 | 2009 |
|---|
| 113 |       | Kevin Matulef,
Ryan O'Donnell,
Ronitt Rubinfeld,
Rocco A. Servedio:
Testing ±1-weight halfspace.
APPROX-RANDOM 2009: 646-657 |
| 112 | | Parikshit Gopalan,
Ryan O'Donnell,
Rocco A. Servedio,
Amir Shpilka,
Karl Wimmer:
Testing Fourier Dimensionality and Sparsity.
ICALP (1) 2009: 500-512 |
| 111 | | Adam R. Klivans,
Philip M. Long,
Rocco A. Servedio:
Learning Halfspaces with Malicious Noise.
ICALP (1) 2009: 609-621 |
| 110 | | Ilias Diakonikolas,
Rocco A. Servedio:
Improved Approximation of Linear Threshold Functions.
IEEE Conference on Computational Complexity 2009: 161-172 |
| 109 | | Kevin Matulef,
Ryan O'Donnell,
Ronitt Rubinfeld,
Rocco A. Servedio:
Testing halfspaces.
SODA 2009: 256-264 |
| 108 | | Ilias Diakonikolas,
Parikshit Gopalan,
Ragesh Jaiswal,
Rocco A. Servedio,
Emanuele Viola:
Bounded Independence Fools Halfspaces
CoRR abs/0902.3757: (2009) |
| 107 | | Ilias Diakonikolas,
Rocco A. Servedio,
Li-Yang Tan,
Andrew Wan:
A regularity lemma, and low-weight approximators, for low-degree polynomial threshold functions
CoRR abs/0909.4727: (2009) |
| 106 | | Ilias Diakonikolas,
Prasad Raghavendra,
Rocco A. Servedio,
Li-Yang Tan:
Average sensitivity and noise sensitivity of polynomial threshold functions
CoRR abs/0909.5011: (2009) |
| 105 | | Ilias Diakonikolas,
Rocco A. Servedio:
Improved Approximation of Linear Threshold Functions
CoRR abs/0910.3719: (2009) |
| 104 | | Ronitt Rubinfeld,
Rocco A. Servedio:
Testing monotone high-dimensional distributions.
Random Struct. Algorithms 34(1): 24-44 (2009) |
| 103 | | Marcus Hutter,
Rocco A. Servedio:
Preface.
Theor. Comput. Sci. 410(19): 1747-1748 (2009) |
| 2008 |
|---|
| 102 |  | Rocco A. Servedio,
Tong Zhang:
21st Annual Conference on Learning Theory - COLT 2008, Helsinki, Finland, July 9-12, 2008
Omnipress 2008 |
| 101 | | Jeffrey C. Jackson,
Homin K. Lee,
Rocco A. Servedio,
Andrew Wan:
Learning Random Monotone DNF.
APPROX-RANDOM 2008: 483-497 |
| 100 | | Adam R. Klivans,
Ryan O'Donnell,
Rocco A. Servedio:
Learning Geometric Concepts via Gaussian Surface Area.
FOCS 2008: 541-550 |
| 99 | | Dana Dachman-Soled,
Homin K. Lee,
Tal Malkin,
Rocco A. Servedio,
Andrew Wan,
Hoeteck Wee:
Optimal Cryptographic Hardness of Learning Monotone Functions.
ICALP (1) 2008: 36-47 |
| 98 | | Ilias Diakonikolas,
Homin K. Lee,
Kevin Matulef,
Rocco A. Servedio,
Andrew Wan:
Efficiently Testing Sparse GF(2) Polynomials.
ICALP (1) 2008: 502-514 |
| 97 | | Philip M. Long,
Rocco A. Servedio:
Random classification noise defeats all convex potential boosters.
ICML 2008: 608-615 |
| 96 | | Philip M. Long,
Rocco A. Servedio:
Adaptive Martingale Boosting.
NIPS 2008: 977-984 |
| 95 | | Ryan O'Donnell,
Rocco A. Servedio:
The chow parameters problem.
STOC 2008: 517-526 |
| 94 | | Rocco A. Servedio:
Learning Constant-Depth Circuits.
Encyclopedia of Algorithms 2008 |
| 93 | | Ilias Diakonikolas,
Homin K. Lee,
Kevin Matulef,
Rocco A. Servedio,
Andrew Wan:
Efficiently Testing Sparse GF(2) Polynomials
CoRR abs/0805.1765: (2008) |
| 92 | | Adam R. Klivans,
Rocco A. Servedio:
Learning intersections of halfspaces with a margin.
J. Comput. Syst. Sci. 74(1): 35-48 (2008) |
| 91 | | Ryan O'Donnell,
Rocco A. Servedio:
Extremal properties of polynomial threshold functions.
J. Comput. Syst. Sci. 74(3): 298-312 (2008) |
| 90 | | Jon Feldman,
Ryan O'Donnell,
Rocco A. Servedio:
Learning Mixtures of Product Distributions over Discrete Domains.
SIAM J. Comput. 37(5): 1536-1564 (2008) |
| 89 | | Adam Tauman Kalai,
Adam R. Klivans,
Yishay Mansour,
Rocco A. Servedio:
Agnostically Learning Halfspaces.
SIAM J. Comput. 37(6): 1777-1805 (2008) |
| 88 | | Alp Atici,
Rocco A. Servedio:
Learning unions of omega(1)-dimensional rectangles.
Theor. Comput. Sci. 405(3): 209-222 (2008) |
| 2007 |
|---|
| 87 | | Marcus Hutter,
Rocco A. Servedio,
Eiji Takimoto:
Algorithmic Learning Theory, 18th International Conference, ALT 2007, Sendai, Japan, October 1-4, 2007, Proceedings
Springer 2007 |
| 86 | | Marcus Hutter,
Rocco A. Servedio,
Eiji Takimoto:
Editors' Introduction.
ALT 2007: 1-8 |
| 85 | | Dana Glasner,
Rocco A. Servedio:
Distribution-Free Testing Lower Bounds for Basic Boolean Functions.
APPROX-RANDOM 2007: 494-508 |
| 84 | | Ilias Diakonikolas,
Homin K. Lee,
Kevin Matulef,
Krzysztof Onak,
Ronitt Rubinfeld,
Rocco A. Servedio,
Andrew Wan:
Testing for Concise Representations.
FOCS 2007: 549-558 |
| 83 | | Michael O. Rabin,
Rocco A. Servedio,
Christopher Thorpe:
Highly Efficient Secrecy-Preserving Proofs of Correctness of Computations and Applications.
LICS 2007: 63-76 |
| 82 | | Philip M. Long,
Rocco A. Servedio:
Boosting the Area under the ROC Curve.
NIPS 2007 |
| 81 | | Zafer Barutçuoglu,
Philip M. Long,
Rocco A. Servedio:
One-Pass Boosting.
NIPS 2007 |
| 80 | | Alp Atici,
Rocco A. Servedio:
Quantum Algorithms for Learning and Testing Juntas
CoRR abs/0707.3479: (2007) |
| 79 | | Rocco A. Servedio:
Every Linear Threshold Function has a Low-Weight Approximator.
Computational Complexity 16(2): 180-209 (2007) |
| 78 | | Ilias Diakonikolas,
Homin K. Lee,
Kevin Matulef,
Krzysztof Onak,
Ronitt Rubinfeld,
Rocco A. Servedio,
Andrew Wan:
Testing for Concise Representations.
Electronic Colloquium on Computational Complexity (ECCC) 14(077): (2007) |
| 77 | | Kevin Matulef,
Ryan O'Donnell,
Ronitt Rubinfeld,
Rocco A. Servedio:
Testing Halfspaces.
Electronic Colloquium on Computational Complexity (ECCC) 14(128): (2007) |
| 76 | | Jeffrey C. Jackson,
Homin K. Lee,
Rocco A. Servedio,
Andrew Wan:
Learning Random Monotone DNF.
Electronic Colloquium on Computational Complexity (ECCC) 14(129): (2007) |
| 75 | | Jon Feldman,
Tal Malkin,
Rocco A. Servedio,
Clifford Stein,
Martin J. Wainwright:
LP Decoding Corrects a Constant Fraction of Errors.
IEEE Transactions on Information Theory 53(1): 82-89 (2007) |
| 74 | | Philip M. Long,
Rocco A. Servedio,
Hans-Ulrich Simon:
Discriminative learning can succeed where generative learning fails.
Inf. Process. Lett. 103(4): 131-135 (2007) |
| 73 | | Ariel Elbaz,
Homin K. Lee,
Rocco A. Servedio,
Andrew Wan:
Separating Models of Learning from Correlated and Uncorrelated Data.
Journal of Machine Learning Research 8: 277-290 (2007) |
| 72 | | Homin K. Lee,
Rocco A. Servedio,
Andrew Wan:
DNF are teachable in the average case.
Machine Learning 69(2-3): 79-96 (2007) |
| 71 | | Ryan O'Donnell,
Rocco A. Servedio:
Learning Monotone Decision Trees in Polynomial Time.
SIAM J. Comput. 37(3): 827-844 (2007) |
| 70 | | Lisa Hellerstein,
Rocco A. Servedio:
On PAC learning algorithms for rich Boolean function classes.
Theor. Comput. Sci. 384(1): 66-76 (2007) |
| 2006 |
|---|
| 69 | | Alp Atici,
Rocco A. Servedio:
Learning Unions of omega(1)-Dimensional Rectangles.
ALT 2006: 32-47 |
| 68 | | Jon Feldman,
Rocco A. Servedio,
Ryan O'Donnell:
PAC Learning Axis-Aligned Mixtures of Gaussians with No Separation Assumption.
COLT 2006: 20-34 |
| 67 | | Homin K. Lee,
Rocco A. Servedio,
Andrew Wan:
DNF Are Teachable in the Average Case.
COLT 2006: 214-228 |
| 66 | | Philip M. Long,
Rocco A. Servedio:
Discriminative Learning Can Succeed Where Generative Learning Fails.
COLT 2006: 319-334 |
| 65 | | Rocco A. Servedio:
Every Linear Threshold Function has a Low-Weight Approximator.
IEEE Conference on Computational Complexity 2006: 18-32 |
| 64 | | Ryan O'Donnell,
Rocco A. Servedio:
Learning Monotone Decision Trees in Polynomial Time.
IEEE Conference on Computational Complexity 2006: 213-225 |
| 63 | | Philip M. Long,
Rocco A. Servedio:
Attribute-efficient learning of decision lists and linear threshold functions under unconcentrated distributions.
NIPS 2006: 921-928 |
| 62 | | Rocco A. Servedio:
On PAC Learning Algorithms for Rich Boolean Function Classes.
TAMC 2006: 442-451 |
| 61 | | Jon Feldman,
Ryan O'Donnell,
Rocco A. Servedio:
PAC Learning Mixtures of Axis-Aligned Gaussians with No Separation Assumption
CoRR abs/cs/0609093: (2006) |
| 60 | | Marta Arias,
Aaron Feigelson,
Roni Khardon,
Rocco A. Servedio:
Polynomial certificates for propositional classes.
Inf. Comput. 204(5): 816-834 (2006) |
| 59 | | Adam R. Klivans,
Rocco A. Servedio:
Toward Attribute Efficient Learning of Decision Lists and Parities.
Journal of Machine Learning Research 7: 587-602 (2006) |
| 58 | | Rocco A. Servedio:
On learning embedded midbit functions.
Theor. Comput. Sci. 350(1): 13-23 (2006) |
| 57 | | Jeffrey C. Jackson,
Rocco A. Servedio:
On Learning Random DNF Formulas Under the Uniform Distribution.
Theory of Computing 2(1): 147-172 (2006) |
| 2005 |
|---|
| 56 | | Jeffrey C. Jackson,
Rocco A. Servedio:
On Learning Random DNF Formulas Under the Uniform Distribution.
APPROX-RANDOM 2005: 342-353 |
| 55 | | Ariel Elbaz,
Homin K. Lee,
Rocco A. Servedio,
Andrew Wan:
Separating Models of Learning from Correlated and Uncorrelated Data.
COLT 2005: 637-651 |
| 54 | | Philip M. Long,
Rocco A. Servedio:
Martingale Boosting.
COLT 2005: 79-94 |
| 53 | | Adam Tauman Kalai,
Adam R. Klivans,
Yishay Mansour,
Rocco A. Servedio:
Agnostically Learning Halfspaces.
FOCS 2005: 11-20 |
| 52 | | Ryan O'Donnell,
Michael E. Saks,
Oded Schramm,
Rocco A. Servedio:
Every decision tree has an in.uential variable.
FOCS 2005: 31-39 |
| 51 | | Jon Feldman,
Ryan O'Donnell,
Rocco A. Servedio:
Learning mixtures of product distributions over discrete domains.
FOCS 2005: 501-510 |
| 50 | | Philip M. Long,
Vinay Varadan,
Sarah Gilman,
Mark Treshock,
Rocco A. Servedio:
Unsupervised evidence integration.
ICML 2005: 521-528 |
| 49 | | Ronitt Rubinfeld,
Rocco A. Servedio:
Testing monotone high-dimensional distributions.
STOC 2005: 147-156 |
| 48 | | Ryan O'Donnell,
Michael E. Saks,
Oded Schramm,
Rocco A. Servedio:
Every decision tree has an influential variable
CoRR abs/cs/0508071: (2005) |
| 47 | | Alp Atici,
Rocco A. Servedio:
Learning Unions of $\omega(1)$-Dimensional Rectangles
CoRR abs/cs/0510038: (2005) |
| 46 | | Rocco A. Servedio,
Andrew Wan:
Computing sparse permanents faster.
Inf. Process. Lett. 96(3): 89-92 (2005) |
| 45 | | Roni Khardon,
Dan Roth,
Rocco A. Servedio:
Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms.
J. Artif. Intell. Res. (JAIR) 24: 341-356 (2005) |
| 44 | | Nader H. Bshouty,
Elchanan Mossel,
Ryan O'Donnell,
Rocco A. Servedio:
Learning DNF from random walks.
J. Comput. Syst. Sci. 71(3): 250-265 (2005) |
| 43 | | Adam Tauman Kalai,
Rocco A. Servedio:
Boosting in the presence of noise.
J. Comput. Syst. Sci. 71(3): 266-290 (2005) |
| 42 | | Roni Khardon,
Rocco A. Servedio:
Maximum Margin Algorithms with Boolean Kernels.
Journal of Machine Learning Research 6: 1405-1429 (2005) |
| 41 | | Jeffrey C. Jackson,
Rocco A. Servedio:
Learning Random Log-Depth Decision Trees under Uniform Distribution.
SIAM J. Comput. 34(5): 1107-1128 (2005) |
| 2004 |
|---|
| 40 | | Adam R. Klivans,
Rocco A. Servedio:
Toward Attribute Efficient Learning of Decision Lists and Parities.
COLT 2004: 224-238 |
| 39 | | Adam R. Klivans,
Rocco A. Servedio:
Learning Intersections of Halfspaces with a Margin.
COLT 2004: 348-362 |
| 38 | | Adam R. Klivans,
Rocco A. Servedio:
Perceptron-Like Performance for Intersections of Halfspaces.
COLT 2004: 639-640 |
| 37 | | Alp Atici,
Rocco A. Servedio:
Improved Bounds on Quantum Learning Algorithms
CoRR quant-ph/0411140: (2004) |
| 36 | | Rocco A. Servedio:
Monotone Boolean formulas can approximate monotone linear threshold functions.
Discrete Applied Mathematics 142(1-3): 181-187 (2004) |
| 35 | | Rocco A. Servedio:
On learning monotone DNF under product distributions.
Inf. Comput. 193(1): 57-74 (2004) |
| 34 | | Adam R. Klivans,
Rocco A. Servedio:
Learning DNF in time 2Õ(n1/3).
J. Comput. Syst. Sci. 68(2): 303-318 (2004) |
| 33 | | Adam R. Klivans,
Ryan O'Donnell,
Rocco A. Servedio:
Learning intersections and thresholds of halfspaces.
J. Comput. Syst. Sci. 68(4): 808-840 (2004) |
| 32 | | Elchanan Mossel,
Ryan O'Donnell,
Rocco A. Servedio:
Learning functions of k relevant variables.
J. Comput. Syst. Sci. 69(3): 421-434 (2004) |
| 31 | | Rocco A. Servedio,
Steven J. Gortler:
Equivalences and Separations Between Quantum and Classical Learnability.
SIAM J. Comput. 33(5): 1067-1092 (2004) |
| 2003 |
|---|
| 30 | | Marta Arias,
Roni Khardon,
Rocco A. Servedio:
Polynomial Certificates for Propositional Classes.
COLT 2003: 537-551 |
| 29 | | Jeffrey C. Jackson,
Rocco A. Servedio:
Learning Random Log-Depth Decision Trees under the Uniform Distribution.
COLT 2003: 610-624 |
| 28 | | Roni Khardon,
Rocco A. Servedio:
Maximum Margin Algorithms with Boolean Kernels.
COLT 2003: 87-101 |
| 27 | | Nader H. Bshouty,
Elchanan Mossel,
Ryan O'Donnell,
Rocco A. Servedio:
Learning DNF from Random Walks.
FOCS 2003: 189- |
| 26 | | Ryan O'Donnell,
Rocco A. Servedio:
Extremal properties of polynomial threshold functions.
IEEE Conference on Computational Complexity 2003: 3-12 |
| 25 | | Adam Kalai,
Rocco A. Servedio:
Boosting in the presence of noise.
STOC 2003: 195-205 |
| 24 | | Elchanan Mossel,
Ryan O'Donnell,
Rocco A. Servedio:
Learning juntas.
STOC 2003: 206-212 |
| 23 | | Ryan O'Donnell,
Rocco A. Servedio:
New degree bounds for polynomial threshold functions.
STOC 2003: 325-334 |
| 22 | | Adam R. Klivans,
Rocco A. Servedio:
Toward Attribute Efficient Learning Algorithms
CoRR cs.LG/0311042: (2003) |
| 21 | | Rocco A. Servedio:
Smooth Boosting and Learning with Malicious Noise.
Journal of Machine Learning Research 4: 633-648 (2003) |
| 20 | | Adam R. Klivans,
Rocco A. Servedio:
Boosting and Hard-Core Set Construction.
Machine Learning 51(3): 217-238 (2003) |
| 2002 |
|---|
| 19 | | Rocco A. Servedio:
On Learning Embedded Midbit Functions.
ALT 2002: 69-82 |
| 18 | | Adam Klivans,
Ryan O'Donnell,
Rocco A. Servedio:
Learning Intersections and Thresholds of Halfspaces.
FOCS 2002: 177-186 |
| 17 | | Jeffrey C. Jackson,
Adam Klivans,
Rocco A. Servedio:
Learnability beyond AC0.
IEEE Conference on Computational Complexity 2002: 26 |
| 16 | | Jeffrey C. Jackson,
Adam Klivans,
Rocco A. Servedio:
Learnability beyond AC0.
STOC 2002: 776-784 |
| 15 | | Rocco A. Servedio:
PAC Analogues of Perceptron and Winnow Via Boosting the Margin.
Machine Learning 47(2-3): 133-151 (2002) |
| 14 | | Rocco A. Servedio:
Perceptron, Winnow, and PAC Learning.
SIAM J. Comput. 31(5): 1358-1369 (2002) |
| 2001 |
|---|
| 13 | | Rocco A. Servedio:
Smooth Boosting and Learning with Malicious Noise.
COLT/EuroCOLT 2001: 473-489 |
| 12 | | Rocco A. Servedio:
On Learning Monotone DNF under Product Distributions.
COLT/EuroCOLT 2001: 558-573 |
| 11 | | Rocco A. Servedio:
Separating Quantum and Classical Learning.
ICALP 2001: 1065-1080 |
| 10 | | Rocco A. Servedio,
Steven J. Gortler:
Quantum versus Classical Learnability.
IEEE Conference on Computational Complexity 2001: 138-148 |
| 9 | | Roni Khardon,
Dan Roth,
Rocco A. Servedio:
Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms.
NIPS 2001: 423-430 |
| 8 | | Adam Klivans,
Rocco A. Servedio:
Learning DNF in time 2Õ(n1/3).
STOC 2001: 258-265 |
| 7 | | Rocco A. Servedio:
On Learning Monotone DNF under Product Distributions
Electronic Colloquium on Computational Complexity (ECCC) 8(6): (2001) |
| 6 | | Rocco A. Servedio:
On the limits of efficient teachability.
Inf. Process. Lett. 79(6): 267-272 (2001) |
| 2000 |
|---|
| 5 | | Rocco A. Servedio:
PAC Analogues of Perceptron and Winnow via Boosting the Margin.
COLT 2000: 148-157 |
| 4 | | Rocco A. Servedio:
Computational Sample Complexity and Attribute-Efficient Learning.
J. Comput. Syst. Sci. 60(1): 161-178 (2000) |
| 1999 |
|---|
| 3 | | Rocco A. Servedio:
On PAC Learning Using Winnow, Perceptron, and a Perceptron-like Algorithm.
COLT 1999: 296-307 |
| 2 | | Adam Klivans,
Rocco A. Servedio:
Boosting and Hard-Core Sets.
FOCS 1999: 624-633 |
| 1 | | Rocco A. Servedio:
Computational Sample Complexity and Attribute-Efficient Learning.
STOC 1999: 701-710 |
