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Yoav Freund
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Publications
- 2023
- [i30]Sanjoy Dasgupta, Yoav Freund:
Active learning using region-based sampling. CoRR abs/2303.02721 (2023) - [i29]Robi Bhattacharjee, Alexander Cloninger, Yoav Freund, Andreas Oslandsbotn:
Effective resistance in metric spaces. CoRR abs/2306.15649 (2023) - 2022
- [j22]Andreas Oslandsbotn, Zeljko Kereta, Valeriya Naumova, Yoav Freund, Alexander Cloninger:
StreaMRAK a streaming multi-resolution adaptive kernel algorithm. Appl. Math. Comput. 426: 127112 (2022) - [j19]Yoav Freund, Yi-An Ma, Tong Zhang:
When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint. J. Mach. Learn. Res. 23: 214:1-214:32 (2022) - [i28]Robi Bhattacharjee, Alex Cloninger, Yoav Freund:
Structure from Voltage. CoRR abs/2203.00063 (2022) - 2021
- [i25]Andreas Oslandsbotn, Zeljko Kereta, Valeriya Naumova, Yoav Freund, Alexander Cloninger:
SreaMRAK a Streaming Multi-Resolution Adaptive Kernel Algorithm. CoRR abs/2108.10411 (2021) - [i24]Yoav Freund, Yi-An Ma, Tong Zhang:
When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint. CoRR abs/2110.01827 (2021) - 2019
- [c58]Akshay Balsubramani, Sanjoy Dasgupta, Yoav Freund, Shay Moran:
An adaptive nearest neighbor rule for classification. NeurIPS 2019: 7577-7586 - [i21]Akshay Balsubramani, Sanjoy Dasgupta, Yoav Freund, Shay Moran:
An adaptive nearest neighbor rule for classification. CoRR abs/1905.12717 (2019) - 2016
- [c53]Akshay Balsubramani, Yoav Freund:
Optimal Binary Classifier Aggregation for General Losses. NIPS 2016: 5033-5040 - [i17]Raef Bassily, Yoav Freund:
Typicality-Based Stability and Privacy. CoRR abs/1604.03336 (2016) - [i16]Akshay Balsubramani, Yoav Freund:
Muffled Semi-Supervised Learning. CoRR abs/1605.08833 (2016) - 2015
- [c52]Yannis Katsis, Yoav Freund, Yannis Papakonstantinou:
Combining Databases and Signal Processing in Plato. CIDR 2015 - [c51]Akshay Balsubramani, Yoav Freund:
Optimally Combining Classifiers Using Unlabeled Data. COLT 2015: 211-225 - [c50]Akshay Balsubramani, Yoav Freund:
Scalable Semi-Supervised Aggregation of Classifiers. NIPS 2015: 1351-1359 - [i15]Akshay Balsubramani, Sanjoy Dasgupta, Yoav Freund:
The Fast Convergence of Incremental PCA. CoRR abs/1501.03796 (2015) - [i14]Akshay Balsubramani, Yoav Freund:
PAC-Bayes with Minimax for Confidence-Rated Transduction. CoRR abs/1501.03838 (2015) - [i13]Akshay Balsubramani, Yoav Freund:
Optimally Combining Classifiers Using Unlabeled Data. CoRR abs/1503.01811 (2015) - [i12]Akshay Balsubramani, Yoav Freund:
Scalable Semi-Supervised Classifier Aggregation. CoRR abs/1506.05790 (2015) - [i11]Akshay Balsubramani, Yoav Freund:
Minimax Binary Classifier Aggregation with General Losses. CoRR abs/1510.00452 (2015) - 2013
- [c46]Akshay Balsubramani, Sanjoy Dasgupta, Yoav Freund:
The Fast Convergence of Incremental PCA. NIPS 2013: 3174-3182 - 2012
- [i8]Kamalika Chaudhuri, Yoav Freund, Daniel J. Hsu:
An Online Learning-based Framework for Tracking. CoRR abs/1203.3471 (2012) - 2010
- [c41]Kamalika Chaudhuri, Yoav Freund, Daniel J. Hsu:
An Online Learning-based Framework for Tracking. UAI 2010: 101-108 - [i6]Mayank Kabra, Annie L. Conery, Eyleen J. O'Rourke, Xin Xie, Vebjorn Ljosa, Thouis R. Jones, Frederick M. Ausubel, Gary Ruvkun, Anne E. Carpenter, Yoav Freund:
Towards automated high-throughput screening of C. elegans on agar. CoRR abs/1003.4287 (2010) - 2009
- [j16]Ron Alterovitz, Aaron Arvey, Sriram Sankararaman, Carolina Dallett, Yoav Freund, Kimmen Sjölander:
ResBoost: characterizing and predicting catalytic residues in enzymes. BMC Bioinform. 10 (2009) - [j15]Sanjoy Dasgupta, Yoav Freund:
Random projection trees for vector quantization. IEEE Trans. Inf. Theory 55(7): 3229-3242 (2009) - [c38]Kamalika Chaudhuri, Yoav Freund, Daniel J. Hsu:
A Parameter-free Hedging Algorithm. NIPS 2009: 297-305 - [i5]Kamalika Chaudhuri, Yoav Freund, Daniel J. Hsu:
A parameter-free hedging algorithm. CoRR abs/0903.2851 (2009) - [i4]Kamalika Chaudhuri, Yoav Freund, Daniel J. Hsu:
Tracking using explanation-based modeling. CoRR abs/0903.2862 (2009) - 2008
- [c37]Sanjoy Dasgupta, Yoav Freund:
Random projection trees for vector quantization. Allerton 2008: 192-197 - [c34]Sanjoy Dasgupta, Yoav Freund:
Random projection trees and low dimensional manifolds. STOC 2008: 537-546 - [e2]Yoav Freund, László Györfi, György Turán, Thomas Zeugmann:
Algorithmic Learning Theory, 19th International Conference, ALT 2008, Budapest, Hungary, October 13-16, 2008. Proceedings. Lecture Notes in Computer Science 5254, Springer 2008, ISBN 978-3-540-87986-2 [contents] - [i2]Yoav Freund, Daniel J. Hsu:
A new Hedging algorithm and its application to inferring latent random variables. CoRR abs/0806.4802 (2008) - 2007
- [c32]Yoav Freund, Sanjoy Dasgupta, Mayank Kabra, Nakul Verma:
Learning the structure of manifolds using random projections. NIPS 2007: 473-480 - 2006
- [j14]Peter V. Kharchenko, Lifeng Chen, Yoav Freund, Dennis Vitkup, George M. Church:
Identifying metabolic enzymes with multiple types of association evidence. BMC Bioinform. 7: 177 (2006) - [j13]Anshul Kundaje, Manuel Middendorf, Mihir Shah, Chris Wiggins, Yoav Freund, Christina S. Leslie:
A classification-based framework for predicting and analyzing gene regulatory response. BMC Bioinform. 7(S-1) (2006) - 2005
- [c31]Manuel Middendorf, Anshul Kundaje, Mihir Shah, Yoav Freund, Chris Wiggins, Christina S. Leslie:
Motif Discovery Through Predictive Modeling of Gene Regulation. RECOMB 2005: 538-552 - 2004
- [c30]Rui Kuang, Eugene Ie, Ke Wang, Kai Wang, Mahira Siddiqi, Yoav Freund, Christina S. Leslie:
Profile-Based String Kernels for Remote Homology Detection and Motif Extraction. CSB 2004: 152-160 - [c29]Manuel Middendorf, Anshul Kundaje, Chris Wiggins, Yoav Freund, Christina S. Leslie:
Predicting genetic regulatory response using classification. ISMB/ECCB (Supplement of Bioinformatics) 2004: 232-240 - [c28]Manuel Middendorf, Anshul Kundaje, Chris Wiggins, Yoav Freund, Christina S. Leslie:
Predicting Genetic Regulatory Response Using Classification: Yeast Stress Response. Regulatory Genomics 2004: 1-13 - 2003
- [j11]Yoav Freund, Raj D. Iyer, Robert E. Schapire, Yoram Singer:
An Efficient Boosting Algorithm for Combining Preferences. J. Mach. Learn. Res. 4: 933-969 (2003) - 2002
- [j10]Yoav Freund, Manfred Opper:
Drifting Games and Brownian Motion. J. Comput. Syst. Sci. 64(1): 113-132 (2002) - [j9]Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, Robert E. Schapire:
The Nonstochastic Multiarmed Bandit Problem. SIAM J. Comput. 32(1): 48-77 (2002) - 2001
- [c25]Yoav Freund, Yishay Mansour, Robert E. Schapire:
Why averaging classifiers can protect against overfitting. AISTATS 2001 - 2000
- [c24]Yoav Freund, Manfred Opper:
Continuous Drifting Games. COLT 2000: 126-132 - [i1]Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, Robert E. Schapire:
Gambling in a rigged casino: The adversarial multi-armed bandit problem. Electron. Colloquium Comput. Complex. TR00 (2000) - 1999
- [j7]Yoav Freund, Robert E. Schapire:
Large Margin Classification Using the Perceptron Algorithm. Mach. Learn. 37(3): 277-296 (1999) - [c23]Yoav Freund, Yishay Mansour:
Estimating a Mixture of Two Product Distributions. COLT 1999: 53-62 - [c21]Yoav Freund, Llew Mason:
The Alternating Decision Tree Learning Algorithm. ICML 1999: 124-133 - 1998
- [c20]Yoav Freund, Robert E. Schapire:
Large Margin Classification Using the Perceptron Algorithm. COLT 1998: 209-217 - [c18]Yoav Freund, Raj D. Iyer, Robert E. Schapire, Yoram Singer:
An Efficient Boosting Algorithm for Combining Preferences. ICML 1998: 170-178 - 1997
- [j6]Yoav Freund, Michael J. Kearns, Dana Ron, Ronitt Rubinfeld, Robert E. Schapire, Linda Sellie:
Efficient Learning of Typical Finite Automata from Random Walks. Inf. Comput. 138(1): 23-48 (1997) - [j5]Nicolò Cesa-Bianchi, Yoav Freund, David Haussler, David P. Helmbold, Robert E. Schapire, Manfred K. Warmuth:
How to use expert advice. J. ACM 44(3): 427-485 (1997) - [j4]Yoav Freund, Robert E. Schapire:
A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting. J. Comput. Syst. Sci. 55(1): 119-139 (1997) - [j3]Yoav Freund, H. Sebastian Seung, Eli Shamir, Naftali Tishby:
Selective Sampling Using the Query by Committee Algorithm. Mach. Learn. 28(2-3): 133-168 (1997) - [c17]Yoav Freund, Yishay Mansour:
Learning Under Persistent Drift. EuroCOLT 1997: 109-118 - [c16]Robert E. Schapire, Yoav Freund, Peter Barlett, Wee Sun Lee:
Boosting the margin: A new explanation for the effectiveness of voting methods. ICML 1997: 322-330 - [c15]Yoav Freund, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth:
Using and Combining Predictors That Specialize. STOC 1997: 334-343 - [e1]Yoav Freund, Robert E. Schapire:
Proceedings of the Tenth Annual Conference on Computational Learning Theory, COLT 1997, Nashville, Tennessee, USA, July 6-9, 1997. ACM 1997, ISBN 0-89791-891-6 [contents] - 1996
- [j2]Nicolò Cesa-Bianchi, Yoav Freund, David P. Helmbold, Manfred K. Warmuth:
On-line Prediction and Conversion Strategies. Mach. Learn. 25(1): 71-110 (1996) - [c13]Yoav Freund, Robert E. Schapire:
Game Theory, On-Line Prediction and Boosting. COLT 1996: 325-332 - [c12]Yoav Freund, Robert E. Schapire:
Experiments with a New Boosting Algorithm. ICML 1996: 148-156 - 1995
- [c11]Yoav Freund, Dana Ron:
Learning to Model Sequences Generated by Switching Distributions. COLT 1995: 41-50 - [c10]Yoav Freund, Robert E. Schapire:
A decision-theoretic generalization of on-line learning and an application to boosting. EuroCOLT 1995: 23-37 - [c9]Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, Robert E. Schapire:
Gambling in a Rigged Casino: The Adversarial Multi-Arm Bandit Problem. FOCS 1995: 322-331 - [c8]Yoav Freund, Michael J. Kearns, Yishay Mansour, Dana Ron, Ronitt Rubinfeld, Robert E. Schapire:
Efficient Algorithms for Learning to Play Repeated Games Against Computationally Bounded Adversaries. FOCS 1995: 332-341 - 1993
- [c7]Nicolò Cesa-Bianchi, Yoav Freund, David P. Helmbold, Manfred K. Warmuth:
On-line prediction and conversion strategies. EuroCOLT 1993: 205-216 - [c6]Yoav Freund, Michael J. Kearns, Dana Ron, Ronitt Rubinfeld, Robert E. Schapire, Linda Sellie:
Efficient learning of typical finite automata from random walks. STOC 1993: 315-324 - [c5]Nicolò Cesa-Bianchi, Yoav Freund, David P. Helmbold, David Haussler, Robert E. Schapire, Manfred K. Warmuth:
How to use expert advice. STOC 1993: 382-391 - 1992
- [c3]Yoav Freund, H. Sebastian Seung, Eli Shamir, Naftali Tishby:
Information, Prediction, and Query by Committee. NIPS 1992: 483-490 - 1991
- [c2]Yoav Freund, David Haussler:
Unsupervised Learning of Distributions of Binary Vectors Using 2-Layer Networks. NIPS 1991: 912-919
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