Consistency and convergence rates of one-class SVMs and related algorithms, Journal of Machine Learning Research 7 (2006), 817-854.
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 817-854
    • Vert, R.1    Vert, J.-P.2
  • 97
    • 85162076891 scopus 로고    scopus 로고
    • Optimal bayesian recommendation sets and myopically optimal choice query sets
    • J.D. Lafferty, C.K.I. Williams, J. Shawe-Taylor, R.S. Zemel and A. Culotta, eds
    • P. Viappiani and C. Boutilier, Optimal Bayesian recommendation sets and myopically optimal choice query sets, in: Advances in Neural Information Processing Systems, J.D. Lafferty, C.K.I. Williams, J. Shawe-Taylor, R.S. Zemel and A. Culotta, eds, 2010, pp. 2352-2360.
    • (2010) Advances in Neural Information Processing Systems , pp. 2352-2360
    • Viappiani, P.1    Boutilier, C.2
  • 100
    • 84911514327 scopus 로고
    • Eliza - A computer program for the study of natural language communication between man and machine
    • J. Weizenbaum, Eliza - a computer program for the study of natural language communication between man and machine, Communications of the ACM 9(1) (1966), 36-45.
    • (1966) Communications of the ACM , vol.9 , Issue.1 , pp. 36-45
    • Weizenbaum, J.1
  • 101
    • 0001795753 scopus 로고
    • Generalization and information storage in networks of Adaline neurons
    • M.C. Yovits, G.T. Jacobi and G.D. Goldstein, eds, Spartan Books
    • B. Widrow, Generalization and information storage in networks of Adaline neurons, in: Self-Organizing Systems, M.C. Yovits, G.T. Jacobi and G.D. Goldstein, eds, Spartan Books, 1962.
    • (1962) Self-Organizing Systems
    • Widrow, B.1
  • 102
    • 0000027741 scopus 로고
    • Learning structural descriptions from examples
    • P.H. Winston, ed., McGraw Hill, New York
    • P.H. Winston, Learning structural descriptions from examples, in: The Psychology of Computer Vision, P.H. Winston, ed., McGraw Hill, New York, 1975, pp. 157-209.
    • (1975) The Psychology of Computer Vision , pp. 157-209
    • Winston, P.H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.