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Wolfgang Maass Vis

Technische Universität Graz, Austria

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*2009
163EEGerhard Neumann, Wolfgang Maass, Jan Peters: Learning complex motions by sequencing simpler motion templates. ICML 2009: 95
162EESabine Janzen, Wolfgang Maass: Ontology-Based Natural Language Processing for In-store Shopping Situations. ICSC 2009: 361-366
161EEStefan Klampfl, Robert A. Legenstein, Wolfgang Maass: Spiking Neurons Can Learn to Solve Information Bottleneck Problems and Extract Independent Components. Neural Computation 21(4): 911-959 (2009)
160EEAndreas Steimer, Wolfgang Maass, Rodney J. Douglas: Belief Propagation in Networks of Spiking Neurons. Neural Computation 21(9): 2502-2523 (2009)
2008
159 Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass: Recurrent Neural Networks - Models, Capacities, and Applications, 20.01. - 25.01.2008 Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany 2008
158EEBernhard Nessler, Michael Pfeiffer, Wolfgang Maass: Hebbian Learning of Bayes Optimal Decisions. NIPS 2008: 1169-1176
157EELuc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass: 08041 Abstracts Collection -- Recurrent Neural Networks - Models, Capacities, and Applications. Recurrent Neural Networks 2008
156EELuc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass: 08041 Summary -- Recurrent Neural Networks - Models, Capacities, and Applications. Recurrent Neural Networks 2008
155 Wolfgang Maass, Andreas Filler, Jan Seeburger: Product-Centered Mobile Reasoning Support for Physical Shopping Situations. TAMoCo 2008: 54-63
154EEWolfgang Maass, Upkar Varshney: Preface to the Focus Theme Section: 'Smart Products'. Electronic Markets 18(3): 211-215 (2008)
153EEDimitris Apostolou, Gregoris Mentzas, Bertin Klein, Andreas Abecker, Wolfgang Maass: Interorganizational Knowledge Exchanges. IEEE Intelligent Systems 23(4): 65-74 (2008)
152EERobert A. Legenstein, Wolfgang Maass: On the Classification Capability of Sign-Constrained Perceptrons. Neural Computation 20(1): 288-309 (2008)
151EEPeter Auer, Harald Burgsteiner, Wolfgang Maass: A learning rule for very simple universal approximators consisting of a single layer of perceptrons. Neural Networks 21(5): 786-795 (2008)
2007
150EEWolfgang Maass: Liquid Computing. CiE 2007: 507-516
149EEGerhard Neumann, Michael Pfeiffer, Wolfgang Maass: Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs. ECML 2007: 250-261
148EEWolfgang Maass, Tobias Kowatsch, Timo Münster: Vocabulary Patterns in Free-for-all Collaborative Indexing Systems. ESOE 2007: 45-57
147 Wolfgang Maass, Matthias Lampe: Integration of Standardized and Non-Standardized Product Data. GI Jahrestagung (1) 2007: 141-146
146EELars Buesing, Wolfgang Maass: Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking Neurons. NIPS 2007
145EERobert A. Legenstein, Dejan Pecevski, Wolfgang Maass: Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity. NIPS 2007
144EEHerbert Jaeger, Wolfgang Maass, José Carlos Príncipe: Special issue on echo state networks and liquid state machines. Neural Networks 20(3): 287-289 (2007)
143EERobert A. Legenstein, Wolfgang Maass: Edge of chaos and prediction of computational performance for neural circuit models. Neural Networks 20(3): 323-334 (2007)
2006
142 Wolfgang Maass, Andreas Filler: Towards an Infrastructure for Semantically Annotated Physical Products. GI Jahrestagung (2) 2006: 544-549
141EEKei Uchizawa, Rodney J. Douglas, Wolfgang Maass: Energy Complexity and Entropy of Threshold Circuits. ICALP (1) 2006: 631-642
140EEDanko Nikolic, Stefan Häusler, Wolf Singer, Wolfgang Maass: Temporal dynamics of information content carried by neurons in the primary visual cortex. NIPS 2006: 1041-1048
139EEStefan Klampfl, Robert A. Legenstein, Wolfgang Maass: Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons. NIPS 2006: 713-720
138EEWolfgang Maass, Prashant Joshi, Eduardo D. Sontag: Computational aspects of feedback in neural circuits. Electronic Colloquium on Computational Complexity (ECCC) 13(137): (2006)
137EEWolfgang Maass, Kei Uchizawa, Rodney J. Douglas: Energy Complexity and Entropy of Threshold Circuits. Electronic Colloquium on Computational Complexity (ECCC) 13(138): (2006)
136EEFlorian Stahl, Wolfgang Maass: Adoption and Diffusion in Electronic Markets: An Empirical Analysis of Attributes Influencing the Adoption of Paid Content. Electronic Markets 16(3): 233-244 (2006)
135EEKei Uchizawa, Rodney J. Douglas, Wolfgang Maass: On the Computational Power of Threshold Circuits with Sparse Activity. Neural Computation 18(12): 2994-3008 (2006)
134EEAlexander Kaske, Wolfgang Maass: A model for the interaction of oscillations and pattern generation with real-time computing in generic neural microcircuit models. Neural Networks 19(5): 600-609 (2006)
133EEWolfgang Maass: "Imitation of life: how biology is inspiring computing" by Nancy Forbes. Pattern Anal. Appl. 8(4): 390-391 (2006)
2005
132EERobert A. Legenstein, Wolfgang Maass: A Criterion for the Convergence of Learning with Spike Timing Dependent Plasticity. NIPS 2005
131EEWolfgang Maass, Prashant Joshi, Eduardo D. Sontag: Principles of real-time computing with feedback applied to cortical microcircuit models. NIPS 2005
130EERobert A. Legenstein, Wolfgang Maass: Wire length as a circuit complexity measure. J. Comput. Syst. Sci. 70(1): 53-72 (2005)
129EERobert A. Legenstein, Christian Naeger, Wolfgang Maass: What Can a Neuron Learn with Spike-Timing-Dependent Plasticity? Neural Computation 17(11): 2337-2382 (2005)
128EEPrashant Joshi, Wolfgang Maass: Movement Generation with Circuits of Spiking Neurons. Neural Computation 17(8): 1715-1738 (2005)
127EEThomas Natschläger, Wolfgang Maass: Dynamics of information and emergent computation in generic neural microcircuit models. Neural Networks 18(10): 1301-1308 (2005)
2004
126EEPrashant Joshi, Wolfgang Maass: Movement Generation and Control with Generic Neural Microcircuits. BioADIT 2004: 258-273
125EEWolfgang Maass, Robert A. Legenstein, Nils Bertschinger: Methods for Estimating the Computational Power and Generalization Capability of Neural Microcircuits. NIPS 2004
124EEWolfgang Maass, Henry Markram: On the computational power of circuits of spiking neurons. J. Comput. Syst. Sci. 69(4): 593-616 (2004)
2003
123EEThomas Natschläger, Wolfgang Maass: Information Dynamics and Emergent Computation in Recurrent Circuits of Spiking Neurons. NIPS 2003
122EEStefan Häusler, Henry Markram, Wolfgang Maass: Perspectives of the high-dimensional dynamics of neural microcircuits from the point of view of low-dimensional readouts. Complexity 8(4): 39-50 (2003)
121EEWolfgang Maass, Jörg P. Müller: Preface to the Special Section on Software Agents. Electronic Markets 13(1): (2003)
2002
120EEWolfgang Maass, Robert A. Legenstein, Henry Markram: A New Approach towards Vision Suggested by Biologically Realistic Neural Microcircuit Models. Biologically Motivated Computer Vision 2002: 282-293
119EEPeter Auer, Harald Burgsteiner, Wolfgang Maass: Reducing Communication for Distributed Learning in Neural Networks. ICANN 2002: 123-128
118EEWolfgang Maass: On the Computational Power of Neural Microcircuit Models: Pointers to the Literature. ICANN 2002: 254-258
117EEWolfgang Maass, Thomas Natschläger, Henry Markram: A Model for Real-Time Computation in Generic Neural Microcircuits. NIPS 2002: 213-220
116EEDimitris Apostolou, Gregoris Mentzas, Andreas Abecker, Wolf-Christian Eickhoff, Wolfgang Maass, Panos Georgolios, Kostas Kafentzis, Sophia Kyriakopoulou: Challenges and Directions in Knowledge Asset Trading. PAKM 2002: 549-564
115EEWolfgang Maass, Henry Markram: On the Computational Power of Recurrent Circuits of Spiking Neurons Electronic Colloquium on Computational Complexity (ECCC)(022): (2002)
114EEWolfgang Maass, Thomas Natschläger, Henry Markram: Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations. Neural Computation 14(11): 2531-2560 (2002)
113EEWolfgang Maass, Henry Markram: Synapses as dynamic memory buffers. Neural Networks 15(1): 155-161 (2002)
112 Robert A. Legenstein, Wolfgang Maass: Neural circuits for pattern recognition with small total wire length. Theor. Comput. Sci. 287(1): 239-249 (2002)
111 Thomas Natschläger, Wolfgang Maass: Spiking neurons and the induction of finite state machines. Theor. Comput. Sci. 287(1): 251-265 (2002)
2001
110 Wolfgang Maass: Neural Computation: A Research Topic for Theoretical Computer Science? Some Thoughts and Pointers. Current Trends in Theoretical Computer Science 2001: 680-690
109EERobert A. Legenstein, Wolfgang Maass: Optimizing the Layout of a Balanced Tree Electronic Colloquium on Computational Complexity (ECCC) 8(069): (2001)
108EERobert A. Legenstein, Wolfgang Maass: Total Wire Length as a Salient Circuit Complexity Measure for Sensory Processing Electronic Colloquium on Computational Complexity (ECCC) 8(070): (2001)
107EERobert A. Legenstein, Wolfgang Maass: Neural Circuits for Pattern Recognition with Small Total Wire Length Electronic Colloquium on Computational Complexity (ECCC) 8(071): (2001)
106EEThomas Natschläger, Wolfgang Maass: Computing the Optimally Fitted Spike Train for a Synapse. Neural Computation 13(11): 2477-2494 (2001)
105EEStephen Grossberg, Wolfgang Maass, Henry Markram: Introduction: Spiking Neurons in Neuroscience and Technology. Neural Networks 14(6-7): 587- (2001)
104EEWolfgang Maass: On the relevance of time in neural computation and learning. Theor. Comput. Sci. 261(1): 157-178 (2001)
2000
103 Thomas Natschläger, Wolfgang Maass: Finding the Key to a Synapse. NIPS 2000: 138-144
102 Thomas Natschläger, Wolfgang Maass, Eduardo D. Sontag, Anthony M. Zador: Processing of Time Series by Neural Circuits with Biologically Realistic Synaptic Dynamics. NIPS 2000: 145-151
101 Robert A. Legenstein, Wolfgang Maass: Foundations for a Circuit Complexity Theory of Sensory Processing. NIPS 2000: 259-265
100EEWolfgang Maass, Gerald Steinbauer, Roland Koholka: Autonomous Fast Learning in a Mobile Robot. Sensor Based Intelligent Robots 2000: 345-356
99 Wolfgang Maass: Neural Computation: A Research Topic for Theoretical Computer Science? Some Thoughts and Pointers. Bulletin of the EATCS 72: 149-158 (2000)
98EEWolfgang Maass: A Simple Model for Neural Computation with Firing Rates and Firing Correlations Electronic Colloquium on Computational Complexity (ECCC) 7(30): (2000)
97EEWolfgang Maass, Eduardo D. Sontag: Neural Systems as Nonlinear Filters Electronic Colloquium on Computational Complexity (ECCC) 7(31): (2000)
96EEWolfgang Maass: On the Computational Power of Winner-Take-All Electronic Colloquium on Computational Complexity (ECCC) 7(32): (2000)
95EEWolfgang Maass: On Computation with Pulses Electronic Colloquium on Computational Complexity (ECCC) 7(38): (2000)
94EEPeter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger: On the Complexity of Function Learning Electronic Colloquium on Computational Complexity (ECCC) 7(50): (2000)
93EEPeter Auer, Stephen Kwek, Wolfgang Maass, Manfred K. Warmuth: Learning of Depth Two Neural Networks with Constant Fan-in at the Hidden Nodes Electronic Colloquium on Computational Complexity (ECCC) 7(55): (2000)
92 Wolfgang Maass: On the Computational Power of Winner-Take-All. Neural Computation 12(11): 2519-2535 (2000)
91 Wolfgang Maass, Thomas Natschläger: A Model for Fast Analog Computation Based on Unreliable Synapses. Neural Computation 12(7): 1679-1704 (2000)
90 Wolfgang Maass, Eduardo D. Sontag: Neural Systems as Nonlinear Filters. Neural Computation 12(8): 1743-1772 (2000)
1999
89EEThomas Natschläger, Wolfgang Maass: Fast analog computation in networks of spiking neurons using unreliable synapses. ESANN 1999: 417-422
88EEWolfgang Maass: Neural Computation with Winner-Take-All as the Only Nonlinear Operation. NIPS 1999: 293-299
87 Wolfgang Maass, Berthold Ruf: On Computations with Pulses. Inf. Comput. 148(2): 202-218 (1999)
86 Wolfgang Maass, Michael Schmitt: On the Complexity of Learning for Spiking Neurons with Temporal Coding. Inf. Comput. 153(1): 26-46 (1999)
85 Wolfgang Maass, Eduardo D. Sontag: Analog Neural Nets with Gaussian or Other Common Noise Distribution Cannot Recognize Arbitrary Regular Languages. Neural Computation 11(3): 771-782 (1999)
84 Wolfgang Maass, Anthony M. Zador: Dynamic Stochastic Synapses as Computational Units. Neural Computation 11(4): 903-917 (1999)
1998
83 Wolfgang Maass: Models for Fast Analog Computation with Spiking Neurons. ICONIP 1998: 187-188
82EEWolfgang Maass: On the Role of Time and Space in Neural Computation. MFCS 1998: 72-83
81 Wolfgang Maass: Spiking Neurons. NC 1998: 16-20
80EEWolfgang Maass, Eduardo D. Sontag: A Precise Characterization of the Class of Languages Recognized by Neural Nets under Gaussian and Other Common Noise Distributions. NIPS 1998: 281-287
79 Wolfgang Maass, Manfred K. Warmuth: Efficient Learning With Virtual Threshold Gates. Inf. Comput. 141(1): 66-83 (1998)
78 Wolfgang Maass, Pekka Orponen: On the Effect of Analog Noise in Discrete-Time Analog Computations. Neural Computation 10(5): 1071-1095 (1998)
1997
77 Wolfgang Maass: On the Relevance of Time in Neural Computation and Learning. ALT 1997: 364-384
76EEWolfgang Maass, Michael Schmitt: On the Complexity of Learning for a Spiking Neuron (Extended Abstract). COLT 1997: 54-61
75 Wolfgang Maass, Anthony M. Zador: Dynamic Stochastic Synapses as Computational Units. NIPS 1997
74EEWolfgang Maass, Michael Schmitt: On the Complexity of Learning for Spiking Neurons with Temporal Coding Electronic Colloquium on Computational Complexity (ECCC) 4(49): (1997)
73EEWolfgang Maass, Pekka Orponen: On the Effect of Analog Noise in Discrete-Time Analog Computations Electronic Colloquium on Computational Complexity (ECCC) 4(51): (1997)
72EEWolfgang Maass, Eduardo D. Sontag: Analog Neural Nets with Gaussian or other Common Noise Distributions cannot Recognize Arbitrary Regular Languages Electronic Colloquium on Computational Complexity (ECCC) 4(52): (1997)
71EEWolfgang Maass: Fast Sigmoidal Networks via Spiking Neurons. Neural Computation 9(2): 279-304 (1997)
70EEWolfgang Maass: Networks of spiking neurons: The third generation of neural network models. Neural Networks 10(9): 1659-1671 (1997)
69 Wolfgang Maass: Bounds for the Computational Power and Learning Complexity of Analog Neural Nets. SIAM J. Comput. 26(3): 708-732 (1997)
1996
68EEPeter Auer, Stephen Kwek, Wolfgang Maass, Manfred K. Warmuth: Learning of Depth Two Neural Networks with Constant Fan-In at the Hidden Nodes (Extended Abstract). COLT 1996: 333-343
67EEWolfgang Maass: Noisy Spiking Neurons with Temporal Coding have more Computational Power than Sigmoidal Neurons. NIPS 1996: 211-217
66EEWolfgang Maass, Pekka Orponen: On the Effect of Analog Noise in Discrete-Time Analog Computations. NIPS 1996: 218-224
65EEWolfgang Maass, Berthold Ruf: The Computational Power of Spiking Neurons Depends on the Shape of the Postsynaptic Potentials Electronic Colloquium on Computational Complexity (ECCC) 3(25): (1996)
64EEWolfgang Maass: Networks of Spiking Neurons: The Third Generation of Neural Network Models Electronic Colloquium on Computational Complexity (ECCC) 3(31): (1996)
63 David P. Dobkin, Dimitrios Gunopulos, Wolfgang Maass: Computing the Maximum Bichromatic Discrepancy with Applications to Computer Graphics and Machine Learning. J. Comput. Syst. Sci. 52(3): 453-470 (1996)
1995
62 Wolfgang Maass: How Spatial Information Connects Visual Perception and Natural Language Generation in Dynamic Environments: Towards a Computational Model. COSIT 1995: 223-240
61 Peter Auer, Robert C. Holte, Wolfgang Maass: Theory and Applications of Agnostic PAC-Learning with Small Decision Trees. ICML 1995: 21-29
60 Wolfgang Maass, Manfred K. Warmuth: Efficient Learning with Virtual Threshold Gates. ICML 1995: 378-386
59EEWolfgang Maass: On the Computational Power of Noisy Spiking Neurons. NIPS 1995: 211-217
58 William J. Bultman, Wolfgang Maass: Fast Identification of Geometric Objects with Membership Queries Inf. Comput. 118(1): 48-64 (1995)
57 Wolfgang Maass: Editor's Foreword. J. Comput. Syst. Sci. 51(3): 339 (1995)
56 Peter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger: On the Complexity of Function Learning. Machine Learning 18(2-3): 187-230 (1995)
1994
55EEWolfgang Maass: Efficient Agnostic PAC-Learning with Simple Hypothesis. COLT 1994: 67-75
54EEWolfgang Maass: On the Computational Complexity of Networks of Spiking Neurons. NIPS 1994: 183-190
53 Wolfgang Maass: From Vision to Multimodal Communication: Incremental Route Descriptions. Artif. Intell. Rev. 8(2-3): 159-174 (1994)
52EEWolfgang Maass: Bounds for the Computational Power and Learning Complexity of Analog Neural Nets Electronic Colloquium on Computational Complexity (ECCC) 1(12): (1994)
51EEWolfgang Maass: Neural Nets with Superlinear VC-Dimension Electronic Colloquium on Computational Complexity (ECCC) 1(17): (1994)
50EEWolfgang Maass: Lower Bounds for the Computational Power of Networks of Spiking Neurons Electronic Colloquium on Computational Complexity (ECCC) 1(19): (1994)
49EEWolfgang Maass: Agnostic PAC-Learning of Functions on Analog Neural Nets Electronic Colloquium on Computational Complexity (ECCC) 1(20): (1994)
48EEDavid P. Dobkin, Dimitrios Gunopulos, Wolfgang Maass: Computing the Maximum Bichromatic Discrepancy, with applications to Computer Graphics and Machine Learning Electronic Colloquium on Computational Complexity (ECCC) 1(25): (1994)
47 Wolfgang Maass, György Turán: Algorithms and Lower Bounds for On-Line Learning of Geometrical Concepts. Machine Learning 14(1): 251-269 (1994)
46 Zhixiang Chen, Wolfgang Maass: On-Line Learning of Rectangles and Unions of Rectangles. Machine Learning 17(2-3): 201-223 (1994)
45EEWolfgang Maass: Neural Nets with Superlinear VC-Dimension. Neural Computation 6(5): 877-884 (1994)
1993
44EEPeter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger: On the Complexity of Function Learning. COLT 1993: 392-401
43 Wolfgang Maass: A Cognitive Model for the Process of Multimodal, Incremental Route Descriptions. COSIT 1993: 1-13
42EEWolfgang Maass: Agnostic PAC-Learning of Functions on Analog Neural Nets. NIPS 1993: 311-318
41EEWolfgang Maass: Bounds for the computational power and learning complexity of analog neural nets. STOC 1993: 335-344
40 Wolfgang Maass, Georg Schnitger, Endre Szemerédi, György Turán: Two Tapes Versus One for Off-Line Turing Machines. Computational Complexity 3: 392-401 (1993)
39 András Hajnal, Wolfgang Maass, Pavel Pudlák, Mario Szegedy, György Turán: Threshold Circuits of Bounded Depth. J. Comput. Syst. Sci. 46(2): 129-154 (1993)
38 Martin Dietzfelbinger, Wolfgang Maass: The Complexity of Matrix Transposition on One-Tape Off-Line Turing Machines with Output Tape. Theor. Comput. Sci. 108(2): 271-290 (1993)
1992
37 Zhixiang Chen, Wolfgang Maass: A Solution of the Credit Assignment Problem in the Case of Learning Rectangles (Abstract). AII 1992: 26-34
36EEZhixiang Chen, Wolfgang Maass: On-line Learning of Rectangles. COLT 1992: 16-28
35 Wolfgang Maass, Theodore A. Slaman: The Complexity Types of Computable Sets. J. Comput. Syst. Sci. 44(2): 168-192 (1992)
34 Wolfgang Maass, György Turán: Lower Bound Methods and Separation Results for On-Line Learning Models. Machine Learning 9: 107-145 (1992)
1991
33EEWolfgang Maass: On-Line Learning with an Oblivious Environment and the Power of Randomization. COLT 1991: 167-175
32EEWilliam J. Bultman, Wolfgang Maass: Fast Identification of Geometric Objects with Membership Queries. COLT 1991: 337-353
31 Wolfgang Maass, Georg Schnitger, Eduardo D. Sontag: On the Computational Power of Sigmoid versus Boolean Threshold Circuits FOCS 1991: 767-776
30 Winfried Graf, Wolfgang Maass: Constraint-basierte Verarbeitung graphischen Wissens. Wissensbasierte Systeme 1991: 243-253
29 Martin Dietzfelbinger, Wolfgang Maass, Georg Schnitger: The Complexity of Matrix Transposition on One-Tape Off-Line Turing Machines. Theor. Comput. Sci. 82(1): 113-129 (1991)
1990
28EEWolfgang Maass, György Turán: On the Complexity of Learning from Counterexamples and Membership Queries (abstract). COLT 1990: 391
27 Wolfgang Maass, György Turán: On the Complexity of Learning from Counterexamples and Membership Queries FOCS 1990: 203-210
26EEAjay Gupta, Wolfgang Maass: Efficient Design of Boltzmann Machines. NIPS 1990: 825-831
1989
25 Wolfgang Maass, Theodore A. Slaman: Extensional Properties of Sets of Time Bounded Complexity (Extended Abstract). FCT 1989: 318-326
24 Wolfgang Maass, György Turán: On the Complexity of Learning From Counterexamples (Extended Abstract) FOCS 1989: 262-267
23 Wolfgang Maass, Theodore A. Slaman: The Complexity Types of Computable Sets. Structure in Complexity Theory Conference 1989: 231-239
1988
22EEMartin Dietzfelbinger, Wolfgang Maass: The Complexity of Matrix Transposition on One-Tape Off-Line Turing Machines with Output Tape. ICALP 1988: 188-200
21 András Hajnal, Wolfgang Maass, György Turán: On the Communication Complexity of Graph Properties STOC 1988: 186-191
20 Klaus Sutner, Wolfgang Maass: Motion Planning Among Time Dependent Obstacles. Acta Inf. 26(1/2): 93-122 (1988)
19 Martin Dietzfelbinger, Wolfgang Maass: Lower Bound Arguments with "Inaccessible" Numbers. J. Comput. Syst. Sci. 36(3): 313-335 (1988)
18 Noga Alon, Wolfgang Maass: Meanders and Their Applications in Lower Bounds Arguments. J. Comput. Syst. Sci. 37(2): 118-129 (1988)
17 Wolfgang Maass: On the Use of Inaccessible Numbers and Order Indiscernibles in Lower Bound Arguments for Random Access Machines. J. Symb. Log. 53(4): 1098-1109 (1988)
1987
16 András Hajnal, Wolfgang Maass, Pavel Pudlák, Mario Szegedy, György Turán: Threshold circuits of bounded depth FOCS 1987: 99-110
15 Wolfgang Maass, Georg Schnitger, Endre Szemerédi: Two Tapes Are Better than One for Off-Line Turing Machines STOC 1987: 94-100
14 Dorit S. Hochbaum, Wolfgang Maass: Fast Approximation Algorithms for a Nonconvex Covering Problem. J. Algorithms 8(3): 305-323 (1987)
13 Wolfgang Maass, Amir Schorr: Speed-Up of Turing Machines with One Work Tape and a Two-Way Input Tape. SIAM J. Comput. 16(1): 195-202 (1987)
1986
12 Noga Alon, Wolfgang Maass: Meanders, Ramsey Theory and Lower Bounds for Branching Programs FOCS 1986: 410-417
11 Martin Dietzfelbinger, Wolfgang Maass: two Lower Bound Arguments with "Inaccessible" Numbers. Structure in Complexity Theory Conference 1986: 163-183
10 Wolfgang Maass, Georg Schnitger: An Optimal Lower Bound for Turing Machines with One Work Tape and a Two- way Input Tape. Structure in Complexity Theory Conference 1986: 249-264
9 Wolfgang Maass: On the Complexity of Nonconvex Covering. SIAM J. Comput. 15(2): 453-467 (1986)
1985
8EEDorit S. Hochbaum, Wolfgang Maass: Approximation Schemes for Covering and Packing Problems in Image Processing and VLSI J. ACM 32(1): 130-136 (1985)
7 Wolfgang Maass: Variations on Promptly Simple Sets. J. Symb. Log. 50(1): 138-148 (1985)
1984
6EEDorit S. Hochbaum, Wolfgang Maass: Approximation Schemes for Covering and Packing Problems in Robotics and VLSI. STACS 1984: 55-62
5 Wolfgang Maass: Quadratic Lower Bounds for Deterministic and Nondeterministic One-Tape Turing Machines (Extended Abstract) STOC 1984: 401-408
4 Wolfgang Maass: On the Orbits of Hyperhypersimple Sets. J. Symb. Log. 49(1): 51-62 (1984)
1983
3 Steven Homer, Wolfgang Maass: Oracle-Dependent Properties of the Lattice of NP Sets. Theor. Comput. Sci. 24: 279-289 (1983)
1982
2 Wolfgang Maass: Recursively Enumerable Generic Sets. J. Symb. Log. 47(4): 809-823 (1982)
1978
1 Wolfgang Maass: The Uniform Regular Set Theorem in a-Recursion Theory. J. Symb. Log. 43(2): 270-279 (1978)

Coauthor Index

1Andreas Abecker [116] [153]
2Noga Alon [12] [18]
3Dimitris Apostolou [116] [153]
4Peter Auer [44] [56] [61] [68] [93] [94] [119] [151]
5Nils Bertschinger [125]
6Lars Buesing [146]
7William J. Bultman [32] [58]
8Harald Burgsteiner [119] [151]
9Zhixiang Chen [36] [37] [46]
10Martin Dietzfelbinger [11] [19] [22] [29] [38]
11David P. Dobkin [48] [63]
12Rodney J. Douglas [135] [137] [141] [160]
13Wolf-Christian Eickhoff [116]
14Andreas Filler [142] [155]
15Panos Georgolios [116]
16Winfried Graf [30]
17Stephen Grossberg [105]
18Dimitrios Gunopulos [48] [63]
19Ajay Gupta [26]
20András Hajnal [16] [21] [39]
21Barbara Hammer [156] [157] [159]
22Stefan Häusler [122] [140]
23Pascal Hitzler [156] [157] [159]
24Dorit S. Hochbaum [6] [8] [14]
25Robert C. Holte (Robert Holte) [61]
26Steven Homer [3]
27Herbert Jaeger [144]
28Sabine Janzen [162]
29Prashant Joshi [126] [128] [131] [138]
30Kostas Kafentzis [116]
31Alexander Kaske [134]
32Stefan Klampfl [139] [161]
33Bertin Klein [153]
34Roland Koholka [100]
35Tobias Kowatsch [148]
36Stephen Kwek [68] [93]
37Sophia Kyriakopoulou [116]
38Matthias Lampe [147]
39Robert A. Legenstein [101] [107] [108] [109] [112] [120] [125] [129] [130] [132] [139] [143] [145] [152] [161]
40Philip M. Long [44] [56] [94]
41Henry Markram [105] [113] [114] [115] [117] [120] [122] [124]
42Gregoris Mentzas (Gregory Mentzas) [116] [153]
43Jörg P. Müller [121]
44Timo Münster [148]
45Christian Naeger [129]
46Thomas Natschläger [89] [91] [102] [103] [106] [111] [114] [117] [123] [127]
47Bernhard Nessler [158]
48Gerhard Neumann [149] [163]
49Danko Nikolic [140]
50Pekka Orponen [66] [73] [78]
51Dejan Pecevski [145]
52Jan Peters [163]
53Michael Pfeiffer [149] [158]
54José Carlos Príncipe (José C. Príncipe, Jose C. Principe) [144]
55Pavel Pudlák [16] [39]
56Luc De Raedt [156] [157] [159]
57Berthold Ruf [65] [87]
58Michael Schmitt [74] [76] [86]
59Georg Schnitger [10] [15] [29] [31] [40]
60Amir Schorr [13]
61Jan Seeburger [155]
62Wolf Singer [140]
63Theodore A. Slaman [23] [25] [35]
64Eduardo D. Sontag [31] [72] [80] [85] [90] [97] [102] [131] [138]
65Florian Stahl [136]
66Andreas Steimer [160]
67Gerald Steinbauer [100]
68Klaus Sutner [20]
69Mario Szegedy [16] [39]
70Endre Szemerédi [15] [40]
71György Turán [16] [21] [24] [27] [28] [34] [39] [40] [47]
72Kei Uchizawa [135] [137] [141]
73Upkar Varshney [154]
74Manfred K. Warmuth [60] [68] [79] [93]
75Gerhard J. Woeginger [44] [56] [94]
76Anthony M. Zador [75] [84] [102]

Colors in the list of coauthors

Copyright © Tue Nov 3 08:52:44 2009 by Michael Ley (ley@uni-trier.de)