Stop the war!Остановите войну!
for scientists:
Google
Google Scholar
Semantic Scholar
IA Scholar
CiteSeerX
ORCIDHans Ulrich Simon
Person information
- affiliation: Faculty of Mathematics, Ruhr University Bochum
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2022
[i6]Hans Ulrich Simon:
Tournaments, Johnson Graphs, and NC-Teaching. CoRR abs/2205.02792 (2022)- [i5]Hans Ulrich Simon:
Minimum Tournaments with the Strong Sk-Property and Implications for Teaching. CoRR abs/2205.08357 (2022)
2010 – 2019
- 2019
- [c68]David G. Kirkpatrick, Hans Ulrich Simon, Sandra Zilles:
Optimal Collusion-Free Teaching. ALT 2019: 506-528 - [i4]David G. Kirkpatrick, Hans Ulrich Simon, Sandra Zilles:
Optimal Collusion-Free Teaching. CoRR abs/1903.04012 (2019) - 2018
- [j53]Francesco Aldà, Hans Ulrich Simon:
A lower bound on the release of differentially private integer partitions. Inf. Process. Lett. 129: 1-4 (2018) - [j52]Malte Darnstädt, Christoph Ries, Hans Ulrich Simon:
Hierarchical design of fast Minimum Disagreement algorithms. Theor. Comput. Sci. 716: 70-88 (2018) - [j51]Ziyuan Gao, Hans Ulrich Simon, Sandra Zilles:
On the teaching complexity of linear sets. Theor. Comput. Sci. 716: 107-123 (2018) - [j50]Ronald Ortner
, Hans Ulrich Simon:
Guest Editors' Foreword. Theor. Comput. Sci. 742: 1-2 (2018) - [c67]Hans Ulrich Simon:
On the Containment Problem for Linear Sets. STACS 2018: 55:1-55:12 - 2017
- [j49]Marius Konitzer, Hans Ulrich Simon:
Regular languages viewed from a graph-theoretic perspective. Inf. Comput. 253: 484-496 (2017) - [j48]Ziyuan Gao, Zeinab Mazadi, Regan Meloche, Hans Ulrich Simon, Sandra Zilles:
Distinguishing pattern languages with membership examples. Inf. Comput. 256: 348-371 (2017) - [j47]Ziyuan Gao, Christoph Ries, Hans Ulrich Simon, Sandra Zilles:
Preference-based Teaching. J. Mach. Learn. Res. 18: 31:1-31:32 (2017) - [c66]Ziyuan Gao, David G. Kirkpatrick, Christoph Ries, Hans Ulrich Simon, Sandra Zilles:
Preference-based Teaching of Unions of Geometric Objects. ALT 2017: 185-207 - [c65]Francesco Aldà, Hans Ulrich Simon:
On the Optimality of the Exponential Mechanism. CSCML 2017: 68-85 - [i3]Ziyuan Gao, Christoph Ries, Hans Ulrich Simon, Sandra Zilles:
Preference-based Teaching. CoRR abs/1702.02047 (2017) - [i2]Hans Ulrich Simon:
On the Containment Problem for Linear Sets. CoRR abs/1710.04533 (2017) - 2016
- [j46]Hans Ulrich Simon:
Efficient computation of approximate isomorphisms between Boolean functions. Inf. Process. Lett. 116(3): 237-240 (2016) - [j45]Malte Darnstädt, Thorsten Kiss, Hans Ulrich Simon, Sandra Zilles:
Order compression schemes. Theor. Comput. Sci. 620: 73-90 (2016) - [c64]Ziyuan Gao, Christoph Ries, Hans Ulrich Simon, Sandra Zilles:
Preference-based Teaching. COLT 2016: 971-997 - [e4]Ronald Ortner, Hans Ulrich Simon, Sandra Zilles:
Algorithmic Learning Theory - 27th International Conference, ALT 2016, Bari, Italy, October 19-21, 2016, Proceedings. Lecture Notes in Computer Science 9925, 2016, ISBN 978-3-319-46378-0 [contents] - 2015
- [c63]Ziyuan Gao, Hans Ulrich Simon, Sandra Zilles:
On the Teaching Complexity of Linear Sets. ALT 2015: 102-116 - [c62]Malte Darnstädt, Christoph Ries, Hans Ulrich Simon:
Hierarchical Design of Fast Minimum Disagreement Algorithms. ALT 2015: 134-148 - [c61]Hans Ulrich Simon:
An Almost Optimal PAC Algorithm. COLT 2015: 1552-1563 - [c60]Hans Ulrich Simon, Sandra Zilles:
Open Problem: Recursive Teaching Dimension Versus VC Dimension. COLT 2015: 1770-1772 - [c59]Christian Brandl, Hans Ulrich Simon:
Complexity Analysis: Transformation Monoids of Finite Automata. DLT 2015: 143-154 - 2014
- [j44]Hans Ulrich Simon:
PAC-learning in the presence of one-sided classification noise. Ann. Math. Artif. Intell. 71(4): 283-300 (2014) - [j43]Thorsten Doliwa, Gaojian Fan, Hans Ulrich Simon, Sandra Zilles:
Recursive teaching dimension, VC-dimension and sample compression. J. Mach. Learn. Res. 15(1): 3107-3131 (2014) - [j42]Malte Darnstädt, Hans Ulrich Simon, Balázs Szörényi:
Supervised learning and Co-training. Theor. Comput. Sci. 519: 68-87 (2014) - [c58]Francesco Aldà, Hans Ulrich Simon:
Randomized Response Schemes, Privacy and Usefulness. AISec@CCS 2014: 15-26 - [c57]Marius Konitzer, Hans Ulrich Simon:
DFA with a Bounded Activity Level. LATA 2014: 478-489 - 2013
- [c56]Malte Darnstädt, Thorsten Doliwa, Hans Ulrich Simon, Sandra Zilles:
Order Compression Schemes. ALT 2013: 173-187 - [c55]Malte Darnstädt, Hans Ulrich Simon, Balázs Szörényi:
Unlabeled Data Does Provably Help. STACS 2013: 185-196 - 2012
- [c54]Hans Ulrich Simon:
Boolean Composition of Visual Secret Sharing Schemes. CSR 2012: 314-325 - [c53]Hans Ulrich Simon:
PAC-Learning in the Presence of One-sided Classification Noise. ISAIM 2012 - 2011
- [j41]Malte Darnstädt, Hans Ulrich Simon:
Smart PAC-learners. Theor. Comput. Sci. 412(19): 1756-1766 (2011) - [c52]Malte Darnstädt, Hans Ulrich Simon, Balázs Szörényi:
Supervised Learning and Co-training. ALT 2011: 425-439 - [c51]Michael Kallweit, Hans Ulrich Simon:
A Close Look to Margin Complexity and Related Parameters. COLT 2011: 437-456 - 2010
- [j40]Hans Ulrich Simon, Balázs Szörényi:
One-inclusion hypergraph density revisited. Inf. Process. Lett. 110(8-9): 341-344 (2010) - [c50]Thorsten Doliwa, Hans Ulrich Simon, Sandra Zilles:
Recursive Teaching Dimension, Learning Complexity, and Maximum Classes. ALT 2010: 209-223
2000 – 2009
- 2009
- [j39]Lisa Hellerstein, Hans Ulrich Simon:
Special Issue: Learning Theory 2006. J. Comput. Syst. Sci. 75(1): 1 (2009) - [c49]Hans Ulrich Simon:
Smart PAC-Learners. ALT 2009: 353-367 - [c48]Hans Ulrich Simon, Nikolas List:
SVM-Optimization and Steepest-Descent Line Search. COLT 2009 - 2008
- [c47]Thorsten Doliwa, Michael Kallweit, Hans Ulrich Simon:
Dimension and Margin Bounds for Reflection-invariant Kernels. COLT 2008: 157-168 - 2007
- [j38]Philip M. Long, Rocco A. Servedio, Hans Ulrich Simon:
Discriminative learning can succeed where generative learning fails. Inf. Process. Lett. 103(4): 131-135 (2007) - [j37]Nikolas List, Hans Ulrich Simon:
General Polynomial Time Decomposition Algorithms. J. Mach. Learn. Res. 8: 303-321 (2007) - [j36]Avrim Blum, Gábor Lugosi, Hans Ulrich Simon:
Introduction to the special issue on COLT 2006. Mach. Learn. 69(2-3): 75-77 (2007) - [j35]Hans Ulrich Simon:
On the complexity of working set selection. Theor. Comput. Sci. 382(3): 262-279 (2007) - [j34]Hans Ulrich Simon, Etsuji Tomita:
Guest editors' foreword. Theor. Comput. Sci. 387(1): 1-3 (2007) - [c46]Shai Ben-David, Dávid Pál, Hans Ulrich Simon:
Stability of k -Means Clustering. COLT 2007: 20-34 - [c45]Hans Ulrich Simon:
A Characterization of Strong Learnability in the Statistical Query Model. STACS 2007: 393-404 - 2006
- [j33]Jürgen Forster, Hans Ulrich Simon:
On the smallest possible dimension and the largest possible margin of linear arrangements representing given concept classes. Theor. Comput. Sci. 350(1): 40-48 (2006) - [c44]Hans Ulrich Simon:
Spectral Norm in Learning Theory: Some Selected Topics. ALT 2006: 13-27 - [c43]Hans Ulrich Simon:
Spectral Norm in Learning Theory: Some Selected Topics. Discovery Science 2006: 16 - [e3]Gábor Lugosi, Hans Ulrich Simon:
Learning Theory, 19th Annual Conference on Learning Theory, COLT 2006, Pittsburgh, PA, USA, June 22-25, 2006, Proceedings. Lecture Notes in Computer Science 4005, Springer 2006, ISBN 3-540-35294-5 [contents] - 2005
- [j32]Eike Kiltz, Hans Ulrich Simon:
Threshold circuit lower bounds on cryptographic functions. J. Comput. Syst. Sci. 71(2): 185-212 (2005) - [j31]Atsuyoshi Nakamura, Michael Schmitt, Niels Schmitt, Hans Ulrich Simon:
Inner Product Spaces for Bayesian Networks. J. Mach. Learn. Res. 6: 1383-1403 (2005) - [c42]Sanjay Jain, Hans Ulrich Simon, Etsuji Tomita:
Editors' Introduction. ALT 2005: 1-9 - [c41]Nikolas List, Hans Ulrich Simon:
General Polynomial Time Decomposition Algorithms. COLT 2005: 308-322 - [c40]Hans Ulrich Simon:
Perfect Reconstruction of Black Pixels Revisited. FCT 2005: 221-232 - [e2]Sanjay Jain, Hans Ulrich Simon, Etsuji Tomita:
Algorithmic Learning Theory, 16th International Conference, ALT 2005, Singapore, October 8-11, 2005, Proceedings. Lecture Notes in Computer Science 3734, Springer 2005, ISBN 3-540-29242-X [contents] - 2004
- [j30]Hans Ulrich Simon:
How Many Missing Answers Can Be Tolerated by Query Learners? Theory Comput. Syst. 37(1): 77-94 (2004) - [c39]Hans Ulrich Simon:
On the Complexity of Working Set Selection. ALT 2004: 324-337 - [c38]Nikolas List, Hans Ulrich Simon:
A General Convergence Theorem for the Decomposition Method. COLT 2004: 363-377 - [c37]Atsuyoshi Nakamura, Michael Schmitt, Niels Schmitt, Hans Ulrich Simon:
Bayesian Networks and Inner Product Spaces. COLT 2004: 518-533 - 2003
- [j29]Hans Ulrich Simon:
How Many Queries Are Needed to Learn One Bit of Information? Ann. Math. Artif. Intell. 39(3): 333-343 (2003) - [j28]Matthias Krause, Hans Ulrich Simon:
Determining The Optimal Contrast For Secret Sharing Schemes In Visual Cryptography. Comb. Probab. Comput. 12(3): 285-299 (2003) - [j27]Jürgen Forster, Niels Schmitt, Hans Ulrich Simon, Thorsten Suttorp:
Estimating the Optimal Margins of Embeddings in Euclidean Half Spaces. Mach. Learn. 51(3): 263-281 (2003) - [c36]Eike Kiltz, Hans Ulrich Simon:
Complexity Theoretic Aspects of Some Cryptographic Functions. COCOON 2003: 294-303 - 2002
- [j26]Shai Ben-David, Nadav Eiron, Hans Ulrich Simon:
The Computational Complexity of Densest Region Detection. J. Comput. Syst. Sci. 64(1): 22-47 (2002) - [j25]Shai Ben-David, Nadav Eiron, Hans Ulrich Simon:
Limitations of Learning Via Embeddings in Euclidean Half Spaces. J. Mach. Learn. Res. 3: 441-461 (2002) - [j24]Paul Fischer, Hans Ulrich Simon, Carl Smith:
Foreword. Theor. Comput. Sci. 284(1): 1-2 (2002) - [j23]José L. Balcázar, Jorge Castro, David Guijarro, Hans Ulrich Simon:
The consistency dimension and distribution-dependent learning from queries. Theor. Comput. Sci. 288(2): 197-215 (2002) - [c35]Jürgen Forster, Hans Ulrich Simon:
On the Smallest Possible Dimension and the Largest Possible Margin of Linear Arrangements Representing Given Concept Classes Uniform Distribution. ALT 2002: 128-138 - [c34]Dietrich Braess, Jürgen Forster, Tomas Sauer, Hans Ulrich Simon:
How to Achieve Minimax Expected Kullback-Leibler Distance from an Unknown Finite Distribution. ALT 2002: 380-394 - [c33]Hans Ulrich Simon:
How Many Missing Answers Can Be Tolerated by Query Learners? STACS 2002: 384-395 - 2001
- [c32]Hans Ulrich Simon:
How Many Queries Are Needed to Learn One Bit of Information? COLT/EuroCOLT 2001: 1-13 - [c31]Shai Ben-David, Nadav Eiron, Hans Ulrich Simon:
Limitations of Learning via Embeddings in Euclidean Half-Spaces. COLT/EuroCOLT 2001: 385-401 - [c30]Jürgen Forster, Niels Schmitt, Hans Ulrich Simon:
Estimating the Optimal Margins of Embeddings in Euclidean Half Spaces. COLT/EuroCOLT 2001: 402-415 - [c29]Jürgen Forster, Matthias Krause, Satyanarayana V. Lokam, Rustam Mubarakzjanov, Niels Schmitt, Hans Ulrich Simon:
Relations Between Communication Complexity, Linear Arrangements, and Computational Complexity. FSTTCS 2001: 171-182 - 2000
- [j22]Norbert Klasner, Hans Ulrich Simon:
General lower bounds on the query complexity within the exact learning model. Discret. Appl. Math. 107(1-3): 61-81 (2000) - [j21]Andreas Birkendorf, Norbert Klasner, Christian Kuhlmann, Hans Ulrich Simon:
Structural Results about Exact Learning with Unspecified Attribute Values. J. Comput. Syst. Sci. 60(2): 258-277 (2000) - [j20]Andreas Birkendorf, Andreas Böker, Hans Ulrich Simon:
Learning Deterministic Finite Automata from Smallest Counterexamples. SIAM J. Discret. Math. 13(4): 465-491 (2000) - [j19]Thomas Hofmeister, Matthias Krause, Hans Ulrich Simon:
Contrast-optimal k out of n secret sharing schemes in visual cryptography. Theor. Comput. Sci. 240(2): 471-485 (2000) - [c28]Shai Ben-David, Nadav Eiron, Hans Ulrich Simon:
The Computational Complexity of Densest Region Detection. COLT 2000: 255-265 - [c27]Matthias Krause, Hans Ulrich Simon:
Determining the Optimal Contrast for Secret Sharing Schemes in Visual Cryptography. LATIN 2000: 280-291 - [c26]Shai Ben-David, Hans Ulrich Simon:
Efficient Learning of Linear Perceptrons. NIPS 2000: 189-195 - [c25]Christian Kuhlmann, Hans Ulrich Simon:
Construction of visual secret sharing schemes with almost optimal contrast. SODA 2000: 263-272 - [i1]Matthias Krause, Hans Ulrich Simon:
Determining the Optimal Contrast for Secret Sharing Schemes in Visual Cryptography. Electron. Colloquium Comput. Complex. 7(3) (2000)
1990 – 1999
- 1999
- [j18]Nicolò Cesa-Bianchi, Eli Dichterman, Paul Fischer, Eli Shamir, Hans Ulrich Simon:
Sample-Efficient Strategies for Learning in the Presence of Noise. J. ACM 46(5): 684-719 (1999) - [c24]José L. Balcázar, Jorge Castro, David Guijarro, Hans Ulrich Simon:
The Consistency Dimension and Distribution-Dependent Learning from Queries (Extended Abstract). ALT 1999: 77-92 - [e1]Paul Fischer, Hans Ulrich Simon:
Computational Learning Theory, 4th European Conference, EuroCOLT '99, Nordkirchen, Germany, March 29-31, 1999, Proceedings. Lecture Notes in Computer Science 1572, Springer 1999, ISBN 3-540-65701-0 [contents] - 1998
- [j17]Andreas Birkendorf, Hans Ulrich Simon:
Using Computational Learning Strategies as a Tool for Combinatorial Optimization. Ann. Math. Artif. Intell. 22(3-4): 237-257 (1998) - [j16]Andreas Birkendorf, Eli Dichterman, Jeffrey C. Jackson, Norbert Klasner, Hans Ulrich Simon:
On Restricted-Focus-of-Attention Learnability of Boolean Functions. Mach. Learn. 30(1): 89-123 (1998) - [c23]Andreas Birkendorf, Norbert Klasner, Christian Kuhlmann, Hans Ulrich Simon:
Structural Results about Exact Learning with Unspecified Attribute Values. COLT 1998: 144-153 - [c22]Andreas Birkendorf, Andreas Böker, Hans Ulrich Simon:
Learning Deterministic Finite Automata from Smallest Counterexamples. SODA 1998: 599-608 - 1997
- [j15]Hans Ulrich Simon:
Bounds on the Number of Examples Needed for Learning Functions. SIAM J. Comput. 26(3): 751-763 (1997) - [c21]Thomas Hofmeister, Matthias Krause, Hans Ulrich Simon:
Contrast-Optimal k out of n Secret Sharing Schemes in Visual Cryptography. COCOON 1997: 176-185 - [c20]Nicolò Cesa-Bianchi, Paul Fischer, Eli Shamir, Hans Ulrich Simon:
Randomized Hypotheses and Minimum Disagreement Hypotheses for Learning with Noise. EuroCOLT 1997: 119-133 - 1996
- [j14]Svetlana Anoulova, Paul Fischer, Stefan Pölt, Hans Ulrich Simon:
Probably Almost Bayes Decisions. Inf. Comput. 129(1): 63-71 (1996) - [j13]Hans Ulrich Simon:
General Bounds on the Number of Examples Needed for Learning Probabilistic Concepts. J. Comput. Syst. Sci. 52(2): 239-254 (1996) - [c19]Andreas Birkendorf, Eli Dichterman, Jeffrey C. Jackson, Norbert Klasner, Hans Ulrich Simon:
On Restricted-Focus-of-Attention Learnability of Boolean Functions. COLT 1996: 205-216 - [c18]Nicolò Cesa-Bianchi, Eli Dichterman, Paul Fischer, Hans Ulrich Simon:
Noise-Tolerant Learning Near the Information-Theoretic Bound. STOC 1996: 141-150 - 1995
- [j12]Klaus-Uwe Höffgen, Hans Ulrich Simon, Kevin S. Van Horn:
Robust Trainability of Single Neurons. J. Comput. Syst. Sci. 50(1): 114-125 (1995) - [c17]Norbert Klasner, Hans Ulrich Simon:
From Noise-Free to Noise-Tolerant and from On-line to Batch Learning. COLT 1995: 250-257 - [c16]Hans Ulrich Simon:
Learning decision lists and trees with equivalence-queries. EuroCOLT 1995: 322-336 - 1993
- [c15]Jorge Ricardo Cuellar, Hans Ulrich Simon:
Neural Discriminant Analysis. ALT 1993: 223-236 - [c14]Hans Ulrich Simon:
General Bounds on the Number of Examples Needed for Learning Probabilistic Concepts. COLT 1993: 402-411 - [c13]Hans Ulrich Simon:
Bounds on the number of examples needed for learning functions. EuroCOLT 1993: 83-94 - 1992
- [j11]Paul Fischer, Hans Ulrich Simon:
On Learning Ring-Sum-Expansions. SIAM J. Comput. 21(1): 181-192 (1992) - [c12]Svetlana Anoulova, Paul Fischer, Stefan Pölt, Hans Ulrich Simon:
PAB-Decisions for Boolean and Real-Valued Features. COLT 1992: 353-362 - [c11]Klaus-Uwe Höffgen, Hans Ulrich Simon:
Robust Trainability of Single Neurons. COLT 1992: 428-439 - [p1]Hans Ulrich Simon:
Bemerkungen zum Schätzen von Bayesschen Diskriminantenfunktionen. Informatik 1992: 381-385 - 1991
- [j10]Hans Ulrich Simon:
The Vapnik-Chervonenkis Dimension of Decision Trees with Bounded Rank. Inf. Process. Lett. 39(3): 137-141 (1991) - [j9]Hans Ulrich Simon:
Neuronales Lernen auf der Basis empirischer Daten / Neural Learning Based on Empirical Data. it Inf. Technol. 33(6): 323-328 (1991) - [c10]Paul Fischer, Stefan Pölt, Hans Ulrich Simon:
Probably Almost Bayes Decisions. COLT 1991: 88-94 - [c9]Hans Ulrich Simon:
Algorithmisches Lernen auf der Basis empirischer Daten. Wissensbasierte Systeme 1991: 467-475 - [c8]Bernd Schürmann, Gerd Hirzinger, Daniel Hernández, Hans Ulrich Simon, Heidi Hackbarth:
Neural Control Within the BMFT-Project NERES. Wissensbasierte Systeme 1991: 533-544 - 1990
- [j8]Hans Ulrich Simon:
On Approximate Solutions for Combinatorial Optimization Problems. SIAM J. Discret. Math. 3(2): 294-310 (1990) - [c7]Paul Fischer, Hans Ulrich Simon:
On Learning Ring-Sum-Expansions. COLT 1990: 130-143 - [c6]Hans Ulrich Simon:
On the Number of Examples and Stages Needed for Learning Decision Trees. COLT 1990: 303-313 - [c5]Paul Fischer, Hans Ulrich Simon:
Separation Problems and Circular Arc Systems. WG 1990: 251-259
1980 – 1989
- 1989
- [j7]Hans Ulrich Simon:
Continuous Reductions Among Combinatorial Optimization Problems. Acta Informatica 26(8): 771-785 (1989) - [c4]Hans Ulrich Simon:
Approximation Algorithms for Channel Assignment in Cellular Radio Networks. FCT 1989: 405-415 - 1988
- [j6]Hans Ulrich Simon:
A Continuous Bound on the Performance of Critical-Path Schedules. J. Inf. Process. Cybern. 24(4/5): 171-187 (1988) - [j5]Bernd Becker, Hans Ulrich Simon:
How Robust Is The n-Cube? Inf. Comput. 77(2): 162-178 (1988) - 1986
- [c3]Bernd Becker, Hans Ulrich Simon:
How Robust Is the n-Cube? (Extended Abstract). FOCS 1986: 283-291 - 1983
- [j4]Hans Ulrich Simon:
Pattern Matching in Trees and Nets. Acta Informatica 20: 227-248 (1983) - [j3]Hans Ulrich Simon:
The Structure of the Monoid (N, X) of Logic Circuits. J. Inf. Process. Cybern. 19(6): 279-296 (1983) - [j2]Hans Ulrich Simon:
Classes of X-functions Reducing Pattern Matching on Nets to Pattern Matching on Forests of Binary Trees. J. Inf. Process. Cybern. 19(9): 465-479 (1983) - [c2]Hans Ulrich Simon:
A Tight Omega(loglog n)-Bound on the Time for Parallel Ram's to Compute Nondegenerated Boolean Functions. FCT 1983: 439-444 - 1982
- [j1]Hans Ulrich Simon:
A Tight Omega(log log n)-Bound on the Time for Parallel RAM's to Compute Nondegenerated Boolean Functions. Inf. Control. 55(1-3): 102-106 (1982) - 1981
- [b1]Hans Ulrich Simon:
Komplexitätsbetrachtungen rationaler Baum- und Netzmengen. Saarland University, Saarbrücken, Germany, 1981, pp. 1-147
1970 – 1979
- 1979
- [c1]Hans Ulrich Simon:
Word problems for groups and contextfree recognition. FCT 1979: 417-422