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Author

Uriel Feige

Other affiliations: Max Planck Society, Microsoft, IBM  ...read more
Bio: Uriel Feige is an academic researcher from Weizmann Institute of Science. The author has contributed to research in topics: Approximation algorithm & Time complexity. The author has an hindex of 67, co-authored 282 publications receiving 19733 citations. Previous affiliations of Uriel Feige include Max Planck Society & Microsoft.


Papers
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Journal ArticleDOI
TL;DR: It is proved that (1 - o(1) ln n setcover is a threshold below which setcover cannot be approximated efficiently, unless NP has slightlysuperpolynomial time algorithms.
Abstract: Given a collection ℱ of subsets of S = {1,…,n}, set cover is the problem of selecting as few as possible subsets from ℱ such that their union covers S,, and max k-cover is the problem of selecting k subsets from ℱ such that their union has maximum cardinality. Both these problems are NP-hard. We prove that (1 - o(1)) ln n is a threshold below which set cover cannot be approximated efficiently, unless NP has slightly superpolynomial time algorithms. This closes the gap (up to low-order terms) between the ratio of approximation achievable by the greedy alogorithm (which is (1 - o(1)) ln n), and provious results of Lund and Yanakakis, that showed hardness of approximation within a ratio of (log2n) / 2 ≃0.72 ln n. For max k-cover, we show an approximation threshold of (1 - 1/e)(up to low-order terms), under assumption that P ≠ NP.

2,941 citations

Journal ArticleDOI
TL;DR: This paper defines the definition of unrestricted input zero- knowledge proofs of knowledge in which the prover demonstrates possession of knowledge without revealing any computational information whatsoever (not even the one bit revealed in zero-knowledge proofs of assertions).
Abstract: In this paper we extend the notion of interactive proofs of assertions to interactive proofs of knowledge. This leads to the definition of unrestricted input zero-knowledge proofs of knowledge in which the prover demonstrates possession of knowledge without revealing any computational information whatsoever (not even the one bit revealed in zero-knowledge proofs of assertions). We show the relevance of these notions to identification schemes, in which parties prove their identity by demonstrating their knowledge rather than by proving the validity of assertions. We describe a novel scheme which is provably secure if factoring is difficult and whose practical implementations are about two orders of magnitude faster than RSA-based identification schemes. The advantages of thinking in terms of proofs of knowledge rather than proofs of assertions are demonstrated in two efficient variants of the scheme: unrestricted input zero-knowledge proofs of knowledge are used in the construction of a scheme which needs no directory; a version of the scheme based on parallel interactive proofs (which are not known to be zero knowledge) is proved secure by observing that the identification protocols are proofs of knowledge.

1,187 citations

Proceedings ArticleDOI
01 Apr 1990
TL;DR: This work proves two central results: Unlike zero knowledge protocols, witness indistinguishablity is preserved under arbi t rary composition of protocols, including parallel execution, and any witness indistinguishable protocol for this s ta tement is also.
Abstract: A two par ty protocol in which par ty A uses one of several secret witnesses to an NP assertion is witness indistinguishable if par ty B cannot tell which witness A is actually using. The protocol is witness hiding if by the end of the protocol B cannot compute any new witness which he did not know before the protocol began. Witness hiding is a natural security requirement, and can replace zero knowledge in many cryptographic protocols. We prove two central results: 1. Unlike zero knowledge protocols, witness indistinguishablity is preserved under arbi t rary composition of protocols, including parallel execution. 2. If a s ta tement has at least two independent witnesses, then any witness indistinguishable protocol for this s ta tement is also

639 citations

Journal ArticleDOI
TL;DR: An approximation algorithm is developed for the problem of computing the dense k -vertex subgraph of a given graph, namely, the subgraph with the most edges, with approximation ratio O(nδ) , for some δ < 1/3 .
Abstract: This paper considers the problem of computing the dense k -vertex subgraph of a given graph, namely, the subgraph with the most edges. An approximation algorithm is developed for the problem, with approximation ratio O(n δ ) , for some δ < 1/3 .

596 citations

Journal ArticleDOI
TL;DR: The connection between cliques and efficient multi-prover interaction proofs, is shown to yield hardness results on the complexity of approximating the size of the largest clique in a graph.
Abstract: The contribution of this paper is two-fold. First, a connection is established between approximating the size of the largest clique in a graph and multi-prover interactive proofs. Second, an efficient multi-prover interactive proof for NP languages is constructed, where the verifier uses very few random bits and communication bits. Last, the connection between cliques and efficient multi-prover interaction proofs, is shown to yield hardness results on the complexity of approximating the size of the largest clique in a graph.Of independent interest is our proof of correctness for the multilinearity test of functions.

527 citations


Cited by
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Book
01 Jan 1996
TL;DR: A valuable reference for the novice as well as for the expert who needs a wider scope of coverage within the area of cryptography, this book provides easy and rapid access of information and includes more than 200 algorithms and protocols.
Abstract: From the Publisher: A valuable reference for the novice as well as for the expert who needs a wider scope of coverage within the area of cryptography, this book provides easy and rapid access of information and includes more than 200 algorithms and protocols; more than 200 tables and figures; more than 1,000 numbered definitions, facts, examples, notes, and remarks; and over 1,250 significant references, including brief comments on each paper.

13,597 citations

Proceedings ArticleDOI
13 Aug 2016
TL;DR: In this article, the authors propose LIME, a method to explain models by presenting representative individual predictions and their explanations in a non-redundant way, framing the task as a submodular optimization problem.
Abstract: Despite widespread adoption, machine learning models remain mostly black boxes. Understanding the reasons behind predictions is, however, quite important in assessing trust, which is fundamental if one plans to take action based on a prediction, or when choosing whether to deploy a new model. Such understanding also provides insights into the model, which can be used to transform an untrustworthy model or prediction into a trustworthy one. In this work, we propose LIME, a novel explanation technique that explains the predictions of any classifier in an interpretable and faithful manner, by learning an interpretable model locally varound the prediction. We also propose a method to explain models by presenting representative individual predictions and their explanations in a non-redundant way, framing the task as a submodular optimization problem. We demonstrate the flexibility of these methods by explaining different models for text (e.g. random forests) and image classification (e.g. neural networks). We show the utility of explanations via novel experiments, both simulated and with human subjects, on various scenarios that require trust: deciding if one should trust a prediction, choosing between models, improving an untrustworthy classifier, and identifying why a classifier should not be trusted.

11,104 citations

Journal ArticleDOI
TL;DR: A thorough exposition of community structure, or clustering, is attempted, from the definition of the main elements of the problem, to the presentation of most methods developed, with a special focus on techniques designed by statistical physicists.
Abstract: The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices of the same cluster and comparatively few edges joining vertices of different clusters. Such clusters, or communities, can be considered as fairly independent compartments of a graph, playing a similar role like, e. g., the tissues or the organs in the human body. Detecting communities is of great importance in sociology, biology and computer science, disciplines where systems are often represented as graphs. This problem is very hard and not yet satisfactorily solved, despite the huge effort of a large interdisciplinary community of scientists working on it over the past few years. We will attempt a thorough exposition of the topic, from the definition of the main elements of the problem, to the presentation of most methods developed, with a special focus on techniques designed by statistical physicists, from the discussion of crucial issues like the significance of clustering and how methods should be tested and compared against each other, to the description of applications to real networks.

9,057 citations

Journal ArticleDOI
TL;DR: A thorough exposition of the main elements of the clustering problem can be found in this paper, with a special focus on techniques designed by statistical physicists, from the discussion of crucial issues like the significance of clustering and how methods should be tested and compared against each other, to the description of applications to real networks.

8,432 citations

Proceedings ArticleDOI
22 Jan 2006
TL;DR: Some of the major results in random graphs and some of the more challenging open problems are reviewed, including those related to the WWW.
Abstract: We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

7,116 citations