default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDMartin Slawski
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
Books and Theses
- 2015
[b1]Martin Slawski:
Topics in learning sparse and low-rank models of non-negative data. Saarland University, 2015
Journal Articles
- 2024
- [j13]Martin Slawski, Bodhisattva Sen:
Permuted and Unlinked Monotone Regression in R^d: an approach based on mixture modeling and optimal transport. J. Mach. Learn. Res. 25: 183:1-183:57 (2024) - 2022
- [j12]Hang Zhang, Martin Slawski, Ping Li
:
The Benefits of Diversity: Permutation Recovery in Unlabeled Sensing From Multiple Measurement Vectors. IEEE Trans. Inf. Theory 68(4): 2509-2529 (2022) - 2021
- [j11]Martin Slawski, Guoqing Diao, Emanuel Ben-David:
A Pseudo-Likelihood Approach to Linear Regression With Partially Shuffled Data. J. Comput. Graph. Stat. 30(4): 991-1003 (2021) - [j10]Xiaochen Zhu, Martin Slawski, P. Jonathon Phillips, Liansheng Larry Tang:
Order-Constrained ROC Regression With Application to Facial Recognition. Technometrics 63(3): 343-353 (2021) - [j9]Qingzhe Li, Amir Alipour-Fanid, Martin Slawski, Yanfang Ye, Lingfei Wu, Kai Zeng, Liang Zhao:
Large-scale Cost-Aware Classification Using Feature Computational Dependency Graph. IEEE Trans. Knowl. Data Eng. 33(5): 2029-2044 (2021) - 2020
- [j8]Felicitas J. Detmer, Daniel Lückehe, Fernando Mut, Martin Slawski, Sven Hirsch, Philippe Bijlenga, Gabriele von Voigt, Juan R. Cebral:
Comparison of statistical learning approaches for cerebral aneurysm rupture assessment. Int. J. Comput. Assist. Radiol. Surg. 15(1): 141-150 (2020) - [j7]Martin Slawski, Emanuel Ben-David, Ping Li:
Two-Stage Approach to Multivariate Linear Regression with Sparsely Mismatched Data. J. Mach. Learn. Res. 21: 204:1-204:42 (2020) - 2018
- [j6]Felicitas J. Detmer, Bong Jae Chung, Fernando Mut, Martin Slawski, Farid Hamzei-Sichani, Christopher M. Putman, Carlos Jiménez, Juan R. Cebral:
Development and internal validation of an aneurysm rupture probability model based on patient characteristics and aneurysm location, morphology, and hemodynamics. Int. J. Comput. Assist. Radiol. Surg. 13(11): 1767-1779 (2018) - [j5]Martin Slawski, Ping Li:
On the Trade-Off Between Bit Depth and Number of Samples for a Basic Approach to Structured Signal Recovery From b-Bit Quantized Linear Measurements. IEEE Trans. Inf. Theory 64(6): 4159-4178 (2018) - 2012
- [j4]Martin Slawski, Rene Hussong, Andreas Tholey, Thomas Jakoby, Barbara Gregorius, Andreas Hildebrandt, Matthias Hein:
Isotope pattern deconvolution for peptide mass spectrometry by non-negative least squares/least absolute deviation template matching. BMC Bioinform. 13: 291 (2012) - [j3]Martin Slawski:
The structured elastic net for quantile regression and support vector classification. Stat. Comput. 22(1): 153-168 (2012) - 2009
- [j2]Anne-Laure Boulesteix, Martin Slawski:
Stability and aggregation of ranked gene lists. Briefings Bioinform. 10(5): 556-568 (2009) - 2008
- [j1]Martin Slawski, Martin Daumer, Anne-Laure Boulesteix:
CMA - a comprehensive Bioconductor package for supervised classification with high dimensional data. BMC Bioinform. 9 (2008)
Conference and Workshop Papers
- 2023
- [c12]Zhenbang Wang, Emanuel Ben-David, Martin Slawski:
Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group. AISTATS 2023: 2939-2959 - 2020
- [c11]Yujing Chen, Yue Ning, Martin Slawski, Huzefa Rangwala:
Asynchronous Online Federated Learning for Edge Devices with Non-IID Data. IEEE BigData 2020: 15-24 - 2019
- [c10]Hang Zhang, Martin Slawski, Ping Li:
Permutation Recovery from Multiple Measurement Vectors in Unlabeled Sensing. ISIT 2019: 1857-1861 - [c9]Martin Slawski, Mostafa Rahmani, Ping Li:
A Sparse Representation-Based Approach to Linear Regression with Partially Shuffled Labels. UAI 2019: 38-48 - 2018
- [c8]Liang Zhao, Amir Alipour-Fanid, Martin Slawski, Kai Zeng:
Prediction-time Efficient Classification Using Feature Computational Dependencies. KDD 2018: 2787-2796 - 2017
- [c7]Martin Slawski:
Compressed Least Squares Regression revisited. AISTATS 2017: 1207-1215 - [c6]Ping Li, Martin Slawski:
Simple strategies for recovering inner products from coarsely quantized random projections. NIPS 2017: 4567-4576 - 2016
- [c5]Ping Li, Michael Mitzenmacher, Martin Slawski:
Quantized Random Projections and Non-Linear Estimation of Cosine Similarity. NIPS 2016: 2748-2756 - 2015
- [c4]Martin Slawski, Ping Li:
b-bit Marginal Regression. NIPS 2015: 2062-2070 - [c3]Martin Slawski, Ping Li, Matthias Hein:
Regularization-Free Estimation in Trace Regression with Symmetric Positive Semidefinite Matrices. NIPS 2015: 2782-2790 - 2013
- [c2]Martin Slawski, Matthias Hein, Pavlo Lutsik:
Matrix factorization with binary components. NIPS 2013: 3210-3218 - 2011
- [c1]Martin Slawski, Matthias Hein:
Sparse recovery by thresholded non-negative least squares. NIPS 2011: 1926-1934
Informal and Other Publications
- 2022
- [i9]Martin Slawski, Bodhisattva Sen:
Permuted and Unlinked Monotone Regression in Rd: an approach based on mixture modeling and optimal transport. CoRR abs/2201.03528 (2022) - 2021
- [i8]Zhenbang Wang, Emanuel Ben-David, Martin Slawski:
Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group. CoRR abs/2111.01767 (2021) - 2019
- [i7]Martin Slawski, Emanuel Ben-David, Ping Li:
A Two-Stage Approach to Multivariate Linear Regression with Sparsely Mismatched Data. CoRR abs/1907.07148 (2019) - [i6]Hang Zhang, Martin Slawski, Ping Li:
Permutation Recovery from Multiple Measurement Vectors in Unlabeled Sensing. CoRR abs/1909.02496 (2019) - [i5]Martin Slawski, Guoqing Diao, Emanuel Ben-David:
A Pseudo-Likelihood Approach to Linear Regression with Partially Shuffled Data. CoRR abs/1910.01623 (2019) - 2016
- [i4]Ping Li, Syama Sundar Rangapuram, Martin Slawski:
Methods for Sparse and Low-Rank Recovery under Simplex Constraints. CoRR abs/1605.00507 (2016) - [i3]Martin Slawski, Ping Li:
Linear signal recovery from b-bit-quantized linear measurements: precise analysis of the trade-off between bit depth and number of measurements. CoRR abs/1607.02649 (2016) - 2015
- [i2]Martin Slawski, Ping Li, Matthias Hein:
Regularization-free estimation in trace regression with symmetric positive semidefinite matrices. CoRR abs/1504.06305 (2015) - 2014
- [i1]Martin Slawski, Matthias Hein, Pavlo Lutsik:
Matrix factorization with Binary Components. CoRR abs/1401.6024 (2014)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 22:15 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
