Christian Kanzow

Computational Theory and Mathematics · 2003–2018

A researcher in the Science corpus: 12 papers; trusts 23 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 50 citations into it; #3,449 of 12,182 by trust here, #1,936 by citations
• Numerical Analysis — 41 citations into it; #937 of 3,586 by trust here, #337 by citations
• Control and Systems Engineering — 13 citations into it; #3,657 of 8,257 by trust here, #4,262 by citations
• Economics and Econometrics — 13 citations into it; #10,660 of 23,481 by trust here, #9,863 by citations
• Artificial Intelligence — 8 citations into it; #9,045 of 35,345 by trust here, #12,387 by citations
• Mathematical Optimization — 7 citations into it
• Management Science and Operations Research — 6 citations into it
• Applied Mathematics — 5 citations into it

Whom Christian Kanzow trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Michael L. Flegel
2. Stefan Scholtes
3. Jane J. Ye
4. Yura Malitsky
5. Alfredo Noel Iusem
6. Rapeepan Kraikaew
7. Tim Hoheisel
8. Boris S. Mordukhovich
9. Michael Brückner
10. Amir Globerson

Who trusts Christian Kanzow overall

1. Michael L. Flegel
2. Tim Hoheisel
3. Battista Biggio
4. Jirí Vladimír Outrata
5. Nedim Srndic
6. Yekini Shehu
7. Fabio Roli
8. Samuel Rota Bulò
9. Davide Maiorca
10. Jacob Steinhardt

Papers from Christian Kanzow's perspective

Ordered by how strongly the researchers Christian Kanzow trusts endorse each paper. Same corpus, a different order for every researcher.

1. Mathematical Programs with Complementarity Constraints: Stationarity, Optimality, and Sensitivity (Mathematics of Operations Research)
2. Convergence Properties of a Regularization Scheme for Mathematical Programs with Complementarity Constraints (SIAM Journal on Optimization)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Learning Multiple Layers of Features from Tiny Images
7. Theorie und Numerik restringierter Optimierungsaufgaben
8. Nightmare at test time: robust learning by feature deletion
9. Error bounds in mathematical programming
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Static prediction games for adversarial learning problems (2012) — 216 citations
• Generalized Nash equilibrium problems (2007) — 1,378 citations
• On the Guignard constraint qualification for mathematical programs with equilibrium constraints (2005) — 120 citations
• Abadie-Type Constraint Qualification for Mathematical Programs with Equilibrium Constraints (2005) — 128 citations
• A Fritz John Approach to First Order Optimality Conditions for Mathematical Programs with Equilibrium Constraints (2003) — 47 citations
• Stationary conditions for mathematical programs with vanishing constraints using weak constraint qualifications (2008) — 89 citations
• First-and second-order optimality conditions for mathematical programs with vanishing constraints (2007) — 86 citations
• Optimality Conditions for Disjunctive Programs with Application to Mathematical Programs with Equilibrium Constraints (2007) — 118 citations
• On the Abadie and Guignard constraint qualifications for Mathematical Programmes with Vanishing Constraints (2009) — 94 citations
• Strong convergence of a double projection-type method for monotone variational inequalities in Hilbert spaces (2018) — 49 citations
• Exact penalty results for mathematical programs with vanishing constraints (2010) — 62 citations
• On M-stationary points for mathematical programs with equilibrium constraints (2005) — 72 citations