Tools
Sorted by:
Try your query at:
 |
 |
 |
 |
 |
 |
Results 1 - 10
of
8,663
The Bias Problem and Language Models
"... We used the YFILTER filtering system for experiments on updating profiles and setting thresholds. We developed a new method of using language models for updating profiles that is more focused on picking informative/discriminative words for query. The new method was compared with the well-known Rocch ..."
Abstract
- Add to MetaCart
is corpus dependant. The experimental results also show the sampling bias problem of training data while filtering makes the final profile learned biased.
Solving the Bias Problem in Censored Pharmacokinetic Data
"... Running head: Solving the bias problem in censored PK ..."
The file drawer problem and tolerance for null results
- Psychological Bulletin
, 1979
"... For any given research area, one cannot tell how many studies have been con-ducted but never reported. The extreme view of the "file drawer problem " is that journals are filled with the 5 % of the studies that show Type I errors, while the file drawers are filled with the 95 % of the stud ..."
Abstract
-
Cited by 497 (0 self)
- Add to MetaCart
sciences are a biased sample of the studies that are actually carried out (Bakan, 1967; McNemar, 1960; Smart, 1964; Sterling, 1959). The extreme view of this problem, the "file drawer prob-lem, " is that the journals are filled with the 5 % of the studies that show Type I errors, while the file
RS: Correcting for the sampling bias problem in spike train information measures
- J Neurophysiol
"... for the sampling bias problem in spike train information measures. J ..."
Abstract
-
Cited by 60 (9 self)
- Add to MetaCart
for the sampling bias problem in spike train information measures. J
L.: On bias problem in relevance feedback
- In: Proceedings of the 20th ACM international conference on Information and knowledge management
, 2011
"... Relevance feedback is an effective approach to improve re-trieval quality over the initial query. Typical relevance feed-back methods usually select top-ranked documents for rele-vance judgments, then query expansion or model updating are carried out based on the feedback documents. However, the num ..."
Abstract
-
Cited by 1 (0 self)
- Add to MetaCart
first show how and where the bias problem exists through experiments. Then we study how the bias can be reduced by utilizing the unlabeled documents. After ana-lyzing the usefulness of a document to relevance feedback, we propose an approach that extends the feedback set with carefully selected
Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms
- Evolutionary Computation
, 1994
"... In trying to solve multiobjective optimization problems, many traditional methods scalarize the objective vector into a single objective. In those cases, the obtained solution is highly sensitive to the weight vector used in the scalarization process and demands the user to have knowledge about t ..."
Abstract
-
Cited by 539 (5 self)
- Add to MetaCart
number of solutions simultaneously. Although a vector evaluated GA (VEGA) has been implemented by Schaffer and has been tried to solve a number of multiobjective problems, the algorithm seems to have bias towards some regions. In this paper, we investigate Goldberg's notion of nondominated
Estimating standard errors in finance panel data sets: comparing approaches.
- Review of Financial Studies
, 2009
"... Abstract In both corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms and across time, and OLS standard errors can be biased. Historically, the two literatures have used different solut ..."
Abstract
-
Cited by 890 (7 self)
- Add to MetaCart
Abstract In both corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms and across time, and OLS standard errors can be biased. Historically, the two literatures have used different
Greedy Randomized Adaptive Search Procedures
, 2002
"... GRASP is a multi-start 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 ..."
Abstract
-
Cited by 647 (82 self)
- Add to MetaCart
GRASP is a multi-start 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
An empirical comparison of voting classification algorithms: Bagging, boosting, and variants.
- Machine Learning,
, 1999
"... Abstract. Methods for voting classification algorithms, such as Bagging and AdaBoost, have been shown to be very successful in improving the accuracy of certain classifiers for artificial and real-world datasets. We review these algorithms and describe a large empirical study comparing several vari ..."
Abstract
-
Cited by 707 (2 self)
- Add to MetaCart
variants in conjunction with a decision tree inducer (three variants) and a Naive-Bayes inducer. The purpose of the study is to improve our understanding of why and when these algorithms, which use perturbation, reweighting, and combination techniques, affect classification error. We provide a bias
Trade Liberalization, Exit, and Productivity Improvements: Evidence from Chilean Plants
- Review of Economic Studies
, 2002
"... This paper empirically investigates the effects of liberalized trade on plant productivity in the case of Chile. Chile presents an interesting setting to study this relationship since it underwent a massive trade liberalization that significantly exposed its plants to competition from abroad during ..."
Abstract
-
Cited by 555 (16 self)
- Add to MetaCart
the late 1970s and early 1980s. Methodologically, I approach this question in two steps. In the first step, I estimate a production function to obtain a measure of plant productivity. I estimate the production function semiparametrically to correct for the presence of selection and simultaneity biases
Results 1 - 10
of
8,663
