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Statistical queries and faulty PAC oracles
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Weakly learning DNF and characterizing statistical query learning using Fourier analysis
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General bounds on statistical query learning and PAC learning with noise via hypothesis boosting
Information and Computation
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Efficient noise-tolerant learning from statistical queries
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On polynomial approximation to the shortest lattice vector length
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A sieve algorithm for the shortest lattice vector problem
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
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A Generalized Birthday Problem
CRYPTO '02 Proceedings of the 22nd Annual International Cryptology Conference on Advances in Cryptology
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Security Parallels between People and Pervasive Devices
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On lattices, learning with errors, random linear codes, and cryptography
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Active EM to reduce noise in activity recognition
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Protocols for RFID tag/reader authentication
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Unconditional lower bounds for learning intersections of halfspaces
Machine Learning
Lossy trapdoor functions and their applications
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Evolvability from learning algorithms
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On agnostic boosting and parity learning
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
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Semantic security for the McEliece cryptosystem without random oracles
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Attacks on CKK Family of RFID Authentication Protocols
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On lattices, learning with errors, random linear codes, and cryptography
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Extracting Computational Entropy and Learning Noisy Linear Functions
COCOON '09 Proceedings of the 15th Annual International Conference on Computing and Combinatorics
Design and implementation of S-MARKS: A secure middleware for pervasive computing applications
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Two Attacks against the Ff RFID Protocol
INDOCRYPT '09 Proceedings of the 10th International Conference on Cryptology in India: Progress in Cryptology
Efficient cryptographic protocols based on the hardness of learning parity with noise
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Local list-decoding and testing of random linear codes from high error
Proceedings of the forty-second ACM symposium on Theory of computing
Differentially private data release through multidimensional partitioning
SDM'10 Proceedings of the 7th VLDB conference on Secure data management
SIAM Journal on Computing
Hardness of Reconstructing Multivariate Polynomials over Finite Fields
SIAM Journal on Computing
Better key sizes (and attacks) for LWE-based encryption
CT-RSA'11 Proceedings of the 11th international conference on Topics in cryptology: CT-RSA 2011
Attack on the GridCode one-time password
Proceedings of the 6th ACM Symposium on Information, Computer and Communications Security
Tree-based HB protocols for privacy-preserving authentication of RFID tags
Journal of Computer Security - 2010 Workshop on RFID Security (RFIDSec'10 Asia)
Some recent results on local testing of sparse linear codes
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Property testing
Efficient authentication from hard learning problems
EUROCRYPT'11 Proceedings of the 30th Annual international conference on Theory and applications of cryptographic techniques: advances in cryptology
Practical attacks on HB and HB+ protocols
WISTP'11 Proceedings of the 5th IFIP WG 11.2 international conference on Information security theory and practice: security and privacy of mobile devices in wireless communication
New algorithms for learning in presence of errors
ICALP'11 Proceedings of the 38th international colloquim conference on Automata, languages and programming - Volume Part I
Generalized learning problems and applications to non-commutative cryptography
ProvSec'11 Proceedings of the 5th international conference on Provable security
On noise-tolerant learning of sparse parities and related problems
ALT'11 Proceedings of the 22nd international conference on Algorithmic learning theory
Cryptography in constant parallel time
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SIAM Journal on Computing
SIAM Journal on Computing
INDOCRYPT'06 Proceedings of the 7th international conference on Cryptology in India
Spectral norm in learning theory: some selected topics
ALT'06 Proceedings of the 17th international conference on Algorithmic Learning Theory
Improved lower bounds for learning intersections of halfspaces
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APPROX'05/RANDOM'05 Proceedings of the 8th international workshop on Approximation, Randomization and Combinatorial Optimization Problems, and Proceedings of the 9th international conference on Randamization and Computation: algorithms and techniques
Security problems of systems of extremely weak devices
Annales UMCS, Informatica - Security Systems
Solving medium-density subset sum problems in expected polynomial time
STACS'05 Proceedings of the 22nd annual conference on Theoretical Aspects of Computer Science
Authenticating pervasive devices with human protocols
CRYPTO'05 Proceedings of the 25th annual international conference on Advances in Cryptology
SCN'06 Proceedings of the 5th international conference on Security and Cryptography for Networks
Parallel and concurrent security of the HB and HB+ protocols
EUROCRYPT'06 Proceedings of the 24th annual international conference on The Theory and Applications of Cryptographic Techniques
The leakage-resilience limit of a computational problem is equal to its unpredictability entropy
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Cryptography from learning parity with noise
SOFSEM'12 Proceedings of the 38th international conference on Current Trends in Theory and Practice of Computer Science
On learning finite-state quantum sources
Quantum Information & Computation
A complete characterization of statistical query learning with applications to evolvability
Journal of Computer and System Sciences
Pseudorandom functions and lattices
EUROCRYPT'12 Proceedings of the 31st Annual international conference on Theory and Applications of Cryptographic Techniques
Lossy Trapdoor Functions and Their Applications
SIAM Journal on Computing
A survey on fast correlation attacks
Cryptography and Communications
A hybrid generative/discriminative method for semi-supervised classification
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Lapin: an efficient authentication protocol based on Ring-LPN
FSE'12 Proceedings of the 19th international conference on Fast Software Encryption
Commitments and efficient zero-knowledge proofs from learning parity with noise
ASIACRYPT'12 Proceedings of the 18th international conference on The Theory and Application of Cryptology and Information Security
Hidden bits approach for authentication in RFID systems
RFIDSec'12 Proceedings of the 8th international conference on Radio Frequency Identification: security and privacy issues
RFIDSec'12 Proceedings of the 8th international conference on Radio Frequency Identification: security and privacy issues
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Solving the learning parity with noise's open question
Information Processing Letters
Linear-time encodable codes meeting the gilbert-varshamov bound and their cryptographic applications
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We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise, a problem closely related to several cryptographic and coding problems. Our algorithm runs in polynomial time for the case of parity functions that depend on only the first O(log n log log n) bits of input, which provides the first known instance of an efficient noise-tolerant algorithm for a concept class that is not learnable in the Statistical Query model of Kearns [1998]. Thus, we demonstrate that the set of problems learnable in the statistical query model is a strict subset of those problems learnable in the presence of noise in the PAC model.In coding-theory terms, what we give is a poly(n)-time algorithm for decoding linear k × n codes in the presence of random noise for the case of k = c log n log log n for some c 0. (The case of k = O(log n) is trivial since one can just individually check each of the 2k possible messages and choose the one that yields the closest codeword.)A natural extension of the statistical query model is to allow queries about statistical properties that involve t-tuples of examples, as opposed to just single examples. The second result of this article is to show that any class of functions learnable (strongly or weakly) with t-wise queries for t = O(log n) is also weakly learnable with standard unary queries. Hence, this natural extension to the statistical query model does not increase the set of weakly learnable functions.