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6,042
Learning to Order Things
 Journal of Artificial Intelligence Research
, 1998
"... There are many applications in which it is desirable to order rather than classify instances. Here we consider the problem of learning how to order, given feedback in the form of preference judgments, i.e., statements to the effect that one instance should be ranked ahead of another. We outline a ..."
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Cited by 409 (12 self)
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a twostage approach in which one first learns by conventional means a preference function, of the form PREF(u; v), which indicates whether it is advisable to rank u before v. New instances are then ordered so as to maximize agreements with the learned preference function. We show
Online selection of discriminative tracking features
, 2003
"... This paper presents an online feature selection mechanism for evaluating multiple features while tracking and adjusting the set of features used to improve tracking performance. Our hypothesis is that the features that best discriminate between object and background are also best for tracking the ..."
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Cited by 356 (5 self)
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according to how well they separate sample distributions of object and background pixels. This feature evaluation mechanism is embedded in a meanshift tracking system that adaptively selects the topranked discriminative features for tracking. Examples are presented that demonstrate how this method adapts
Submodular functions, matroids and certain polyhedra
, 2003
"... The viewpoint of the subject of matroids, and related areas of lattice theory, has always been, in one way or another, abstraction of algebraic dependence or, equivalently, abstraction of the incidence relations in geometric representations of algebra. Often one of the main derived facts is that all ..."
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Cited by 355 (0 self)
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is that all bases have the same cardinality. (See Van der Waerden, Section 33.) From the viewpoint of mathematical programming, the equal cardinality of all bases has special meaning — namely, that every basis is an optimumcardinality basis. We are thus prompted to study this simple property in the context
Data Clustering: 50 Years Beyond KMeans
, 2008
"... Organizing data into sensible groupings is one of the most fundamental modes of understanding and learning. As an example, a common scheme of scientific classification puts organisms into taxonomic ranks: domain, kingdom, phylum, class, etc.). Cluster analysis is the formal study of algorithms and m ..."
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Cited by 294 (7 self)
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Organizing data into sensible groupings is one of the most fundamental modes of understanding and learning. As an example, a common scheme of scientific classification puts organisms into taxonomic ranks: domain, kingdom, phylum, class, etc.). Cluster analysis is the formal study of algorithms
A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirtythree Old and New Classification Algorithms
, 2000
"... . Twentytwo decision tree, nine statistical, and two neural network algorithms are compared on thirtytwo datasets in terms of classication accuracy, training time, and (in the case of trees) number of leaves. Classication accuracy is measured by mean error rate and mean rank of error rate. Both cr ..."
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Cited by 234 (8 self)
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. Twentytwo decision tree, nine statistical, and two neural network algorithms are compared on thirtytwo datasets in terms of classication accuracy, training time, and (in the case of trees) number of leaves. Classication accuracy is measured by mean error rate and mean rank of error rate. Both
The concept of power
 Behavioral Science
, 1957
"... What is “power”? Most people have an intuitive notion of what it means. But scientists have not yet formulated a statement of the concept of power that is rigorous enough to be of use in the systematic study of this important social phenomenon. Power is here defined in terms of a relation between p ..."
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Cited by 240 (0 self)
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What is “power”? Most people have an intuitive notion of what it means. But scientists have not yet formulated a statement of the concept of power that is rigorous enough to be of use in the systematic study of this important social phenomenon. Power is here defined in terms of a relation between
Fast Computation of Low Rank Matrix Approximations
, 2001
"... In many practical applications, given an m n matrix A it is of interest to nd an approximation to A that has low rank. We introduce a technique that exploits spectral structure in A to accelerate Orthogonal Iteration and Lanczos Iteration, the two most common methods for computing such approximat ..."
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Cited by 165 (5 self)
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be viewed as adding a random matrix E to A, where the entries of E are independent, zeromean random variables of bounded variance. Such random matrices posses no significant linear structure, and we can thus prove that the effect of sampling and quantization nearly vanishes when a low rank approximation
Beyond Independent Relevance: Methods and Evaluation Metrics for Subtopic Retrieval
 In Proceedings of SIGIR
, 2003
"... We present a nontraditional retrieval problem we call subtopic retrieval. The subtopic retrieval problem is concerned with finding documents that cover many different subtopics of a query topic. This means that the utility of a document in a ranking is dependent on other documents in the ranking, v ..."
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Cited by 217 (6 self)
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We present a nontraditional retrieval problem we call subtopic retrieval. The subtopic retrieval problem is concerned with finding documents that cover many different subtopics of a query topic. This means that the utility of a document in a ranking is dependent on other documents in the ranking
Automatic Combination of Multiple Ranked Retrieval Systems
, 1994
"... Retrieval performance can often be improved significantly by using a number of different retrieval algorithms and combining the results, in contrast to using just a single retrieval algorithm. This is because different retrieval algorithms, or retrieval experts, often emphasize different document an ..."
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Cited by 164 (5 self)
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be automatically combined to result in superior retrieval performance. We apply the method to two expert combination tasks. The applications demonstrate that the method can identify high performance combinations of experts and also is a novel means for determining the combined effectiveness of experts. 1
Matrix completion from a few entries
"... Let M be a random nα × n matrix of rank r ≪ n, and assume that a uniformly random subset E of its entries is observed. We describe an efficient algorithm that reconstructs M from E  = O(r n) observed entries with relative root mean square error RMSE ≤ C(α) ..."
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Cited by 196 (9 self)
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Let M be a random nα × n matrix of rank r ≪ n, and assume that a uniformly random subset E of its entries is observed. We describe an efficient algorithm that reconstructs M from E  = O(r n) observed entries with relative root mean square error RMSE ≤ C(α)
Results 1  10
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6,042