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2020 – today
- 2023
[j33]Giora Simchoni, Saharon Rosset:
Integrating Random Effects in Deep Neural Networks. J. Mach. Learn. Res. 24: 156:1-156:57 (2023)- [i12]Yuval Oren, Saharon Rosset:
Mixed Semi-Supervised Generalized-Linear-Regression with applications to Deep learning. CoRR abs/2302.09526 (2023) - 2022
- [j32]Assaf Rabinowicz, Saharon Rosset:
Tree-Based Models for Correlated Data. J. Mach. Learn. Res. 23: 258:1-258:31 (2022) - [i11]Giora Simchoni, Saharon Rosset:
Integrating Random Effects in Deep Neural Networks. CoRR abs/2206.03314 (2022) - 2021
- [c41]Giora Simchoni, Saharon Rosset:
Using Random Effects to Account for High-Cardinality Categorical Features and Repeated Measures in Deep Neural Networks. NeurIPS 2021: 25111-25122 - 2020
- [j31]Amichai Painsky
, Saharon Rosset, Meir Feder:
Innovation Representation of Stochastic Processes With Application to Causal Inference. IEEE Trans. Inf. Theory 66(2): 1136-1154 (2020) - [i10]Yuval Oren, Saharon Rosset:
Semi-Supervised Empirical Risk Minimization: When can unlabeled data improve prediction. CoRR abs/2009.00606 (2020)
2010 – 2019
- 2019
- [j30]Amichai Painsky, Saharon Rosset:
Lossless Compression of Random Forests. J. Comput. Sci. Technol. 34(2): 494-506 (2019) - [j29]Omer Weissbrod, Shachar Kaufman, David Golan, Saharon Rosset:
Maximum Likelihood for Gaussian Process Classification and Generalized Linear Mixed Models under Case-Control Sampling. J. Mach. Learn. Res. 20: 108:1-108:30 (2019) - [i9]Amit Moscovich, Saharon Rosset:
Rescaling and other forms of unsupervised preprocessing introduce bias into cross-validation. CoRR abs/1901.08974 (2019) - [i8]Trevor Hastie, Andrea Montanari, Saharon Rosset, Ryan J. Tibshirani:
Surprises in High-Dimensional Ridgeless Least Squares Interpolation. CoRR abs/1903.08560 (2019) - 2018
- [j28]Regev Schweiger, Eyal Fisher, Elior Rahmani, Liat Shenhav, Saharon Rosset, Eran Halperin:
Using Stochastic Approximation Techniques to Efficiently Construct Confidence Intervals for Heritability. J. Comput. Biol. 25(7): 794-808 (2018) - [j27]Shlomi Lifshits, Omri Tomer, Ittai Shamir, Daniel Barazany, Galia Tsarfaty, Saharon Rosset, Yaniv Assaf:
Resolution considerations in imaging of the cortical layers. NeuroImage 164: 112-120 (2018) - [j26]Amichai Painsky, Saharon Rosset, Meir Feder:
Linear Independent Component Analysis Over Finite Fields: Algorithms and Bounds. IEEE Trans. Signal Process. 66(22): 5875-5886 (2018) - [c40]Blake E. Woodworth, Vitaly Feldman, Saharon Rosset, Nati Srebro:
The Everlasting Database: Statistical Validity at a Fair Price. NeurIPS 2018: 6532-6541 - [c39]Elior Rahmani, Regev Schweiger, Saharon Rosset, Sriram Sankararaman, Eran Halperin:
Tensor Composition Analysis Detects Cell-Type Specific Associations in Epigenetic Studies. RECOMB 2018: 274-275 - [i7]Blake E. Woodworth, Vitaly Feldman, Saharon Rosset, Nathan Srebro:
The Everlasting Database: Statistical Validity at a Fair Price. CoRR abs/1803.04307 (2018) - [i6]Amichai Painsky, Saharon Rosset, Meir Feder:
Linear Independent Component Analysis over Finite Fields: Algorithms and Bounds. CoRR abs/1809.05815 (2018) - [i5]Amichai Painsky, Saharon Rosset:
Lossless (and Lossy) Compression of Random Forests. CoRR abs/1810.11197 (2018) - [i4]Amichai Painsky, Saharon Rosset, Meir Feder:
Innovation Representation of Stochastic Processes with Application to Causal Inference. CoRR abs/1811.10071 (2018) - 2017
- [j25]Omer Weissbrod, Elior Rahmani, Regev Schweiger, Saharon Rosset, Eran Halperin:
Association testing of bisulfite-sequencing methylation data via a Laplace approximation. Bioinform. 33(14): i325-i332 (2017) - [j24]Amichai Painsky, Saharon Rosset:
Cross-Validated Variable Selection in Tree-Based Methods Improves Predictive Performance. IEEE Trans. Pattern Anal. Mach. Intell. 39(11): 2142-2153 (2017) - [j23]Amichai Painsky, Saharon Rosset, Meir Feder:
Large Alphabet Source Coding Using Independent Component Analysis. IEEE Trans. Inf. Theory 63(10): 6514-6529 (2017) - [c38]Regev Schweiger, Eyal Fisher, Elior Rahmani, Liat Shenhav, Saharon Rosset, Eran Halperin:
Using Stochastic Approximation Techniques to Efficiently Construct Confidence Intervals for Heritability. RECOMB 2017: 241-256 - 2016
- [j22]Amichai Painsky, Saharon Rosset:
Isotonic Modeling with Non-Differentiable Loss Functions with Application to Lasso Regularization. IEEE Trans. Pattern Anal. Mach. Intell. 38(2): 308-321 (2016) - [j21]Amichai Painsky, Saharon Rosset, Meir Feder:
Generalized Independent Component Analysis Over Finite Alphabets. IEEE Trans. Inf. Theory 62(2): 1038-1053 (2016) - [c37]Amichai Painsky, Saharon Rosset, Meir Feder:
A Simple and Efficient Approach for Adaptive Entropy Coding over Large Alphabets. DCC 2016: 369-378 - [c36]Amichai Painsky, Saharon Rosset:
Compressing Random Forests. ICDM 2016: 1131-1136 - [c35]Amichai Painsky, Saharon Rosset, Meir Feder:
Binary independent component analysis: Theory, bounds and algorithms. MLSP 2016: 1-6 - [i3]Amichai Painsky, Saharon Rosset, Meir Feder:
Large Alphabet Source Coding using Independent Component Analysis. CoRR abs/1607.07003 (2016) - 2015
- [c34]Amichai Painsky, Saharon Rosset, Meir Feder:
Universal Compression of Memoryless Sources over Large Alphabets via Independent Component Analysis. DCC 2015: 213-222 - [i2]Amichai Painsky, Saharon Rosset, Meir Feder:
Generalized Independent Component Analysis Over Finite Alphabets. CoRR abs/1508.04934 (2015) - 2014
- [j20]Amichai Painsky, Saharon Rosset:
Optimal Set Cover Formulation for Exclusive Row Biclustering of Gene Expression. J. Comput. Sci. Technol. 29(3): 423-435 (2014) - [c33]Amichai Painsky, Saharon Rosset, Meir Feder:
Generalized binary independent component analysis. ISIT 2014: 1326-1330 - 2013
- [c32]Amichai Painsky, Saharon Rosset, Meir Feder:
Memoryless representation of Markov processes. ISIT 2013: 2294-2298 - 2012
- [j19]David Golan, Yaniv Erlich, Saharon Rosset:
Weighted pooling - practical and cost-effective techniques for pooled high-throughput sequencing. Bioinform. 28(12): 197-206 (2012) - [j18]Giles Hooker, Saharon Rosset:
Prediction-based regularization using data augmented regression. Stat. Comput. 22(1): 237-249 (2012) - [j17]Shachar Kaufman, Saharon Rosset, Claudia Perlich, Ori Stitelman:
Leakage in data mining: Formulation, detection, and avoidance. ACM Trans. Knowl. Discov. Data 6(4): 15:1-15:21 (2012) - [c31]Amichai Painsky, Saharon Rosset:
Exclusive Row Biclustering for Gene Expression Using a Combinatorial Auction Approach. ICDM 2012: 1056-1061 - [c30]Melissa Gymrek, David Golan, Saharon Rosset, Yaniv Erlich:
lobSTR: A Short Tandem Repeat Profiler for Personal Genomes. RECOMB 2012: 62-63 - 2011
- [j16]David Golan, Saharon Rosset:
Accurate estimation of heritability in genome wide studies using random effects models. Bioinform. 27(13): 317-323 (2011) - [j15]Ehud Aharoni, Hani Neuvirth, Saharon Rosset:
The Quality Preserving Database: A Computational Framework for Encouraging Collaboration, Enhancing Power and Controlling False Discovery. IEEE ACM Trans. Comput. Biol. Bioinform. 8(5): 1431-1437 (2011) - [c29]Slava Borodovsky, Saharon Rosset:
A/B Testing at SweetIM: The Importance of Proper Statistical Analysis. ICDM Workshops 2011: 733-740 - [c28]Shachar Kaufman, Saharon Rosset, Claudia Perlich:
Leakage in data mining: formulation, detection, and avoidance. KDD 2011: 556-563 - [i1]Ronny Luss, Saharon Rosset, Moni Shahar:
Isotonic Recursive Partitioning. CoRR abs/1102.5496 (2011) - 2010
- [j14]Osnat Ravid-Amir, Saharon Rosset:
Maximum likelihood estimation of locus-specific mutation rates in Y-chromosome short tandem repeats. Bioinform. 26(18) (2010) - [j13]Saharon Rosset, Claudia Perlich, Grzegorz Swirszcz, Prem Melville, Yan Liu:
Medical data mining: insights from winning two competitions. Data Min. Knowl. Discov. 20(3): 439-468 (2010) - [j12]Rick Lawrence, Claudia Perlich, Saharon Rosset, Ildar Khabibrakhmanov, Shilpa Mahatma, Sholom M. Weiss, Matthew Callahan, Matt Collins, Alexey Ershov, Shiva Kumar:
Operations Research Improves Sales Force Productivity at IBM. Interfaces 40(1): 33-46 (2010) - [c27]Ronny Luss, Saharon Rosset, Moni Shahar:
Decomposing Isotonic Regression for Efficiently Solving Large Problems. NIPS 2010: 1513-1521
2000 – 2009
- 2009
- [j11]Aurélie C. Lozano, Naoki Abe, Yan Liu, Saharon Rosset:
Grouped graphical Granger modeling for gene expression regulatory networks discovery. Bioinform. 25(12) (2009) - [j10]Saharon Rosset:
Bi-Level Path Following for Cross Validated Solution of Kernel Quantile Regression. J. Mach. Learn. Res. 10: 2473-2505 (2009) - [c26]Aurélie C. Lozano, Naoki Abe, Yan Liu, Saharon Rosset:
Grouped graphical Granger modeling methods for temporal causal modeling. KDD 2009: 577-586 - [r1]Claudia Perlich, Saharon Rosset, Bianca Zadrozny:
Modeling Quantiles. Encyclopedia of Data Warehousing and Mining 2009: 1324-1329 - 2008
- [j9]Claudia Perlich, Prem Melville, Yan Liu, Grzegorz Swirszcz, Richard D. Lawrence, Saharon Rosset:
Breast cancer identification: KDD CUP winner's report. SIGKDD Explor. 10(2): 39-42 (2008) - [c25]Saharon Rosset:
Bi-level path following for cross validated solution of kernel quantile regression. ICML 2008: 840-847 - [c24]Prem Melville, Saharon Rosset, Richard D. Lawrence:
Customer targeting models using actively-selected web content. KDD 2008: 946-953 - 2007
- [j8]Saharon Rosset:
Efficient inference on known phylogenetic trees using Poisson regression. Bioinform. 23(2): 142-147 (2007) - [j7]Richard D. Lawrence, Claudia Perlich, Saharon Rosset, Jorge Arroyo, Matthew Callahan, J. Matthew Collins, Alexey Ershov, Sheri Feinzig, Ildar Khabibrakhmanov, Shilpa Mahatma, Mark Niemaszyk, Sholom M. Weiss:
Analytics-driven solutions for customer targeting and sales-force allocation. IBM Syst. J. 46(4): 797-816 (2007) - [j6]Saharon Rosset, Claudia Perlich, Bianca Zadrozny:
Ranking-based evaluation of regression models. Knowl. Inf. Syst. 12(3): 331-353 (2007) - [j5]Saharon Rosset, Claudia Perlich, Yan Liu:
Making the most of your data: KDD Cup 2007 "How Many Ratings" winner's report. SIGKDD Explor. 9(2): 66-69 (2007) - [c23]Saharon Rosset, Grzegorz Swirszcz, Nathan Srebro, Ji Zhu:
l1 Regularization in Infinite Dimensional Feature Spaces. COLT 2007: 544-558 - [c22]Wojciech Gryc, Mary E. Helander, Richard D. Lawrence, Yan Liu, Claudia Perlich, Chandan K. Reddy, Saharon Rosset:
Looking for Great Ideas: Analyzing the Innovation Jam. WebKDD/SNA-KDD 2007: 21-39 - [c21]Claudia Perlich, Saharon Rosset, Richard D. Lawrence, Bianca Zadrozny:
High-quantile modeling for customer wallet estimation and other applications. KDD 2007: 977-985 - [c20]Claudia Perlich, Saharon Rosset:
Identifying Bundles of Product Options using Mutual Information Clustering. SDM 2007: 390-397 - 2006
- [c19]Srujana Merugu, Saharon Rosset, Claudia Perlich:
A new multi-view regression approach with an application to customer wallet estimation. KDD 2006: 656-661 - [c18]Ajay K. Royyuru, Gabriela Alexe, Daniel E. Platt, Ravi Vijaya Satya, Laxmi Parida, Saharon Rosset, Gyan Bhanot:
Inferring Common Origins from mtDNA. RECOMB 2006: 246-247 - [c17]Saharon Rosset, Richard D. Lawrence:
Data-Enhanced Predictive Modeling for Sales Targeting. SDM 2006: 569-573 - [p1]Saharon Rosset, Ji Zhu:
Sparse, Flexible and Efficient Modeling using L 1 Regularization. Feature Extraction 2006: 375-394 - 2005
- [c16]Saharon Rosset, Claudia Perlich, Bianca Zadrozny:
Ranking-Based Evaluation of Regression Models. ICDM 2005: 370-377 - [c15]Sofus A. Macskassy, Foster J. Provost, Saharon Rosset:
ROC confidence bands: an empirical evaluation. ICML 2005: 537-544 - [c14]Saharon Rosset:
Robust boosting and its relation to bagging. KDD 2005: 249-255 - 2004
- [j4]Saharon Rosset, Ji Zhu, Trevor Hastie:
Boosting as a Regularized Path to a Maximum Margin Classifier. J. Mach. Learn. Res. 5: 941-973 (2004) - [j3]Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu:
The Entire Regularization Path for the Support Vector Machine. J. Mach. Learn. Res. 5: 1391-1415 (2004) - [c13]Saharon Rosset:
Model selection via the AUC. ICML 2004 - [c12]Trevor Hastie, Saharon Rosset, Robert Tibshirani, Ji Zhu:
The Entire Regularization Path for the Support Vector Machine. NIPS 2004: 561-568 - [c11]Saharon Rosset:
Following Curved Regularized Optimization Solution Paths. NIPS 2004: 1153-1160 - [c10]Saharon Rosset, Ji Zhu, Hui Zou, Trevor Hastie:
A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning. NIPS 2004: 1161-1168 - 2003
- [j2]Saharon Rosset, Einat Neumann, Uri Eick, Nurit Vatnik:
Customer Lifetime Value Models for Decision Support. Data Min. Knowl. Discov. 7(3): 321-339 (2003) - [c9]Saharon Rosset, Ji Zhu, Trevor Hastie:
Boosting and support vector machines as optimal separators. DRR 2003: 1-7 - [c8]Saharon Rosset, Einat Neumann:
Integrating Customer Value Considerations into Predictive Modeling. ICDM 2003: 283-290 - [c7]Ji Zhu, Saharon Rosset, Trevor Hastie, Robert Tibshirani:
1-norm Support Vector Machines. NIPS 2003: 49-56 - [c6]Saharon Rosset, Ji Zhu, Trevor Hastie:
Margin Maximizing Loss Functions. NIPS 2003: 1237-1244 - 2002
- [c5]Saharon Rosset, Einat Neumann, Uri Eick, Nurit Vatnik, Yizhak Idan:
Customer lifetime value modeling and its use for customer retention planning. KDD 2002: 332-340 - [c4]Saharon Rosset, Eran Segal:
Boosting Density Estimation. NIPS 2002: 641-648 - 2001
- [c3]Saharon Rosset, Einat Neumann, Uri Eick, Nurit Vatnik, Yizhak Idan:
Evaluation of prediction models for marketing campaigns. KDD 2001: 456-461 - 2000
- [j1]Saharon Rosset, Aron Inger:
KDD-Cup 99: Knowledge Discovery In a Charitable Organization's Donor Database. SIGKDD Explor. 1(2): 85-90 (2000)
1990 – 1999
- 1999
- [c2]Saharon Rosset, Uzi Murad, Einat Neumann, Yizhak Idan, Gadi Pinkas:
Discovery of Fraud Rules for Telecommunications - Challenges and Solutions. KDD 1999: 409-413 - 1998
- [c1]Saharon Rosset:
Ranking - Methods for Flexible Evaluation and Efficient Comparison of Classification Performance. KDD 1998: 324-328
Coauthor Index
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