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ORCIDSören Laue
Person information
- affiliation: University of Hamburg, Germany
- affiliation (former): Friedrich Schiller University Jena, Faculty of Mathematics and Computer Science, Germany
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2020 – today
- 2024
[j12]Stefan Canzar
, Van Hoan Do, Slobodan Jelic, Sören Laue, Domagoj Matijevic, Tomislav Prusina:
Metric multidimensional scaling for large single-cell datasets using neural networks. Algorithms Mol. Biol. 19(1): 21 (2024)- [c35]Michaela Regneri, Alhassan Abdelhalim, Sören Laue:
Detecting Conceptual Abstraction in LLMs. LREC/COLING 2024: 4697-4704 - [i13]Michaela Regneri, Alhassan Abdelhalim, Sören Laue:
Detecting Conceptual Abstraction in LLMs. CoRR abs/2404.15848 (2024) - [i12]Sören Laue, Tomislav Prusina:
Efficient Line Search Method Based on Regression and Uncertainty Quantification. CoRR abs/2405.10897 (2024) - 2023
- [j11]Joachim Giesen, Paul Kahlmeyer, Sören Laue, Matthias Mitterreiter, Frank Nussbaum, Christoph Staudt:
Mixed membership Gaussians. J. Multivar. Anal. 195: 105141 (2023) - [j10]Mark Blacher, Julien Klaus, Christoph Staudt, Sören Laue, Viktor Leis, Joachim Giesen:
Efficient and Portable Einstein Summation in SQL. Proc. ACM Manag. Data 1(2): 121:1-121:19 (2023) - [c34]Matthias Mitterreiter, Marcel Koch, Joachim Giesen, Sören Laue:
Why Capsule Neural Networks Do Not Scale: Challenging the Dynamic Parse-Tree Assumption. AAAI 2023: 9209-9216 - [i11]Matthias Mitterreiter, Marcel Koch, Joachim Giesen, Sören Laue:
Why Capsule Neural Networks Do Not Scale: Challenging the Dynamic Parse-Tree Assumption. CoRR abs/2301.01583 (2023) - 2022
- [c33]Sören Laue, Mark Blacher, Joachim Giesen:
Optimization for Classical Machine Learning Problems on the GPU. AAAI 2022: 7300-7308 - [c32]Mark Blacher, Joachim Giesen, Sören Laue, Julien Klaus, Viktor Leis:
Machine Learning, Linear Algebra, and More: Is SQL All You Need? CIDR 2022 - [c31]Julien Klaus, Niklas Merk, Konstantin Wiedom, Sören Laue, Joachim Giesen:
Convexity Certificates from Hessians. NeurIPS 2022 - [p1]Joachim Giesen, Lars Kuehne, Sören Laue:
The GENO Software Stack. Algorithms for Big Data 2022: 213-228 - [i10]Sören Laue, Mark Blacher, Joachim Giesen:
Optimization for Classical Machine Learning Problems on the GPU. CoRR abs/2203.16340 (2022) - [i9]Julien Klaus, Niklas Merk, Konstantin Wiedom, Sören Laue, Joachim Giesen:
Convexity Certificates from Hessians. CoRR abs/2210.10430 (2022) - 2021
- [c30]Joachim Giesen, Paul Kahlmeyer, Sören Laue, Matthias Mitterreiter, Frank Nussbaum, Christoph Staudt, Sina Zarrieß:
Method of Moments for Topic Models with Mixed Discrete and Continuous Features. IJCAI 2021: 2418-2424 - 2020
- [j9]Sören Laue, Matthias Mitterreiter, Joachim Giesen:
A Simple and Efficient Tensor Calculus for Machine Learning. Fundam. Informaticae 177(2): 157-179 (2020) - [j8]Joachim Giesen, Sören Laue, Matthias Mitterreiter:
Optimization frameworks for machine learning: Examples and case study. it Inf. Technol. 62(3-4): 169-180 (2020) - [c29]Sören Laue, Matthias Mitterreiter, Joachim Giesen:
A Simple and Efficient Tensor Calculus. AAAI 2020: 4527-4534 - [c28]Sören Laue, Matthias Mitterreiter, Joachim Giesen:
GENO - Optimization for Classical Machine Learning Made Fast and Easy. AAAI 2020: 13620-13621 - [c27]Mark Blacher, Joachim Giesen, Sören Laue, Julien Klaus, Matthias Mitterreiter:
Fast Entity Resolution With Mock Labels and Sorted Integer Sets. DI2KG@VLDB 2020 - [i8]Sören Laue, Matthias Mitterreiter, Joachim Giesen:
A Simple and Efficient Tensor Calculus for Machine Learning. CoRR abs/2010.03313 (2020)
2010 – 2019
- 2019
- [j7]Joachim Giesen, Julien Klaus, Sören Laue, Ferdinand Schreck:
Visualization Support for Developing a Matrix Calculus Algorithm: A Case Study. Comput. Graph. Forum 38(3): 351-361 (2019) - [c26]Joachim Giesen, Sören Laue, Andreas Löhne, Christopher Schneider:
Using Benson's Algorithm for Regularization Parameter Tracking. AAAI 2019: 3689-3696 - [c25]Joachim Giesen, Sören Laue:
Combining ADMM and the Augmented Lagrangian Method for Efficiently Handling Many Constraints. IJCAI 2019: 4525-4531 - [c24]Sören Laue, Matthias Mitterreiter, Joachim Giesen:
GENO - GENeric Optimization for Classical Machine Learning. NeurIPS 2019: 2187-2198 - [c23]Sören Laue, Matthias Mitterreiter, Joachim Giesen:
MatrixCalculus.org - Computing Derivatives of Matrix and Tensor Expressions. ECML/PKDD (3) 2019: 769-772 - [c22]Van Hoan Do, Mislav Blazevic, Pablo Monteagudo, Luka Borozan, Khaled M. Elbassioni, Sören Laue, Francisca Rojas Ringeling, Domagoj Matijevic, Stefan Canzar:
Dynamic Pseudo-time Warping of Complex Single-Cell Trajectories. RECOMB 2019: 294-296 - [i7]Sören Laue:
On the Equivalence of Forward Mode Automatic Differentiation and Symbolic Differentiation. CoRR abs/1904.02990 (2019) - [i6]Sören Laue, Matthias Mitterreiter, Joachim Giesen:
GENO - GENeric Optimization for Classical Machine Learning. CoRR abs/1905.13587 (2019) - 2018
- [j6]Thomas Bläsius, Tobias Friedrich, Anton Krohmer, Sören Laue:
Efficient Embedding of Scale-Free Graphs in the Hyperbolic Plane. IEEE/ACM Trans. Netw. 26(2): 920-933 (2018) - [c21]Sören Laue, Matthias Mitterreiter, Joachim Giesen:
Computing Higher Order Derivatives of Matrix and Tensor Expressions. NeurIPS 2018: 2755-2764 - 2017
- [c20]Stefan Funke, Sören Laue, Sabine Storandt:
Personal Routes with High-Dimensional Costs and Dynamic Approximation Guarantees. SEA 2017: 18:1-18:13 - 2016
- [c19]Thomas Bläsius, Tobias Friedrich, Anton Krohmer, Sören Laue:
Efficient Embedding of Scale-Free Graphs in the Hyperbolic Plane. ESA 2016: 16:1-16:18 - [c18]Stefan Funke, Sören Laue, Sabine Storandt:
Deducing individual driving preferences for user-aware navigation. SIGSPATIAL/GIS 2016: 14:1-14:9 - [c17]Moritz von Looz, Mustafa Safa Özdayi, Sören Laue, Henning Meyerhenke:
Generating massive complex networks with hyperbolic geometry faster in practice. HPEC 2016: 1-6 - [i5]Moritz von Looz, Mustafa Özdayi, Sören Laue, Henning Meyerhenke:
Generating massive complex networks with hyperbolic geometry faster in practice. CoRR abs/1606.09481 (2016) - [i4]Joachim Giesen, Sören Laue:
Distributed Convex Optimization with Many Convex Constraints. CoRR abs/1610.02967 (2016) - 2015
- [j5]Slobodan Jelic, Sören Laue, Domagoj Matijevic, Patrick Wijerama:
A Fast Parallel Implementation of a PTAS for Fractional Packing and Covering Linear Programs. Int. J. Parallel Program. 43(5): 840-875 (2015) - [c16]Katharina Blechschmidt, Joachim Giesen, Sören Laue:
Tracking Approximate Solutions of Parameterized Optimization Problems over Multi-Dimensional (Hyper-)Parameter Domains. ICML 2015: 438-447 - [c15]Joachim Giesen, Sören Laue, Jens K. Müller:
Reconstructing a Sparse Solution from a Compressed Support Vector Machine. MACIS 2015: 305-319 - 2014
- [c14]Joachim Giesen, Sören Laue, Lars Kuehne:
Sketching the Support of a Probability Measure. AISTATS 2014: 257-265 - [c13]Joachim Giesen, Sören Laue, Patrick Wieschollek:
Robust and Efficient Kernel Hyperparameter Paths with Guarantees. ICML 2014: 1296-1304 - 2012
- [j4]Joachim Giesen, Martin Jaggi, Sören Laue:
Approximating parameterized convex optimization problems. ACM Trans. Algorithms 9(1): 10:1-10:17 (2012) - [c12]Joachim Giesen, Martin Jaggi, Sören Laue:
Optimizing over the Growing Spectrahedron. ESA 2012: 503-514 - [c11]Sören Laue:
A Hybrid Algorithm for Convex Semidefinite Optimization. ICML 2012 - [c10]Georgiana Dinu, Stefan Thater, Sören Laue:
A comparison of models of word meaning in context. HLT-NAACL 2012: 611-615 - [c9]Joachim Giesen, Jens K. Müller, Sören Laue, Sascha Swiercy:
Approximating Concavely Parameterized Optimization Problems. NIPS 2012: 2114-2122 - [c8]Joachim Giesen, Martin Jaggi, Sören Laue:
Regularization Paths with Guarantees for Convex Semidefinite Optimization. AISTATS 2012: 432-439 - [i3]Sören Laue:
A Hybrid Algorithm for Convex Semidefinite Optimization. CoRR abs/1206.4608 (2012) - 2011
- [j3]Stefan Funke, Sören Laue, Zvi Lotker, Rouven Naujoks:
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) - 2010
- [c7]Joachim Giesen, Martin Jaggi, Sören Laue:
Approximating Parameterized Convex Optimization Problems. ESA (1) 2010: 524-535
2000 – 2009
- 2008
- [b1]Sören Laue:
Approximation algorithms for geometric optimization problems. Saarland University, Germany, 2008 - [j2]Sören Laue, Domagoj Matijevic:
Approximating k-hop minimum spanning trees in Euclidean metrics. Inf. Process. Lett. 107(3-4): 96-101 (2008) - [c6]Stefan Funke, Sören Laue, Rouven Naujoks, Zvi Lotker:
Power Assignment Problems in Wireless Communication: Covering Points by Disks, Reaching few Receivers Quickly, and Energy-Efficient Travelling Salesman Tours. DCOSS 2008: 282-295 - [c5]Sören Laue:
Geometric Set Cover and Hitting Sets for Polytopes in R3. STACS 2008: 479-490 - [i2]Sören Laue:
Geometric Set Cover and Hitting Sets for Polytopes in $R^3$. CoRR abs/0802.2861 (2008) - 2007
- [c4]Sören Laue, Domagoj Matijevic:
Approximating k-hop Minimum Spanning Trees in Euclidean Metrics. CCCG 2007: 117-120 - [c3]Stefan Funke, Sören Laue, Rouven Naujoks:
Minimum-Energy Broadcast with Few Senders. DCOSS 2007: 404-416 - [c2]Stefan Funke, Sören Laue:
Bounded-Hop Energy-Efficient Broadcast in Low-Dimensional Metrics Via Coresets. STACS 2007: 272-283 - 2006
- [i1]Stefan Funke, Sören Laue, Zvi Lotker, Rouven Naujoks:
Power Assignment Problems in Wireless Communication. CoRR abs/cs/0612121 (2006) - 2005
- [j1]Friedrich Eisenbrand, Sören Laue:
A linear algorithm for integer programming in the plane. Math. Program. 102(2): 249-259 (2005) - 2003
- [c1]Friedrich Eisenbrand, Sören Laue:
A Faster Algorithm for Two-Variable Integer Programming. ISAAC 2003: 290-299
Coauthor Index
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last updated on 2024-10-16 20:32 CEST by the dblp team
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