Koby Crammer - RankMe

133 papers A* 30A 12B 4C 1Misc 5Journal 45Unranked 35

Year	Rank	Type	Title / Venue / Authors
2022	A*	`conf`	Weighted Training for Cross-Task Learning. ICLR Shuxiao Chen, Koby Crammer, Hangfeng He, Dan Roth, Weijie J. Su
2021	J	`jnl`	Weighted Training for Cross-Task Learning. CoRR Shuxiao Chen, Koby Crammer, Hangfeng He, Dan Roth, Weijie J. Su
2019	J	`jnl`	Variance Estimation For Online Regression via Spectrum Thresholding. CoRR Mark Kozdoba, Edward Moroshko, Shie Mannor, Koby Crammer
2018	B	`conf`	A Better Resource Allocation Algorithm with Semi-Bandit Feedback. ALT Yuval Dagan, Koby Crammer
2018	J	`jnl`	A Better Resource Allocation Algorithm with Semi-Bandit Feedback. CoRR Yuval Dagan, Koby Crammer
2018	J	`jnl`	Discriminative Keyword Spotting for limited-data applications. Speech Commun. Hadas Benisty, Itamar Katz, Koby Crammer, David Malah
2018	J	`jnl`	Efficient Loss-Based Decoding On Graphs For Extreme Classification. CoRR Itay Evron, Edward Moroshko, Koby Crammer
2018	A*	`conf`	Efficient Loss-Based Decoding on Graphs for Extreme Classification. NeurIPS Itay Evron, Edward Moroshko, Koby Crammer
2018	J	`jnl`	Multi Instance Learning For Unbalanced Data. CoRR Mark Kozdoba, Edward Moroshko, Lior Shani, Takuya Takagi, Takashi Katoh, Shie Mannor, Koby Crammer
2017	J	`jnl`	Learn on Source, Refine on Target: A Model Transfer Learning Framework with Random Forests. IEEE Trans. Pattern Anal. Mach. Intell. Noam Segev, Maayan Harel, Shie Mannor, Koby Crammer, Ran El-Yaniv
2017	—	`conf`	Online Regression with Controlled Label Noise Rate. ECML/PKDD (2) Edward Moroshko, Koby Crammer
2017	—	`conf`	Rotting Bandits. NIPS Nir Levine, Koby Crammer, Shie Mannor
2017	J	`jnl`	Rotting Bandits. CoRR Nir Levine, Koby Crammer, Shie Mannor
2016	J	`jnl`	Bandits meet Computer Architecture: Designing a Smartly-allocated Cache. CoRR Yonatan Glassner, Koby Crammer
2016	J	`jnl`	Grid-based approximation for voice conversion in low resource environments. EURASIP J. Audio Speech Music. Process. Hadas Benisty, David Malah, Koby Crammer
2016	A*	`conf`	That's Not My Question: Learning to Weight Unmatched Terms in CQA Vertical Search. SIGIR Boaz Petersil, Avihai Mejer, Idan Szpektor, Koby Crammer
2015	J	`jnl`	A generalized online mirror descent with applications to classification and regression. Mach. Learn. Francesco Orabona, Koby Crammer, Nicolò Cesa-Bianchi
2015	J	`jnl`	Belief Flows of Robust Online Learning. CoRR Pedro A. Ortega, Koby Crammer, Daniel D. Lee
2015	Misc	`conf`	Belief flows for robust online learning. ITA Pedro A. Ortega, Koby Crammer, Daniel D. Lee
2015	J	`jnl`	CONQUER: Confusion Queried Online Bandit Learning. CoRR Daniel Barsky, Koby Crammer
2015	A	`conf`	Convex Multi-Task Learning by Clustering. AISTATS Aviad Barzilai, Koby Crammer
2015	B	`conf`	In-memory hamming similarity computation in resistive arrays. ISIT Yuval Cassuto, Koby Crammer
2015	J	`jnl`	Learn on Source, Refine on Target: A Model Transfer Learning Framework with Random Forests. CoRR Noam Segev, Maayan Harel, Shie Mannor, Koby Crammer, Ran El-Yaniv
2015	—	`conf`	Linear Multi-Resource Allocation with Semi-Bandit Feedback. NIPS Tor Lattimore, Koby Crammer, Csaba Szepesvári
2015	A*	`conf`	Outlier-Robust Convex Segmentation. AAAI Itamar Katz, Koby Crammer
2015	J	`jnl`	Second-order non-stationary online learning for regression. J. Mach. Learn. Res. Edward Moroshko, Nina Vaits, Koby Crammer
2014	A*	`conf`	Concept Drift Detection Through Resampling. ICML Maayan Harel, Shie Mannor, Ran El-Yaniv, Koby Crammer
2014	A	`conf`	Doubly Aggressive Selective Sampling Algorithms for Classification. AISTATS Koby Crammer
2014	—	`conf`	Learning Multiple Tasks in Parallel with a Shared Annotator. NIPS Haim Cohen, Koby Crammer
2014	Misc	`conf`	Non-parallel voice conversion using joint optimization of alignment by temporal context and spectral distortion. ICASSP Hadas Benisty, David Malah, Koby Crammer
2014	A	`conf`	Optimal Resource Allocation with Semi-Bandit Feedback. UAI Tor Lattimore, Koby Crammer, Csaba Szepesvári
2014	J	`jnl`	Optimal Resource Allocation with Semi-Bandit Feedback. CoRR Tor Lattimore, Koby Crammer, Csaba Szepesvári
2014	J	`jnl`	Outlier-Robust Convex Segmentation. CoRR Itamar Katz, Koby Crammer
2014	A*	`conf`	Prediction with Limited Advice and Multiarmed Bandits with Paid Observations. ICML Yevgeny Seldin, Peter L. Bartlett, Koby Crammer, Yasin Abbasi-Yadkori
2014	A	`conf`	Robust Forward Algorithms via PAC-Bayes and Laplace Distributions. AISTATS Asaf Noy, Koby Crammer
2014	A	`conf`	Selective Sampling with Drift. AISTATS Edward Moroshko, Koby Crammer
2014	J	`jnl`	Selective Sampling with Drift. CoRR Edward Moroshko, Koby Crammer
2014	J	`jnl`	Weighted last-step min-max algorithm with improved sub-logarithmic regret. Theor. Comput. Sci. Edward Moroshko, Koby Crammer
2013	J	`jnl`	A Generalized Online Mirror Descent with Applications to Classification and Regression CoRR Francesco Orabona, Koby Crammer, Nicolò Cesa-Bianchi
2013	J	`jnl`	A Last-Step Regression Algorithm for Non-Stationary Online Learning CoRR Edward Moroshko, Koby Crammer
2013	A	`conf`	A Last-Step Regression Algorithm for Non-Stationary Online Learning. AISTATS Edward Moroshko, Koby Crammer
2013	J	`jnl`	Adaptive regularization of weight vectors. Mach. Learn. Koby Crammer, Alex Kulesza, Mark Dredze
2013	J	`jnl`	Advice-Efficient Prediction with Expert Advice CoRR Yevgeny Seldin, Peter L. Bartlett, Koby Crammer
2013	A*	`conf`	Hartigan's K-Means Versus Lloyd's K-Means - Is It Time for a Change? IJCAI Noam Slonim, Ehud Aharoni, Koby Crammer
2013	A*	`conf`	Multi Class Learning with Individual Sparsity. IJCAI Ben Zion Vatashsky, Koby Crammer
2013	J	`jnl`	Multiclass classification with bandit feedback using adaptive regularization. Mach. Learn. Koby Crammer, Claudio Gentile
2013	A*	`conf`	Open Problem: Adversarial Multiarmed Bandits with Limited Advice. COLT Yevgeny Seldin, Koby Crammer, Peter L. Bartlett
2013	J	`jnl`	Second-Order Non-Stationary Online Learning for Regression CoRR Nina Vaits, Edward Moroshko, Koby Crammer
2013	J	`jnl`	Weighted Last-Step Min-Max Algorithm with Improved Sub-Logarithmic Regret CoRR Edward Moroshko, Koby Crammer
2012	A	`conf`	A Simple Geometric Interpretation of SVM using Stochastic Adversaries. AISTATS Roi Livni, Koby Crammer, Amir Globerson
2012	A*	`conf`	Adaptive Regularization for Similarity Measures. ICML Koby Crammer, Gal Chechik
2012	J	`jnl`	Adaptive Regularization for Weight Matrices CoRR Koby Crammer, Gal Chechik
2012	—	`conf`	Are You Sure? Confidence in Prediction of Dependency Tree Edges. HLT-NAACL Avihai Mejer, Koby Crammer
2012	J	`jnl`	Automated gene-model curation using global discriminative learning. Bioinform. Axel Bernal, Koby Crammer, Fernando Pereira
2012	J	`jnl`	Breaking the curse of kernelization: budgeted stochastic gradient descent for large-scale SVM training. J. Mach. Learn. Res. Zhuang Wang, Koby Crammer, Slobodan Vucetic
2012	J	`jnl`	Confidence-Weighted Linear Classification for Text Categorization. J. Mach. Learn. Res. Koby Crammer, Mark Dredze, Fernando Pereira
2012	J	`jnl`	Discriminative Learning via Semidefinite Probabilistic Models. CoRR Koby Crammer, Amir Globerson
2012	—	`conf`	Graph-Based Transduction with Confidence. ECML/PKDD (2) Matan Orbach, Koby Crammer
2012	—	`conf`	Learning Multiple Tasks using Shared Hypotheses. NIPS Koby Crammer, Yishay Mansour
2012	—	`conf`	Metric Learning for Graph-Based Domain Adaptation. COLING (Posters) Paramveer S. Dhillon, Partha Pratim Talukdar, Koby Crammer
2012	—	`conf`	Modular Global Variance enhancement for voice conversion systems. EUSIPCO Hadas Benisty, David Malah, Koby Crammer
2012	C	`conf`	More Is Better: Large Scale Partially-supervised Sentiment Classication. ACML Yoav Haimovitch, Koby Crammer, Shie Mannor
2012	J	`jnl`	More Is Better: Large Scale Partially-supervised Sentiment Classification - Appendix CoRR Yoav Haimovitch, Koby Crammer, Shie Mannor
2012	Misc	`conf`	New ℌ ICASSP Koby Crammer, Alex Kulesza, Mark Dredze
2012	Misc	`conf`	Online discriminative learning of phoneme recognition via collections of generalized linear models. ICASSP Koby Crammer, Daniel D. Lee
2012	—	`conf`	Training Dependency Parser Using Light Feedback. HLT-NAACL Avihai Mejer, Koby Crammer
2012	—	`conf`	Volume Regularization for Binary Classification. NIPS Koby Crammer, Tal Wagner
2012	B	`conf`	Weighted Last-Step Min-Max Algorithm with Improved Sub-logarithmic Regret. ALT Edward Moroshko, Koby Crammer
2011	A*	`conf`	Active Online Classification via Information Maximization. IJCAI Noam Slonim, Elad Yom-Tov, Koby Crammer
2011	J	`jnl`	Confidence Estimation in Structured Prediction CoRR Avihai Mejer, Koby Crammer
2011	A*	`conf`	Multiclass Classification with Bandit Feedback using Adaptive Regularization. ICML Koby Crammer, Claudio Gentile
2011	B	`conf`	Re-adapting the Regularization of Weights for Non-stationary Regression. ALT Nina Vaits, Koby Crammer
2011	A*	`conf`	Trading representability for scalability: adaptive multi-hyperplane machine for nonlinear classification. KDD Zhuang Wang, Nemanja Djuric, Koby Crammer, Slobodan Vucetic
2010	J	`jnl`	A theory of learning from different domains. Mach. Learn. Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, Jennifer Wortman Vaughan
2010	A*	`conf`	Confidence in Structured-Prediction Using Confidence-Weighted Models. EMNLP Avihai Mejer, Koby Crammer
2010	Misc	`conf`	Efficient online learning with individual learning-rates for phoneme sequence recognition. ICASSP Koby Crammer
2010	A	`conf`	Exploiting Feature Covariance in High-Dimensional Online Learning. AISTATS Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer, Lawrence K. Saul, Fernando Pereira
2010	—	`conf`	Learning Better Data Representation Using Inference-Driven Metric Learning. ACL (2) Paramveer S. Dhillon, Partha Pratim Talukdar, Koby Crammer
2010	—	`conf`	Learning via Gaussian Herding. NIPS Koby Crammer, Daniel D. Lee
2010	A*	`conf`	Multi-Class Pegasos on a Budget. ICML Zhuang Wang, Koby Crammer, Slobodan Vucetic
2010	J	`jnl`	Multi-domain learning by confidence-weighted parameter combination. Mach. Learn. Mark Dredze, Alex Kulesza, Koby Crammer
2010	—	`conf`	New Adaptive Algorithms for Online Classification. NIPS Francesco Orabona, Koby Crammer
2010	A*	`conf`	Regret Minimization With Concept Drift. COLT Koby Crammer, Yishay Mansour, Eyal Even-Dar, Jennifer Wortman Vaughan
2009	—	`conf`	Adaptive Regularization of Weight Vectors. NIPS Koby Crammer, Alex Kulesza, Mark Dredze
2009	A	`conf`	Gaussian Margin Machines. AISTATS Koby Crammer, Mehryar Mohri, Fernando Pereira
2009	A	`conf`	How to loose confidence: probabilistic linear machines for multiclass classification. INTERSPEECH Hui Lin, Jeff A. Bilmes, Koby Crammer
2009	—	`conf`	Loss-Sensitive Discriminative Training of Machine Transliteration Models. HLT-NAACL (Student Research Workshop and Doctoral Consortium) Kedar Bellare, Koby Crammer, Dayne Freitag
2009	A*	`conf`	Multi-Class Confidence Weighted Algorithms. EMNLP Koby Crammer, Mark Dredze, Alex Kulesza
2009	—	`conf`	New Regularized Algorithms for Transductive Learning. ECML/PKDD (2) Partha Pratim Talukdar, Koby Crammer
2009	A*	`conf`	Resolving Identity Uncertainty with Learned Random Walks. ICDM Ted Sandler, Lyle H. Ungar, Koby Crammer
2008	A*	`conf`	A rate-distortion one-class model and its applications to clustering. ICML Koby Crammer, Partha Pratim Talukdar, Fernando C. N. Pereira
2008	—	`conf`	Active Learning with Confidence. ACL (2) Mark Dredze, Koby Crammer
2008	—	`conf`	Advanced Online Learning for Natural Language Processing. ACL (Tutorial Abstracts) Koby Crammer
2008	A*	`conf`	Confidence-weighted linear classification. ICML Mark Dredze, Koby Crammer, Fernando Pereira
2008	—	`conf`	Exact Convex Confidence-Weighted Learning. NIPS Koby Crammer, Mark Dredze, Fernando Pereira
2008	J	`jnl`	Learning from Multiple Sources. J. Mach. Learn. Res. Koby Crammer, Michael J. Kearns, Jennifer Wortman
2008	J	`jnl`	Learning to create data-integrating queries. Proc. VLDB Endow. Partha Pratim Talukdar, Marie Jacob, Muhammad Salman Mehmood, Koby Crammer, Zachary G. Ives, Fernando C. N. Pereira, Sudipto Guha
2008	A*	`conf`	One-Class Clustering in the Text Domain. EMNLP Ron Bekkerman, Koby Crammer
2008	A*	`conf`	Online Methods for Multi-Domain Learning and Adaptation. EMNLP Mark Dredze, Koby Crammer
2008	J	`jnl`	Reranking candidate gene models with cross-species comparison for improved gene prediction. BMC Bioinform. Qian Liu, Koby Crammer, Fernando C. N. Pereira, David S. Roos
2007	A	`conf`	A conservative aggressive subspace tracker. INTERSPEECH Koby Crammer
2007	—	`conf`	Automatic Code Assignment to Medical Text. BioNLP@ACL Koby Crammer, Mark Dredze, Kuzman Ganchev, Partha Pratim Talukdar, Steven Carroll
2007	J	`jnl`	Global Discriminative Learning for Higher-Accuracy Computational Gene Prediction. PLoS Comput. Biol. Axel Bernal, Koby Crammer, Artemis G. Hatzigeorgiou, Fernando Pereira
2007	—	`conf`	Learning Bounds for Domain Adaptation. NIPS John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, Jennifer Wortman
2006	—	`conf`	Analysis of Representations for Domain Adaptation. NIPS Shai Ben-David, John Blitzer, Koby Crammer, Fernando Pereira
2006	A	`conf`	Discriminative Learning via Semidefinite Probabilistic Models. UAI Koby Crammer, Amir Globerson
2006	—	`conf`	Learning from Multiple Sources. NIPS Koby Crammer, Michael J. Kearns, Jennifer Wortman
2006	J	`jnl`	Online Passive-Aggressive Algorithms. J. Mach. Learn. Res. Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz, Yoram Singer
2006	A*	`conf`	Online Tracking of Linear Subspaces. COLT Koby Crammer
2006	A*	`conf`	Robust Support Vector Machine Training via Convex Outlier Ablation. AAAI Linli Xu, Koby Crammer, Dale Schuurmans
2006	—	`conf`	Room Impulse Response Estimation using Sparse Online Prediction and Absolute Loss. ICASSP (3) Koby Crammer, Daniel D. Lee
2005	—	`conf`	Flexible Text Segmentation with Structured Multilabel Classification. HLT/EMNLP Ryan T. McDonald, Koby Crammer, Fernando Pereira
2005	—	`conf`	Learning from Data of Variable Quality. NIPS Koby Crammer, Michael J. Kearns, Jennifer Wortman
2005	A*	`conf`	Loss Bounds for Online Category Ranking. COLT Koby Crammer, Yoram Singer
2005	A*	`conf`	Online Large-Margin Training of Dependency Parsers. ACL Ryan T. McDonald, Koby Crammer, Fernando C. N. Pereira
2005	J	`jnl`	Online Ranking by Projecting. Neural Comput. Koby Crammer, Yoram Singer
2004	—	`conf`	A Temporal Kernel-Based Model for Tracking Hand Movements from Neural Activities. NIPS Lavi Shpigelman, Koby Crammer, Rony Paz, Eilon Vaadia, Yoram Singer
2004	A*	`conf`	A needle in a haystack: local one-class optimization. ICML Koby Crammer, Gal Chechik
2004	—	`—`	Online learning of complex categorical problems (למידה מקוונת של בעיות דירוג מורכבות.). Koby Crammer
2003	J	`jnl`	A Family of Additive Online Algorithms for Category Ranking. J. Mach. Learn. Res. Koby Crammer, Yoram Singer
2003	A*	`conf`	Learning Algorithm for Enclosing Points in Bregmanian Spheres. COLT Koby Crammer, Yoram Singer
2003	—	`conf`	Online Classification on a Budget. NIPS Koby Crammer, Jaz S. Kandola, Yoram Singer
2003	—	`conf`	Online Passive-Aggressive Algorithms. NIPS Shai Shalev-Shwartz, Koby Crammer, Ofer Dekel, Yoram Singer
2003	J	`jnl`	Ultraconservative Online Algorithms for Multiclass Problems. J. Mach. Learn. Res. Koby Crammer, Yoram Singer
2002	A*	`conf`	A new family of online algorithms for category ranking. SIGIR Koby Crammer, Yoram Singer
2002	—	`conf`	Kernel Design Using Boosting. NIPS Koby Crammer, Joseph Keshet, Yoram Singer
2002	—	`conf`	Margin Analysis of the LVQ Algorithm. NIPS Koby Crammer, Ran Gilad-Bachrach, Amir Navot, Naftali Tishby
2002	J	`jnl`	On the Learnability and Design of Output Codes for Multiclass Problems. Mach. Learn. Koby Crammer, Yoram Singer
2001	J	`jnl`	On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines. J. Mach. Learn. Res. Koby Crammer, Yoram Singer
2001	—	`conf`	Pranking with Ranking. NIPS Koby Crammer, Yoram Singer
2001	—	`conf`	Ultraconservative Online Algorithms for Multiclass Problems. COLT/EuroCOLT Koby Crammer, Yoram Singer
2000	—	`conf`	Improved Output Coding for Classification Using Continuous Relaxation. NIPS Koby Crammer, Yoram Singer
2000	A*	`conf`	On the Learnability and Design of Output Codes for Multiclass Problems. COLT Koby Crammer, Yoram Singer