Publications

• M. Blacher, J. Giesen, J. Klaus, Ch. Staudt, S. Laue, V. Leis.
  Efficient and Portable Einstein Summation in SQL, SIGMOD 2023.

• M. Mitterreiter, M. Koch, J. Giesen, S. Laue.
  Why Capsule Neural Networks Do Not Scale: Challenging the Dynamic Parse-Tree Assumption, AAAI 2023.

• J. Giesen, J. Klaus, S. Laue, N. Merk, and K. Wiedom
  Convexity Certificates from Hessians, NeurIPS 2022.

• S. Laue, M. Blacher and J. Giesen
  Optimization for Classical Machine Learning Problems on the GPU, AAAI 2022.

• M. Blacher, J. Giesen, S. Laue, J. Klaus, and V. Leis
  Machine Learning, Linear Algebra, and More: Is SQL All You Need?, CIDR 2022.

• J. Giesen, P. Kahlmeyer, S. Laue, M. Mitterreiter, F. Nussbaum, C. Staudt
  Mixed membership Gaussians, Journal of Multivariate Analysis, 2023.

• J. Giesen, P. Kahlmeyer, S. Laue, M. Mitterreiter, F. Nussbaum, C. Staudt and S. Zarriess
  Method of Moments for Topic Models with Mixed Discrete and Continuous Features, IJCAI 2021.

• S. Laue, M. Mitterreiter, and J. Giesen
  GENO - GENeric Optimization for Classical Machine Learning Made Fast and Easy, AAAI 2020.

• S. Laue, M. Mitterreiter, and J. Giesen
  A Simple and Efficient Tensor Calculus for Machine Learning. Fundam. Informaticae 177(2): 157-179, 2020.
  An extended abstract appeared as:
  A Simple and Efficient Tensor Calculus, AAAI 2020.

• J. Giesen, S. Laue, M. Mitterreiter
  Optimization frameworks for machine learning: Examples and case study. it Inf. Technol. 62(3-4): 169-180, 2020.

• S. Laue, M. Mitterreiter, and J. Giesen
  GENO - GENeric Optimization for Classical Machine Learning, NeurIPS 2019.

• S. Laue, and J. Giesen
  Combining ADMM and the Augmented Lagrangian Method for Efficiently Handling Many Constraints, IJCAI 2019.

• S. Laue, M. Mitterreiter, J. Giesen
  GENO - GENeric Optimization for Classical Machine Learning, arXiv 2019.

• J. Giesen, J. Klaus, S. Laue, and F. Schreck
  Visualization Support for Developing a Matrix Calculus Algorithm: A Case Study, EuroVis 2019.

• V. H. Do, M. Blazevic, P. Monteagudo, L. Borozan, K. Elbassioni, S. Laue, F. Rojas Ringeling, D. Matijevic, and S.Canzar
  Dynamic Pseudo-time Warping of Complex Single-Cell Trajectories, RECOMB 2019.

• J. Giesen, S. Laue, A. Loehne, and Ch. Schneider
  Using Benson’s Algorithm for Regularization Parameter Tracking, AAAI 2019.

• S. Laue
  On the Equivalence of Forward Mode Automatic Differentiation and Symbolic Differentiation, arXiv 2019.

• S. Laue, M. Mitterreiter, and J. Giesen
  Computing Higher Order Derivatives for Matrix and Tensor Expressions, NIPS 2018.

• T. Bläsius, T. Friedrich, A. Krohmer, and S. Laue
  Efficient Embedding of Scale-Free Graphs in the Hyperbolic Plane. IEEE/ACM Trans. Netw. 26(2): 920-933, 2018.
  An extended abstract appeared as:
  Efficient Embedding of Scale-Free Graphs in the Hyperbolic Plane, ESA 2016.
  Recipient of the Best Paper Award.

• S. Funke, S. Laue, and S. Storandt
  Personal Routes with High-Dimensional Costs and Dynamic Approximation Guarantees, SEA 2017.

• S. Funke, S. Laue, and S. Storandt
  Deducing Individual Driving Preferences for User-Aware Navigation, SIGSPATIAL 2016.

• M. von Loos, M. Oezdayi, S. Laue, and H. Meyerhenke
  Generating Massive Complex Networks with Hyperbolic Geometry Faster in Practice, HPEC 2016.

• K. Blechschmidt, J. Giesen, and S. Laue
  Tracking of Approximate Solutions of Parameterized Optimization Problems over Multi-Dimensional (Hyper-)Parameter Domains, ICML 2015.

• S. Jelic, S. Laue, D. Matijevic, and P. Wijerama
  A Fast Parallel Implementation of a PTAS for Fractional Packing and Covering Linear Programs. Intl. Journal of Parallel Programming, 43(5):840-875, 2015.

• J. Giesen, S. Laue, J.K. Müller
  Reconstructing a Sparse Solution from a Compressed Support Vector Machine. MACIS 2015: 305-319

• J. Giesen, S. Laue, and P. Wieschollek
  Robust and Efficient Kernel Hyperparameter Paths with Guarantees, ICML 2014.

• J. Giesen, L. Kühne, and S. Laue
  Sketching the Support of a Probability Measure, AISTATS 2014.

• S. Laue
  A Hybrid Algorithm for Convex Semidefinite Optimization, ICML 2012.

• J. Giesen, S. Laue, J. Mueller, and S. Swiercy
  Approximating Concavely Parameterized Optimization Problems, NIPS 2012.

• J. Giesen, M. Jaggi, and S. Laue
  Optimizing over the Growing Spectrahedron, ESA 2012.

• J. Giesen, M. Jaggi, and S. Laue
  Regularization Paths with Guarantees for Convex Semidefinite Optimization, AISTATS 2012.

• G. Dinu, S. Thater, and S. Laue
  A Comparison of Models of Word Meaning in Context, NAACL 2012.

• J. Giesen, M. Jaggi, and S. Laue
  Approximating Parameterized Convex Optimization Problems ACM Transactions on Algorithms, 9(1):10, 2012.
  An extended abstract appeared as:
  Approximating Parameterized Convex Optimization Problems, ESA 2010.

• S. Laue
  Geometric Set Cover and Hitting Sets for Polytopes in R^3, STACS 2008.

• S. Funke , S. Laue, R. Naujoks , and Z. Lotker
  Power assignment problems in wireless communication: Covering points by disks, reaching few receivers quickly, and energy-efficient travelling salesman tours. Ad Hoc Networks 9(6): 1028-1035, 2011.
  An extended abstract appeared as:
  Power Assignment Problems in Wireless Communication: Covering Points by Disks, Reaching few Receivers Quickly, and Energy-efficient Travelling Salesman Tours, DCOSS 2008.

• S. Laue and D. Matijevic
  Approximating k-hop Minimum Spanning Trees in Euclidean Metrics Information Processing Letters, 107/3-4:96-101, 2008.
  An extended abstract appeared as:
  Approximating k-hop Minimum Spanning Trees in Euclidean Metrics, CCCG 2007.

• S. Funke , S. Laue, and R. Naujoks
  Minimum-Energy Broadcast with Few Senders, DCOSS 2007.

• S. Funke and S. Laue
  Bounded-Hop Energy-Efficient Broadcast in Low-Dimensional Metrics Via Coresets, STACS 2007.

• F. Eisenbrand and S. Laue
  A linear algorithm for integer programming in the plane. Mathematical Programming, 102(2):249-259, 2005.
  An extended abstract appeared as:
  A faster algorithm for two variable integer programming, ISAAC 2003.

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