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Is MinWise Hashing Optimal for Summarizing Set Intersection?
"... Minwise hashing is an important method for estimating the size of the intersection of sets, based on a succinct summary (a “minhash”) independently computed for each set. One application is estimation of the number of data points that satisfy the conjunction of m ≥ 2 simple predicates, where a min ..."
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Cited by 2 (1 self)
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hashing is space optimal for m = 2 predicates in the sense that the estimator’s variance is within a constant factor of the smallest possible among all summaries with the given space usage. But for conjunctions of m> 2 predicates we show that the performance of bbit minwise hashing (and more
bbit minwise hashing in practice
 In Internetware
, 2013
"... Minwise hashing is a standard technique in the context of search for approximating set similarities. The recent work [26, 32] demonstrated a potential use of bbit minwise hashing [23, 24] for efficient search and learning on massive, highdimensional, binary data (which are typical for many appli ..."
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Cited by 3 (1 self)
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Minwise hashing is a standard technique in the context of search for approximating set similarities. The recent work [26, 32] demonstrated a potential use of bbit minwise hashing [23, 24] for efficient search and learning on massive, highdimensional, binary data (which are typical for many
Nearoptimal hashing algorithms for approximate nearest neighbor in high dimensions
, 2008
"... In this article, we give an overview of efficient algorithms for the approximate and exact nearest neighbor problem. The goal is to preprocess a dataset of objects (e.g., images) so that later, given a new query object, one can quickly return the dataset object that is most similar to the query. The ..."
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Cited by 457 (7 self)
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In this article, we give an overview of efficient algorithms for the approximate and exact nearest neighbor problem. The goal is to preprocess a dataset of objects (e.g., images) so that later, given a new query object, one can quickly return the dataset object that is most similar to the query. The problem is of significant interest in a wide variety of areas.
Greedy Randomized Adaptive Search Procedures
, 2002
"... GRASP is a multistart metaheuristic for combinatorial problems, in which each iteration consists basically of two phases: construction and local search. The construction phase builds a feasible solution, whose neighborhood is investigated until a local minimum is found during the local search phas ..."
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Cited by 647 (82 self)
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solution construction mechanisms and techniques to speed up the search are also described: Reactive GRASP, cost perturbations, bias functions, memory and learning, local search on partially constructed solutions, hashing, and filtering. We also discuss in detail implementation strategies of memory
Similarity estimation techniques from rounding algorithms
 In Proc. of 34th STOC
, 2002
"... A locality sensitive hashing scheme is a distribution on a family F of hash functions operating on a collection of objects, such that for two objects x, y, Prh∈F[h(x) = h(y)] = sim(x,y), where sim(x,y) ∈ [0, 1] is some similarity function defined on the collection of objects. Such a scheme leads ..."
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Cited by 449 (6 self)
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to a compact representation of objects so that similarity of objects can be estimated from their compact sketches, and also leads to efficient algorithms for approximate nearest neighbor search and clustering. Minwise independent permutations provide an elegant construction of such a locality
A Characterization of ${\rm Min}$Wise Independent Permutations Families
"... Abstract. A ${\rm Min}$Wise Independent Permutation Family is an efficient tool to estimate similarity of documents. We present a characterization of Exact MWIPFs by size uniformity, which represents certain symmetry of the string representation of a family. Also, we present a general construction ..."
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Abstract. A ${\rm Min}$Wise Independent Permutation Family is an efficient tool to estimate similarity of documents. We present a characterization of Exact MWIPFs by size uniformity, which represents certain symmetry of the string representation of a family. Also, we present a general
A Small Approximately MinWise Independent Family of Hash Functions
 Journal of Algorithms
, 1999
"... In this paper we give a construction of a small approximately minwise independent family of hash functions. The number of bits needed to represent each function is O(logn \Delta log 1=ffl). This construction gives a solution to the main open problem of [2]. 1 Introduction A family of functions H ..."
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Cited by 82 (1 self)
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In this paper we give a construction of a small approximately minwise independent family of hash functions. The number of bits needed to represent each function is O(logn \Delta log 1=ffl). This construction gives a solution to the main open problem of [2]. 1 Introduction A family of functions
Exponential Time Improvement for minwise Based Algorithms ∗
"... In this paper we extend the notion of minwise independent family of hash functions by defining a kminwise independent family of hash functions. Informally, under this definition, all subsets of size k of any fixed set X have an equal chance to have the minimal hash values among all the elements i ..."
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Cited by 8 (4 self)
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In this paper we extend the notion of minwise independent family of hash functions by defining a kminwise independent family of hash functions. Informally, under this definition, all subsets of size k of any fixed set X have an equal chance to have the minimal hash values among all the elements
A Derandomization Using MinWise Independent Permutations
 In Randomization and approximation techniques in computer science
"... . Minwise independence is a recently introduced notion of limited independence, similar in spirit to pairwise independence. The later has proven essential for the derandomization of many algorithms. Here we show that approximate minwise independence allows similar uses, by presenting a derando ..."
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Cited by 19 (2 self)
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. Minwise independence is a recently introduced notion of limited independence, similar in spirit to pairwise independence. The later has proven essential for the derandomization of many algorithms. Here we show that approximate minwise independence allows similar uses, by presenting a
Constructing an Optimal Family of MinWise Independent Permutations
, 2000
"... this paper, we shallcoll[53 a familyF ..."
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