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223
Recognizing Realistic Actions from Videos “in the Wild”
"... In this paper, we present a systematic framework for recognizing realistic actions from videos “in the wild. ” Such unconstrained videos are abundant in personal collections as well as on the web. Recognizing action from such videos has not been addressed extensively, primarily due to the tremendous ..."
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Cited by 227 (13 self)
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visual vocabularies, a divisive information-theoretic algorithm is employed to group semantically related features. Finally, AdaBoost is chosen to integrate all the heterogeneous yet complementary features for recognition. We have tested the framework on the KTH dataset and our own dataset consisting
Improved Combinatorial Group Testing Algorithms for Real-World Problem Sizes
, 2007
"... We study practically efficient methods for performing combinatorial group testing. We present efficient nonadaptive and two-stage combinatorial group testing algorithms, which identify the at most d items out of a given set of n items that are defective, using fewer tests for all practical set siz ..."
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Cited by 18 (2 self)
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sizes. For example, our two-stage algorithm matches the information-theoretic lower bound for the number of tests in a combinatorial group testing regimen.
The capacity of adaptive group testing
- In 2013 IEEE International Symposium on Information Theory, Istanbul Turkey
, 2013
"... Abstract—We define capacity for group testing problems and deduce bounds for the capacity of a variety of noisy models, based on the capacity of equivalent noisy communication channels. For noiseless adaptive group testing we prove an information-theoretic lower bound which tightens a bound of Chan ..."
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Cited by 4 (3 self)
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Abstract—We define capacity for group testing problems and deduce bounds for the capacity of a variety of noisy models, based on the capacity of equivalent noisy communication channels. For noiseless adaptive group testing we prove an information-theoretic lower bound which tightens a bound of Chan
Group testing with prior statistics
- in IEEE International Symposium on Information Theory (ISIT). IEEE
"... Abstract—We consider a new group testing model wherein each item is a binary random variable defined by an a priori probabil-ity of being defective. We assume each that probability is small and that items are independent, but not necessarily identically distributed. The goal of group testing algorit ..."
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Cited by 1 (0 self)
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; in the second class we use non-adaptive measurements. Under loose assumptions on prior statistics, our algorithms, with high probability, only need a number of measurements that is close to the information-theoretic entropy lower bound, up to an explicit universal constant factor.
T~~s resea=c ~ was sup?or~ed by ~~e ~ussell Sage Foundation. An Information-Theoretic Scale for Cultural Rule Systems* ABSnAC'l'.
"... Important cultural mes.ages are expressed in nonverbal media.uch a. food, clothing, or the allocation of space Or time. For in.tance, how and what a group of persons eats on a particular occasion may convey public information about that occasion and about the group of person. eating together. Wherea ..."
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Important cultural mes.ages are expressed in nonverbal media.uch a. food, clothing, or the allocation of space Or time. For in.tance, how and what a group of persons eats on a particular occasion may convey public information about that occasion and about the group of person. eating together
Spectrum Sensing Algorithms for Cognitive Radio Based on Statistical Covariances
, 2008
"... Spectrum sensing, i.e., detecting the presence of primary users in a licensed spectrum, is a fundamental problem in cognitive radio. Since the statistical covariances of received signal and noise are usually different, they can be used to differentiate the case where the primary user’s signal is pre ..."
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Cited by 77 (2 self)
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presence is made by comparing the two test statistics. Theoretical analysis for the proposed algorithms is given. Detection probability and associated threshold are found based on statistical theory. The methods do not need any information of the signal, the channel and noise power a priori. Also
Anonymous Hierarchical Identity-Based Encryption (Without Random Oracles). In: Dwork
- CRYPTO 2006. LNCS,
, 2006
"... Abstract We present an identity-based cryptosystem that features fully anonymous ciphertexts and hierarchical key delegation. We give a proof of security in the standard model, based on the mild Decision Linear complexity assumption in bilinear groups. The system is efficient and practical, with sm ..."
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Cited by 119 (10 self)
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/pZ for the set of residues modp and Z × p = Z p \ {0} for its multiplicative group. Assumptions Since bilinear groups first appeared in cryptography half a decade ago 4 Informally, we say that an assumption is mild if it is tautological in the generic group model Decision BDH: The Bilinear DH assumption
Non-adaptive Group Testing: Explicit bounds and novel algorithms
"... PAPER AWARD1. We present computationally efficient and provably correct algorithms with near-optimal sample-complexity for noisy non-adaptive group testing. Group testing involves grouping arbitrary subsets of items into pools. Each pool is then tested to identify the defective items, which are usua ..."
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show that the sample-complexities of our algorithms are near-optimal with respect to known information-theoretic bounds. I.
Semiquantitative Group Testing
- IEEE Trans. Inf. Theory
"... Abstract—We consider a novel group testing procedure, termed semi-quantitative group testing, motivated by a class of problems arising in genome sequence processing. Semi-quantitative group testing (SQGT) is a non-binary pooling scheme that may be viewed as a combination of an adder model followed b ..."
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Cited by 4 (3 self)
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by a quantizer. For the new testing scheme we define the capacity and evaluate the capacity for some special choices of parameters using information theoretic methods. We also define a new class of disjunct codes suitable for SQGT, termed SQ-disjunct codes. We also provide both explicit
The capacity of non-identical adaptive group testing
"... Abstract—We consider the group testing problem, in the case where the items are defective independently but with non-constant probability. We introduce and analyse an algorithm to solve this problem by grouping items together appropriately. We give conditions under which the algorithm performs essen ..."
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essentially optimally in the sense of information-theoretic capacity. We use concentration of measure results to bound the probability that this algorithm requires many more tests than the expected number. This has applications to the allocation of spectrum to cognitive radios, in the case where a database
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223