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ORCIDHaim Schweitzer
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- affiliation: University of Texas at Dallas, USA
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2020 – today
- 2024
[j20]Guihong Wan
, Baokun He, Haim Schweitzer:
The art of centering without centering for robust principal component analysis. Data Min. Knowl. Discov. 38(2): 699-724 (2024)- [j19]Guihong Wan, Haim Schweitzer:
Spectral pursuit for simultaneous sparse representation with accuracy guarantees. Int. J. Data Sci. Anal. 17(4): 425-441 (2024) - [c47]Wei Mao, Guihong Wan, Haim Schweitzer:
Graph Clustering Methods Derived from Column Subset Selection (Student Abstract). AAAI 2024: 23573-23575 - [c46]Guihong Wan, Wei Mao, Yevgeniy R. Semenov, Haim Schweitzer:
Equivalence between Graph Spectral Clustering and Column Subset Selection (Student Abstract). AAAI 2024: 23673-23675 - [c45]Boshen Yan, Guihong Wan, Haim Schweitzer, Zoltan Maliga, Sara Khattab, Kun-Hsing Yu, Peter K. Sorger, Yevgeniy R. Semenov:
Pass-Efficient Algorithms for Graph Spectral Clustering (Student Abstract). AAAI 2024: 23690-23692 - 2023
- [c44]Guihong Wan, Meng Jiao, Xinglong Ju, Yu Zhang, Haim Schweitzer, Feng Liu:
Electrophysiological Brain Source Imaging via Combinatorial Search with Provable Optimality. AAAI 2023: 12491-12499 - 2021
- [c43]Guihong Wan, Haim Schweitzer:
Accelerated Combinatorial Search for Outlier Detection with Provable Bound on Sub-Optimality. AAAI 2021: 12436-12444 - [c42]Guihong Wan, Haim Schweitzer:
A New Robust Subspace Recovery Algorithm (Student Abstract). AAAI 2021: 15911-15912 - [c41]Guihong Wan, Haim Schweitzer:
Edge Sparsification for Graphs via Meta-Learning. ICDE 2021: 2733-2738 - [c40]Guihong Wan, Haim Schweitzer:
A Lookahead Algorithm for Robust Subspace Recovery. ICDM 2021: 1379-1384 - [c39]Guihong Wan, Haim Schweitzer:
Heuristic Search for Approximating One Matrix in Terms of Another Matrix. IJCAI 2021: 1600-1606 - [c38]Guihong Wan, Haim Schweitzer:
A Fast Algorithm for Simultaneous Sparse Approximation. PAKDD (3) 2021: 42-54 - 2020
- [c37]Baokun He, Guihong Wan, Haim Schweitzer:
A Bias Trick for Centered Robust Principal Component Analysis (Student Abstract). AAAI 2020: 13807-13808 - [c36]Guihong Wan, Crystal Maung, Chenxu Zhang, Haim Schweitzer:
Fast Distance Metrics in Low-dimensional Space for Neighbor Search Problems. ICDM 2020: 1304-1309
2010 – 2019
- 2019
- [c35]Baokun He, Swair Shah, Crystal Maung, Gordon Arnold, Guihong Wan, Haim Schweitzer:
Heuristic Search Algorithm for Dimensionality Reduction Optimally Combining Feature Selection and Feature Extraction. AAAI 2019: 2280-2287 - [c34]Guihong Wan, Crystal Maung, Haim Schweitzer:
Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method. ICTAI 2019: 808-815 - [i2]Guihong Wan, Crystal Maung, Haim Schweitzer:
Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method. CoRR abs/1907.11094 (2019) - [i1]Baokun He, Guihong Wan, Haim Schweitzer:
A Bias Trick for Centered Robust Principal Component Analysis. CoRR abs/1911.08024 (2019) - 2018
- [j18]Swair Shah, Baokun He, Crystal Maung, Haim Schweitzer:
Computing Robust Principal Components by A* Search. Int. J. Artif. Intell. Tools 27(7): 1860013:1-1860013:19 (2018) - [j17]Ke Xu, Crystal Maung, Hiromasa Arai, Haim Schweitzer:
Two-Stage Feature Selection with Unsupervised Second Stage. Int. J. Artif. Intell. Tools 27(7): 1860014:1-1860014:18 (2018) - [c33]Swair Shah, Baokun He, Ke Xu, Crystal Maung, Haim Schweitzer:
Solving Generalized Column Subset Selection With Heuristic Search. AAAI 2018: 8153-8154 - 2017
- [c32]Ke Xu, Tongyi Cao, Swair Shah, Crystal Maung, Haim Schweitzer:
Cleaning the Null Space: A Privacy Mechanism for Predictors. AAAI 2017: 2789-2795 - [c31]Ke Xu, Swair Shah, Tongyi Cao, Crystal Maung, Haim Schweitzer:
Enhancing the Privacy of Predictors. AAAI 2017: 5009-5010 - [c30]Ke Xu, Hiromasa Arai, Crystal Maung, Haim Schweitzer:
Two-Stage Feature Selection with Unsupervised Second Stage. ICTAI 2017: 153-159 - [c29]Swair Shah, Baokun He, Crystal Maung, Haim Schweitzer:
Computing Robust Principal Components by A* Search. ICTAI 2017: 1042-1049 - 2016
- [c28]Hiromasa Arai, Crystal Maung, Ke Xu, Haim Schweitzer:
Unsupervised Feature Selection by Heuristic Search with Provable Bounds on Suboptimality. AAAI 2016: 666-672 - [c27]Hiromasa Arai, Ke Xu, Crystal Maung, Haim Schweitzer:
Weighted A* Algorithms for Unsupervised Feature Selection with Provable Bounds on Suboptimality. AAAI 2016: 4194-4195 - 2015
- [j16]Crystal Maung, Haim Schweitzer:
Improved Greedy Algorithms for Sparse Approximation of a Matrix in Terms of Another Matrix. IEEE Trans. Knowl. Data Eng. 27(3): 769-780 (2015) - [c26]Hiromasa Arai, Crystal Maung, Haim Schweitzer:
Optimal Column Subset Selection by A-Star Search. AAAI 2015: 1079-1085 - 2013
- [c25]Crystal Maung, Haim Schweitzer:
Pass-efficient unsupervised feature selection. NIPS 2013: 1628-1636 - 2011
- [j15]Haim Schweitzer, Rui A. Deng, Robert Finis Anderson:
A Dual-Bound Algorithm for Very Fast and Exact Template Matching. IEEE Trans. Pattern Anal. Mach. Intell. 33(3): 459-470 (2011)
2000 – 2009
- 2009
- [c24]Haim Schweitzer, Robert Finis Anderson, Rui A. Deng:
A near optimal acceptance-rejection algorithm for exact cross-correlation search. ICCV 2009: 1089-1094 - [c23]Robert Finis Anderson, Haim Schweitzer:
Fixed Time Template Matching. SMC 2009: 1359-1364 - 2005
- [c22]Feng Wu, Haim Schweitzer:
Fast Selection of Linear Features in Image Data. CVPR Workshops 2005: 49 - [c21]Feng Wu, Haim Schweitzer:
Feature Selection for Learning from Images. VISION 2005: 127-133 - 2004
- [c20]Tomohiro Yoshizawa, Haim Schweitzer:
Long-term learning of semantic grouping from relevance-feedback. Multimedia Information Retrieval 2004: 165-172 - 2002
- [c19]Haim Schweitzer, J. W. Bell, Feng Wu:
Very Fast Template Matching. ECCV (4) 2002: 358-372 - [c18]Haim Schweitzer:
Computing Content-Plots for Video. ECCV (4) 2002: 491-501 - 2001
- [c17]Haim Schweitzer:
Template Matching Approach to Content Based Image Indexing by Low Dimensional Euclidean Embedding. ICCV 2001: 566-571
1990 – 1999
- 1999
- [j14]Haim Schweitzer:
Organizing image databases as visual-content search trees. Image Vis. Comput. 17(7): 501-511 (1999) - [j13]Haim Schweitzer:
Precise induction from statistical data. J. Exp. Theor. Artif. Intell. 11(2): 185-199 (1999) - [c16]Haim Schweitzer:
Optimal Eigenfeature Selection by Optimal Image Registration. CVPR 1999: 1219-1224 - [c15]Haim Schweitzer:
Utilizing Scatter for Pixel Subspace Selection. ICCV 1999: 1111-1116 - 1998
- [j12]Haim Schweitzer, Janell Straach:
Utilizing Moment Invariants and Grobner Bases to Reason about Shapes. Comput. Intell. 14(4): 461-474 (1998) - [j11]Haim Schweitzer, Sanjeev R. Kulkarni:
Computational limitations of model-based recognition. Int. J. Intell. Syst. 13(5): 431-443 (1998) - [c14]Haim Schweitzer:
Computing Ritz Approximations of Primary Images. ICCV 1998: 139-144 - [c13]Haim Schweitzer:
Indexing Images by Trees of Visual Content. ICCV 1998: 582-587 - 1997
- [j10]Haim Schweitzer:
A Distributed Algorithm for Content Based Indexing of Images by Projections on Ritz Primary Images. Data Min. Knowl. Discov. 1(4): 375-390 (1997) - [c12]Haim Schweitzer:
Classification and Reductio-ad-Absurdum Optimality Proofs. AAAI/IAAI 1997: 88-93 - 1996
- [c11]Haim Schweitzer, Radha Krishnan:
Structure from Multiple 2D Affine Correspondences without Camera Calibration. CVPR 1996: 258-263 - 1995
- [j9]Haim Schweitzer:
Occam Algorithms for Computing Visual Motion. IEEE Trans. Pattern Anal. Mach. Intell. 17(11): 1033-1042 (1995) - [c10]Haim Schweitzer, Janell Straach:
Utilizing Moment Invariants and Gröbner Bases to Reason About Shapes. IJCAI (1) 1995: 908-914 - 1993
- [c9]Haim Schweitzer:
A surface matching algorithm for two perspective views. CVPR 1993: 742-743 - [c8]Haim Schweitzer:
Occam algorithms for computing visual motion. ICCV 1993: 551-555 - 1991
- [j8]James R. Bergen, Haim Schweitzer:
A Probabilistic Algorithm for Computing Hough Transforms. J. Algorithms 12(4): 639-656 (1991) - 1990
- [j7]Haim Schweitzer:
A Necessary Condition for Learning from Positive Examples. Mach. Learn. 5: 101-113 (1990) - [j6]Haim Shvaytser:
Learnable and Nonlearnable Visual Concepts. IEEE Trans. Pattern Anal. Mach. Intell. 12(5): 459-466 (1990) - [j5]Lisa Gottesfeld Brown, Haim Shvaytser:
Surface Orientation from Projective Foreshortening of Isotropic Texture Autocorrelation. IEEE Trans. Pattern Anal. Mach. Intell. 12(6): 584-588 (1990) - [c7]Haim Schweitzer:
Probabilities that Imply Certainties. AAAI 1990: 665-670 - [c6]Haim Shvaytser:
Towards a computational theory of model based vision and perception. ICCV 1990: 283-286
1980 – 1989
- 1988
- [c5]Haim Schweitzer:
Non-Learnable Classes of Boolean Formulae That Are Closer Under Variable Permutation. COLT 1988: 155-166 - [c4]Lisa Gottesfeld Brown, Haim Shvaytser:
Surface orientation from projective foreshortening of isotropic texture autocorrelation. CVPR 1988: 510-514 - [c3]Haim Shvaytser:
Detecting motion in out-of-register pictures. CVPR 1988: 696-701 - [c2]Haim Shvaytser:
Learnable And Non-learnable Visual Concepts. ICCV 1988: 264-268 - [c1]Haim Shvaytser:
Representing Knowledge in Learning Systems by Pseudo Boolean Functions. TARK 1988: 245-259 - 1987
- [j4]Haim Shvaytser, Shmuel Peleg:
Inversion of picture operators. Pattern Recognit. Lett. 5(1): 49-61 (1987) - [j3]Haim Shvaytser, Shmuel Peleg:
Representation of patterns of symbols by equations with applications to puzzle solving. Pattern Recognit. Lett. 5(2): 119-128 (1987) - 1986
- [b1]Haim Shvaytser:
Mathematical models in image processing and pattern recognition (מודלים מתמטיים בעבוד תמונות וזהוי צורות.). Hebrew University of Jerusalem, Israel, 1986 - 1985
- [j2]Haim Shvaytser, Shmuel Peleg:
Fuzzy and probability vectors as elements of a vector space. Inf. Sci. 36(3): 231-247 (1985) - [j1]Eli Harouche, Shmuel Peleg, Haim Shvaytser, Larry S. Davis:
Noisy image restoration by cost function minimization. Pattern Recognit. Lett. 3(1): 65-69 (1985)
Coauthor Index
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