Kagan Tumer

2008
46	EE	Nikunj C. Oza, Kagan Tumer: Applications of ensemble methods. Information Fusion 9(1): 2-3 (2008)
45	EE	Nikunj C. Oza, Kagan Tumer: Classifier ensembles: Select real-world applications. Information Fusion 9(1): 4-20 (2008)
2007
44	EE	Kagan Tumer, Adrian K. Agogino: Distributed agent-based air traffic flow management. AAMAS 2007: 255
43	EE	Adrian K. Agogino, Kagan Tumer: Evolving distributed agents for managing air traffic. GECCO 2007: 1888-1895
42	EE	Kagan Tumer, Adrian K. Agogino: Evolving Multi Rover Systems in Dynamic and Noisy Environments. Evolutionary Computation in Dynamic and Uncertain Environments 2007: 371-387
2006
41		Adrian K. Agogino, Kagan Tumer: QUICR-Learning for Multi-Agent Coordination. AAAI 2006
40	EE	Adrian K. Agogino, Kagan Tumer: Efficient agent-based cluster ensembles. AAMAS 2006: 1079-1086
39	EE	Kagan Tumer: Coordinating simple and unreliable agents. AAMAS 2006: 1119-1121
38	EE	Nachi Gupta, Adrian K. Agogino, Kagan Tumer: Efficient agent-based models for non-genomic evolution. AAMAS 2006: 58-64
37	EE	Adrian K. Agogino, Kagan Tumer: Distributed evaluation functions for fault tolerant multi-rover systems. GECCO 2006: 1079-1086
36	EE	Adrian K. Agogino, Kagan Tumer: Handling Communication Restrictions and Team Formation in Congestion Games. Autonomous Agents and Multi-Agent Systems 13(1): 97-115 (2006)
2005
35	EE	Adrian K. Agogino, Kagan Tumer, Risto Miikkulainen: Efficient credit assignment through evaluation function decomposition. GECCO 2005: 1309-1316
34	EE	Kagan Tumer, Adrian K. Agogino: Coordinating multi-rover systems: evaluation functions for dynamic and noisy environments. GECCO 2005: 591-598
33	EE	Kagan Tumer, Adrian K. Agogino: Efficient Reward Functions for Adaptive Multi-rover Systems. LAMAS 2005: 177-191
2004
32	EE	Kagan Tumer, Adrian K. Agogino: Time-Extended Policies in Multi-Agent Reinforcement Learning. AAMAS 2004: 1338-1339
31	EE	Adrian K. Agogino, Kagan Tumer: Unifying Temporal and Structural Credit Assignment Problems. AAMAS 2004: 980-987
30	EE	Adrian K. Agogino, Kagan Tumer: Efficient Evaluation Functions for Multi-rover Systems. GECCO (1) 2004: 1-11
2003
29	EE	Kagan Tumer, John W. Lawson: Collectives for multiple resource job scheduling across heterogeneous servers. AAMAS 2003: 1142-1143
28	EE	Adrian K. Agogino, Kagan Tumer: Team formation and communication restrictions in collectives. AAMAS 2003: 916-917
27	EE	Stéphane Airiau, Sandip Sen, David Wolpert, Kagan Tumer: Providing Effective Access to Shared Resources: A COIN Approach. Engineering Self-Organising Systems 2003: 249-264
26	EE	Nikunj C. Oza, Kagan Tumer, Irem Y. Tumer, Edward M. Huff: Classification of Aircraft Maneuvers for Fault Detection. Multiple Classifier Systems 2003: 375-384
25	EE	Kagan Tumer, David Wolpert: Collectives for the Optimal Combination of Imperfect Objects CoRR cond-mat/0301459: (2003)
24	EE	David Wolpert, Kagan Tumer, Esfandiar Bandari: Improving Search Algorithms by Using Intelligent Coordinates CoRR math.OC/0301268: (2003)
23	EE	Kagan Tumer, Nikunj C. Oza: Input decimated ensembles. Pattern Anal. Appl. 6(1): 65-77 (2003)
2002
22	EE	Kagan Tumer, Adrian K. Agogino, David Wolpert: Learning sequences of actions in collectives of autonomous agents. AAMAS 2002: 378-385
21		Jussi Karlgren, Pentti Kanerva, Björn Gambäck, Kenneth D. Forbus, Kagan Tumer, Peter Stone, Kai Goebel, Gaurav S. Sukhatme, Tucker R. Balch, Bernd Fischer, Doug Smith, Sanda M. Harabagiu, Vinay Chaudri, Mike Barley, Hans W. Guesgen, Thomas F. Stahovich, Randall Davis, James A. Landay: The 2002 AAAI Spring Symposium Series. AI Magazine 23(4): 101-106 (2002)
20	EE	David Wolpert, Kagan Tumer: Collective Intelligence, Data Routing and Braess' Paradox. J. Artif. Intell. Res. (JAIR) 16: 359-387 (2002)
19	EE	Kagan Tumer, Joydeep Ghosh: Robust Combining of Disparate Classifiers through Order Statistics. Pattern Anal. Appl. 5(2): 189-200 (2002)
2001
18		David Wolpert, Joseph Sill, Kagan Tumer: Reinforcement Learning in Distributed Domains: Beyond Team Games. IJCAI 2001: 819-824
17	EE	Nikunj C. Oza, Kagan Tumer: Input Decimation Ensembles: Decorrelation through Dimensionality Reduction. Multiple Classifier Systems 2001: 238-247
2000
16		Kagan Tumer, David Wolpert: Collective Intelligence and Braess' Paradox. AAAI/IAAI 2000: 104-109
15	EE	David Wolpert, Sergey Kirshner, Christopher J. Merz, Kagan Tumer: Adaptivity in agent-based routing for data networks. Agents 2000: 396-403
1999
14	EE	David Wolpert, Kevin R. Wheeler, Kagan Tumer: General Principles of Learning-Based Multi-Agent Systems. Agents 1999: 77-83
13	EE	Kagan Tumer, David Wolpert: Avoiding Braess' Paradox through Collective Intelligence CoRR cs.DC/9912012: (1999)
12	EE	David Wolpert, Kagan Tumer, Jeremy Frank: Using Collective Intelligence to Route Internet Traffic CoRR cs.LG/9905004: (1999)
11	EE	Kagan Tumer, Joydeep Ghosh: Robust Combining of Disparate Classifiers through Order Statistics CoRR cs.LG/9905013: (1999)
10	EE	David Wolpert, Kevin R. Wheeler, Kagan Tumer: Collective Intelligence for Control of Distributed Dynamical Systems CoRR cs.LG/9908013: (1999)
9	EE	David Wolpert, Kagan Tumer: An Introduction to Collective Intelligence CoRR cs.LG/9908014: (1999)
8	EE	David Wolpert, Kevin R. Wheeler, Kagan Tumer: General Principles of Learning-Based Multi-Agent Systems CoRR cs.MA/9905005: (1999)
7	EE	David Wolpert, Sergey Kirshner, Christopher J. Merz, Kagan Tumer: Adaptivity in Agent-Based Routing for Data Networks CoRR cs.MA/9912011: (1999)
6	EE	Kagan Tumer, Nirmala Ramanujam, Joydeep Ghosh, Rebecca R. Richards-Kortum: Ensembles of Radial Basis Function Networks for Spectroscopic Detection of Cervical Pre-Cancer CoRR cs.NE/9905011: (1999)
5	EE	Kagan Tumer, Joydeep Ghosh: Linear and Order Statistics Combiners for Pattern Classification CoRR cs.NE/9905012: (1999)
1996
4	EE	Kagan Tumer, Nirmala Ramanujam, Rebecca R. Richards-Kortum, Joydeep Ghosh: Spectroscopic Detection of Cervical Pre-Cancer through Radial Basis Function Networks. NIPS 1996: 981-987
3	EE	Kagan Tumer, Joydeep Ghosh: Error Correlation and Error Reduction in Ensemble Classifiers. Connect. Sci. 8(3): 385-404 (1996)
2	EE	Kagan Tumer, Joydeep Ghosh: Analysis of decision boundaries in linearly combined neural classifiers. Pattern Recognition 29(2): 341-348 (1996)
1994
1	EE	Kagan Tumer, Joydeep Ghosh: Sequence Recognition by Input Anticipation. IEA/AIE 1994: 77-86

Coauthor Index

1	Adrian K. Agogino	[22] [28] [30] [31] [32] [33] [34] [35] [36] [37] [38] [40] [41] [42] [43] [44]
2	Stéphane Airiau	[27]
3	Tucker R. Balch	[21]
4	Esfandiar Bandari	[24]
5	Mike Barley	[21]
6	Vinay Chaudri	[21]
7	Randall Davis	[21]
8	Bernd Fischer	[21]
9	Kenneth D. Forbus	[21]
10	Jeremy Frank	[12]
11	Björn Gambäck	[21]
12	Joydeep Ghosh	[1] [2] [3] [4] [5] [6] [11] [19]
13	Kai Goebel	[21]
14	Hans W. Guesgen	[21]
15	Nachi Gupta	[38]
16	Sanda M. Harabagiu	[21]
17	Edward M. Huff	[26]
18	Pentti Kanerva	[21]
19	Jussi Karlgren	[21]
20	Sergey Kirshner	[7] [15]
21	James A. Landay	[21]
22	John W. Lawson	[29]
23	Christopher J. Merz	[7] [15]
24	Risto Miikkulainen	[35]
25	Nikunj C. Oza	[17] [23] [26] [45] [46]
26	Nirmala Ramanujam	[4] [6]
27	Rebecca R. Richards-Kortum	[4] [6]
28	Sandip Sen	[27]
29	Joseph Sill	[18]
30	Doug Smith	[21]
31	Thomas F. Stahovich	[21]
32	Peter Stone	[21]
33	Gaurav S. Sukhatme (Gaurav Sukhatme)	[21]
34	Irem Y. Tumer	[26]
35	Kevin R. Wheeler	[8] [10] [14]
36	David Wolpert (David H. Wolpert)	[7] [8] [9] [10] [12] [13] [14] [15] [16] [18] [20] [22] [24] [25] [27]

Colors in the list of coauthors