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759
Coding for Computing
 IEEE Transactions on Information Theory
, 1998
"... A sender communicates with a receiver who wishes to reliably evaluate a function of their combined data. We show that if only the sender can transmit, the number of bits required is a conditional entropy of a naturally defined graph. We also determine the number of bits needed when the communicators ..."
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Cited by 138 (0 self)
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A sender communicates with a receiver who wishes to reliably evaluate a function of their combined data. We show that if only the sender can transmit, the number of bits required is a conditional entropy of a naturally defined graph. We also determine the number of bits needed when the communicators exchange two messages. 1 Introduction Let f be a function of two random variables X and Y . A sender PX knows X, a receiver PY knows Y , and both want PY to reliably determine f(X; Y ). How many bits must PX transmit? Embedding this communicationcomplexity scenario (Yao [22]) in the standard informationtheoretic setting (Shannon [17]), we assume that (1) f(X; Y ) must be determined for a block of many independent (X; Y )instances, (2) PX transmits after observing the whole block of X instances, (3) a vanishing block error probability is allowed, and (4) the problem's rate L f (XjY ) is the number of bits transmitted for the block, normalized by the number of instances. Two simple bou...
The communication requirements of efficient allocations and supporting prices
 Journal of Economic Theory
, 2006
"... We show that any communication finding a Pareto efficient allocation in a privateinformation economy must also discover supporting Lindahl prices. In particular, efficient allocation of L indivisible objects requires naming a price for each of the 2 L ¡1 bundles. Furthermore, exponential communicat ..."
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Cited by 134 (18 self)
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We show that any communication finding a Pareto efficient allocation in a privateinformation economy must also discover supporting Lindahl prices. In particular, efficient allocation of L indivisible objects requires naming a price for each of the 2 L ¡1 bundles. Furthermore, exponential communication in L is needed just to ensure a higher share of surplus than that realized by auctioning all items as a bundle, or even a higher expected surplus (for some probability distribution over valuations). When the valuations are submodular, efficiency still requires exponential communication (and fully polynomial approximation is impossible). When the objects are homogeneous, arbitrarily good approximation is obtained using exponentially less communication than that needed for exact efficiency.
Protecting Data Privacy in Private Information Retrieval Schemes
 JCSS
"... Private Information Retrieval (PIR) schemes allow a user to retrieve the ith bit of an nbit data string x, replicated in k 2 databases (in the informationtheoretic setting) or in k 1 databases (in the computational setting), while keeping the value of i private. The main cost measure for suc ..."
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Cited by 133 (21 self)
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Private Information Retrieval (PIR) schemes allow a user to retrieve the ith bit of an nbit data string x, replicated in k 2 databases (in the informationtheoretic setting) or in k 1 databases (in the computational setting), while keeping the value of i private. The main cost measure for such a scheme is its communication complexity.
Simulating BPP Using a General Weak Random Source
 ALGORITHMICA
, 1996
"... We show how to simulate BPP and approximation algorithms in polynomial time using the output from a ffisource. A ffisource is a weak random source that is asked only once for R bits, and must output an Rbit string according to some distribution that places probability no more than 2 \GammaffiR on ..."
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Cited by 124 (17 self)
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We show how to simulate BPP and approximation algorithms in polynomial time using the output from a ffisource. A ffisource is a weak random source that is asked only once for R bits, and must output an Rbit string according to some distribution that places probability no more than 2 \GammaffiR on any particular string. We also give an application to the unapproximability of Max Clique.
Secure multiparty computation of approximations
, 2001
"... Approximation algorithms can sometimes provide efficient solutions when no efficient exact computation is known. In particular, approximations are often useful in a distributed setting where the inputs are held by different parties and may be extremely large. Furthermore, for some applications, the ..."
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Cited by 108 (25 self)
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Approximation algorithms can sometimes provide efficient solutions when no efficient exact computation is known. In particular, approximations are often useful in a distributed setting where the inputs are held by different parties and may be extremely large. Furthermore, for some applications, the parties want to compute a function of their inputs securely, without revealing more information than necessary. In this work we study the question of simultaneously addressing the above efficiency and security concerns via what we call secure approximations. We start by extending standard definitions of secure (exact) computation to the setting of secure approximations. Our definitions guarantee that no additional information is revealed by the approximation beyond what follows from the output of the function being approximated. We then study the complexity of specific secure approximation problems. In particular, we obtain a sublinearcommunication protocol for securely approximating the Hamming distance and a polynomialtime protocol for securely approximating the permanent and related #Phard problems. 1
Towards scaling fully personalized PageRank
 In Proceedings of the 3rd Workshop on Algorithms and Models for the WebGraph (WAW
, 2004
"... Abstract Personalized PageRank expresses backlinkbased page quality around userselected pages in a similar way as PageRank expresses quality over the entire Web. Existing personalized PageRank algorithms can however serve online queries only for a restricted choice of page selection. In this pape ..."
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Cited by 104 (2 self)
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Abstract Personalized PageRank expresses backlinkbased page quality around userselected pages in a similar way as PageRank expresses quality over the entire Web. Existing personalized PageRank algorithms can however serve online queries only for a restricted choice of page selection. In this paper we achieve full personalization by a novel algorithm that computes a compact database of simulated random walks; this database can serve arbitrary personal choices of small subsets of web pages. We prove that for a fixed error probability, the size of our database is linear in the number of web pages. We justify our estimation approach by asymptotic worstcase lower bounds; we show that exact personalized PageRank values can only be obtained from a database of quadratic size. 1
Index Coding with Side Information
, 2006
"... Motivated by a problem of transmitting supplemental data over broadcast channels (Birk and Kol, INFOCOM 1998), we study the following coding problem: a sender communicates with n receivers R1,..., Rn. He holds an input x ∈ {0, 1} n and wishes to broadcast a single message so that each receiver Ri c ..."
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Cited by 103 (0 self)
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Motivated by a problem of transmitting supplemental data over broadcast channels (Birk and Kol, INFOCOM 1998), we study the following coding problem: a sender communicates with n receivers R1,..., Rn. He holds an input x ∈ {0, 1} n and wishes to broadcast a single message so that each receiver Ri can recover the bit xi. Each Ri has prior side information about x, induced by a directed graph G on n nodes; Ri knows the bits of x in the positions {j  (i, j) is an edge of G}. G is known to the sender and to the receivers. We call encoding schemes that achieve this goal INDEX codes for {0, 1} n with side information graph G. In this paper we identify a measure on graphs, the minrank, which exactly characterizes the minimum length of linear and certain types of nonlinear INDEX codes. We show that for natural classes of side information graphs, including directed acyclic graphs, perfect graphs, odd holes, and odd antiholes, minrank is the optimal length of arbitrary INDEX codes. For arbitrary INDEX codes and arbitrary graphs, we obtain a lower bound in terms of the size of the maximum acyclic induced subgraph. This bound holds even for randomized codes, but is shown not to be tight.
On the Limitations of Universally Composable TwoParty Computation without Setup Assumptions
 Journal of Cryptology
, 2003
"... Abstract. The recently proposed universally composable (UC) security framework, for analyzing security of cryptographic protocols, provides very strong security guarantees. In particular, a protocol proven secure in this framework is guaranteed to maintain its security even when deployed in arbitrar ..."
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Cited by 103 (18 self)
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Abstract. The recently proposed universally composable (UC) security framework, for analyzing security of cryptographic protocols, provides very strong security guarantees. In particular, a protocol proven secure in this framework is guaranteed to maintain its security even when deployed in arbitrary multiparty, multiprotocol, multiexecution environments. Protocols for securely carrying out essentially any cryptographic task in a universally composable way exist, both in the case of an honest majority (in the plain model, i.e., without setup assumptions) and in the case of no honest majority (in the common reference string model). However, in the plain model, little was known for the case of no honest majority and, in particular, for the important special case of twoparty protocols. We study the feasibility of universally composable twoparty function evaluation in the plain model. Our results show that very few functions can be computed in this model so as to provide the UC security guarantees. Specifically, for the case of deterministic functions, we provide a full characterization of the functions computable in this model. (Essentially, these are the functions that depend on at most one of the parties’ inputs, and furthermore are “efficiently invertible ” in a sense defined within.) For the case of probabilistic functions, we show that the only functions computable in this model are those where one of the parties can essentially uniquely determine the joint output. 1
Informational Complexity and the Direct Sum Problem for Simultaneous Message Complexity
 In Proceedings of the 42nd Annual IEEE Symposium on Foundations of Computer Science
, 2001
"... Given m copies of the same problem, does it take m times the amount of resources to solve these m problems? This is the direct sum problem, a fundamental question that has been studied in many computational models. We study this question in the simultaneous message (SM) model of communication introd ..."
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Cited by 102 (10 self)
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Given m copies of the same problem, does it take m times the amount of resources to solve these m problems? This is the direct sum problem, a fundamental question that has been studied in many computational models. We study this question in the simultaneous message (SM) model of communication introduced by Yao [Y79]. The equality problem for nbit strings is well known to have SM complexity ( p n). We prove that solving m copies of the problem has complexity m p n); the best lower bound provable using previously known techniques is p mn). We also prove similar lower bounds on certain Boolean combinations of multiple copies of the equality function. These results can be generalized to a broader class of functions. We introduce a new notion of informational complexity which is related to SM complexity and has nice direct sum properties. This notion is used as a tool to prove the above results; it appears to be quite powerful and may be of independent interest. 1