A Generalized Framework for Revealing Analogous Themes across Related Topics (2005)
Marx, Zvika, Dagan, Ido, Shamir, Eli
This work addresses the task of identifying thematic correspondences across subcorpora focused on different topics. We introduce an unsupervised algorithmic framework based on distributional data...
Annotating Concept Mention Patterns (2004)
Beata Beigman Klebanov, Eli Shamir
This paper presents an annotation project aimed at elicitation of concept interconnections within people's common knowledge. Motivation, annotation scheme and relevant previous work are discussed and...
Identifying structure across pre-partitioned data (2004)
Marx, Zvika, Dagan, Dr. Ido, Shamir, Eli
We propose an information-theoretic clustering approach that incorporates a pre-known partition of the data, aiming to identify common clusters that cut across the given partition. In the standard...
Coupled Clustering: A Method for Detecting Structural Correspondence (2003)
Zvika Marx, Ido Dagan, Joachim M. Buhmann, Eli Shamir, E. Brodley, Andrea Danyluk
This paper proposes a new paradigm and a computational framework for revealing equivalencies (analogies) between sub-structures of distinct composite systems that are initially represented by...
Cross-dataset Clustering: Revealing Corresponding Themes Across Multiple Corpora (2002)
Ido Dagan, Zvika Marx, Eli Shamir
We present a method for identifying corresponding themes across several corpora that are focused on related, but distinct, domains. This task is approached through simultaneous clustering of keyword...
Cross-dataset Clustering: Revealing Corresponding Themes Across Multiple Corpora (2002)
Ido Dagan, Zvika Marx, Eli Shamir
We present a method for identifying corresponding themes across several corpora that are focused on related, but distinct, domains. This task is approached through simultaneous clustering of keyword...
Cross-component Clustering for Template Induction (2002)
Zvika Marx, Ido Dagan, Eli Shamir
We suggest an unsupervised approach to template induction for information extraction, through detecting sub-topics and themes that cut across the documents of a topical corpus. We introduce a new...
Learning with Queries Corrupted by Classification Noise (2001)
Kearns introduced the statistical query" (SQ) model as a general method for producing learning algorithms which are robust against classication noise. We extend this approach in several ways in order...
Selective Sampling Using the Query by Committee Algorithm (2001)
Yoav Freund, Eli Shamir, David Haussler
. We analyze the "query by committee" algorithm, a method for filtering informative queries from a random stream of inputs. We show that if the two-member committee algorithm achieves information...
Learning Using Query by Committee, Linear Separation and Random Walks (2000)
Shai Fine, Ran Gilad-bachrach, Eli Shamir
. In the Active Learning paradigm [CAL90] the learner tries to minimize the number of labeled instances it uses in the process of learning. The reasoning comes from many real life problems where the...
Shai Fine, Ran Gilad-bachrach, Eli Shamir, Naftali Tishby
Generalization in most PAC learning analysis starts around O (d) examples, where d = V C dim of the class. Nevertheless, analysis of learning curves using statistical mechanics shows much earlier...
Sample-efficient Strategies for Learning in the Presence of Noise (2000)
Eli Dichterman Lse, Via Comelico, Eli Dichterman, Royal Holloway, Paul Fischer, Eli Shamir, ...
In this paper we prove various results about PAC learning in the presence of malicious noise. Our main interest is the sample size behaviour of learning algorithms. We prove the first nontrivial...
Detecting Sub-Topic Correspondence through Bipartite Term Clustering (1999)
Marx, Zvika, Dagan, Ido, Shamir, Eli
This paper addresses a novel task of detecting sub-topic correspondence in a pair of text fragments, enhancing common notions of text similarity. This task is addressed by coupling corresponding term...
Selective sampling using the Query by Committee algorithm (1999)
Yoav Freund, H. Sebastian Seung, Eli Shamir, Naftali Tishby
We analyze the "query by committee" algorithm, a method for filtering informative queries from a random stream of inputs. We show that if the two-member committee algorithm achieves information gain...
Noise Tolerant Learning Using Early Predictors (1999)
Shai Fine, Ran Gilad-bachrach, Eli Shamir, Naftali Tishby
Generalization in most PAC learning analysis starts around O (d) examples, where d = V C dim of the class. Nevertheless, analysis of learning curves using statistical mechanics shows much earlier...
Detecting Sub-Topic Correspondence through Bipartite Term Clustering (1999)
Zvika Marx, Ido Dagan, Eli Shamir
This paper addresses a novel task of detecting sub-topic correspondence in a pair of text fragments, enhancing common notions of text similarity. This task is addressed by coupling corresponding term...
Query by Committee, Linear Separation and (1999)
Ran Bachrach, Shai Fine, Eli Shamir
Recent works have shown the advantage of using Active Learning methods, such as the Query by Committee (QBC) algorithm, to various learning problems. This class of Algorithms requires an oracle with...
Sample-efficient Strategies for Learning in the Presence of Noise (1999)
Eli Dichterman, Paul Fischer, Eli Shamir, Hans Ulrich Simon
In this paper we prove various results about PAC learning in the presence of malicious noise. Our main interest is the sample size behaviour of learning algorithms. We prove the first nontrivial...
Query by Committee, Linear Separation and Random Walks (1998)
Ran Bachrach, Shai Fine, Eli Shamir
Recent works have shown the advantage of using Active Learning methods, such as the Query by Committee (QBC) algorithm, to various learning problems. This class of Algorithms requires an oracle with...
Query by Committee, Linear Separation and Random Walks (1998)
Ran Bachrach, Shai Fine, Eli Shamir
Recent works have shown the advantage of using Active Learning methods, such as the Query by Committee (QBC) algorithm, to various learning problems. This class of Algorithms requires an oracle with...
Selective sampling using the Query by Committee algorithm (1998)
. We analyze the "query by committee" algorithm, a method for filtering informative queries from a random stream of inputs. We show that if the two-member committee algorithm achieves information...
Finding hidden Hamiltonian cycles (1998)
Andrei Z. Broder, Alan M. Frieze, Eli Shamir
Consider a random graph G composed of a Hamiltonian cycle on n labeled vertices and dn random edges that "hide" the cycle. Is it possible to unravel the structure, that is, to efficiently find a...
Finding hidden Hamiltonian cycles (1997)
Andrei Z. Broder, Alan M. Frieze, Eli Shamir
Consider a random graph G composed of a Hamiltonian cycle on n labeled vertices and dn random edges that "hide" the cycle. Is it possible to unravel the structure, that is, to efficiently find a...
Selective sampling using the Query by Committee algorithm (1997)
Yoav Freund, H. Sebastian Seung, Eli Shamir, Naftali Tishby
We analyze the "query by committee" algorithm, a method for filtering informative queries from a random stream of inputs. We show that if the two-member committee algorithm achieves information gain...
Selective sampling using the Query by Committee algorithm (1997)
Yoav Freund, H. Sebastian Seung, Eli Shamir, Naftali Tishby
We analyze the "query by committee" algorithm, a method for filtering informative queries from a random stream of inputs. We show that if the two-member committee algorithm achieves information gain...