Martin Slawski

36 papers A* 1A 3B 1Journal 23Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Linear Regression from 1-bit Quantized Data. CoRR Daniel Hill, Martin Slawski
2024	J	`jnl`	Permuted and Unlinked Monotone Regression in R^d: an approach based on mixture modeling and optimal transport. J. Mach. Learn. Res. Martin Slawski, Bodhisattva Sen
2023	A	`conf`	Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group. AISTATS Zhenbang Wang, Emanuel Ben-David, Martin Slawski
2022	J	`jnl`	Permuted and Unlinked Monotone Regression in R CoRR Martin Slawski, Bodhisattva Sen
2022	J	`jnl`	The Benefits of Diversity: Permutation Recovery in Unlabeled Sensing From Multiple Measurement Vectors. IEEE Trans. Inf. Theory Hang Zhang, Martin Slawski, Ping Li
2021	J	`jnl`	A Pseudo-Likelihood Approach to Linear Regression With Partially Shuffled Data. J. Comput. Graph. Stat. Martin Slawski, Guoqing Diao, Emanuel Ben-David
2021	J	`jnl`	Large-scale Cost-Aware Classification Using Feature Computational Dependency Graph. IEEE Trans. Knowl. Data Eng. Qingzhe Li, Amir Alipour-Fanid, Martin Slawski, Yanfang Ye, Lingfei Wu, Kai Zeng, Liang Zhao
2021	J	`jnl`	Order-Constrained ROC Regression With Application to Facial Recognition. Technometrics Xiaochen Zhu, Martin Slawski, P. Jonathon Phillips, Liansheng Larry Tang
2021	J	`jnl`	Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group. CoRR Zhenbang Wang, Emanuel Ben-David, Martin Slawski
2020	—	`conf`	Asynchronous Online Federated Learning for Edge Devices with Non-IID Data. IEEE BigData Yujing Chen, Yue Ning, Martin Slawski, Huzefa Rangwala
2020	J	`jnl`	Comparison of statistical learning approaches for cerebral aneurysm rupture assessment. Int. J. Comput. Assist. Radiol. Surg. Felicitas J. Detmer, Daniel Lückehe, Fernando Mut, Martin Slawski, Sven Hirsch, Philippe Bijlenga, Gabriele von Voigt, Juan R. Cebral
2020	J	`jnl`	Two-Stage Approach to Multivariate Linear Regression with Sparsely Mismatched Data. J. Mach. Learn. Res. Martin Slawski, Emanuel Ben-David, Ping Li
2019	J	`jnl`	A Pseudo-Likelihood Approach to Linear Regression with Partially Shuffled Data. CoRR Martin Slawski, Guoqing Diao, Emanuel Ben-David
2019	A	`conf`	A Sparse Representation-Based Approach to Linear Regression with Partially Shuffled Labels. UAI Martin Slawski, Mostafa Rahmani, Ping Li
2019	J	`jnl`	A Two-Stage Approach to Multivariate Linear Regression with Sparsely Mismatched Data. CoRR Martin Slawski, Emanuel Ben-David, Ping Li
2019	B	`conf`	Permutation Recovery from Multiple Measurement Vectors in Unlabeled Sensing. ISIT Hang Zhang, Martin Slawski, Ping Li
2019	J	`jnl`	Permutation Recovery from Multiple Measurement Vectors in Unlabeled Sensing. CoRR Hang Zhang, Martin Slawski, Ping Li
2018	J	`jnl`	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. Felicitas J. Detmer, Bong Jae Chung, Fernando Mut, Martin Slawski, Farid Hamzei-Sichani, Christopher M. Putman, Carlos Jiménez, Juan R. Cebral
2018	J	`jnl`	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 Martin Slawski, Ping Li
2018	A*	`conf`	Prediction-time Efficient Classification Using Feature Computational Dependencies. KDD Liang Zhao, Amir Alipour-Fanid, Martin Slawski, Kai Zeng
2017	A	`conf`	Compressed Least Squares Regression revisited. AISTATS Martin Slawski
2017	—	`conf`	Simple strategies for recovering inner products from coarsely quantized random projections. NIPS Ping Li, Martin Slawski
2016	J	`jnl`	Linear signal recovery from b-bit-quantized linear measurements: precise analysis of the trade-off between bit depth and number of measurements. CoRR Martin Slawski, Ping Li
2016	J	`jnl`	Methods for Sparse and Low-Rank Recovery under Simplex Constraints. CoRR Ping Li, Syama Sundar Rangapuram, Martin Slawski
2016	—	`conf`	Quantized Random Projections and Non-Linear Estimation of Cosine Similarity. NIPS Ping Li, Michael Mitzenmacher, Martin Slawski
2015	—	`conf`	Regularization-Free Estimation in Trace Regression with Symmetric Positive Semidefinite Matrices. NIPS Martin Slawski, Ping Li, Matthias Hein
2015	J	`jnl`	Regularization-free estimation in trace regression with symmetric positive semidefinite matrices. CoRR Martin Slawski, Ping Li, Matthias Hein
2015	—	`—`	Topics in learning sparse and low-rank models of non-negative data. Martin Slawski
2015	—	`conf`	b-bit Marginal Regression. NIPS Martin Slawski, Ping Li
2014	J	`jnl`	Matrix factorization with Binary Components. CoRR Martin Slawski, Matthias Hein, Pavlo Lutsik
2013	—	`conf`	Matrix factorization with binary components. NIPS Martin Slawski, Matthias Hein, Pavlo Lutsik
2012	J	`jnl`	Isotope pattern deconvolution for peptide mass spectrometry by non-negative least squares/least absolute deviation template matching. BMC Bioinform. Martin Slawski, Rene Hussong, Andreas Tholey, Thomas Jakoby, Barbara Gregorius, Andreas Hildebrandt, Matthias Hein
2012	J	`jnl`	The structured elastic net for quantile regression and support vector classification. Stat. Comput. Martin Slawski
2011	—	`conf`	Sparse recovery by thresholded non-negative least squares. NIPS Martin Slawski, Matthias Hein
2009	J	`jnl`	Stability and aggregation of ranked gene lists. Briefings Bioinform. Anne-Laure Boulesteix, Martin Slawski
2008	J	`jnl`	CMA - a comprehensive Bioconductor package for supervised classification with high dimensional data. BMC Bioinform. Martin Slawski, Martin Daumer, Anne-Laure Boulesteix