Identifying and Accounting for Task-Dependent Bias in Crowdsourcing
... relationships among task features, workers’ biases, annotations and ground truth task answers (labels). Given a set of ground-truth labels provided by experts, the models can detect and learn about task-dependent biases by observing when majority opinion disagrees with ground truth. Inferences about ...
... relationships among task features, workers’ biases, annotations and ground truth task answers (labels). Given a set of ground-truth labels provided by experts, the models can detect and learn about task-dependent biases by observing when majority opinion disagrees with ground truth. Inferences about ...
pptx - Electrical and Computer Engineering
... contain more than one entry per state-letter pair – When more than one transition is possible, a non-deterministic Turing machine branches and creating a new sequence of computation for each possible transition ...
... contain more than one entry per state-letter pair – When more than one transition is possible, a non-deterministic Turing machine branches and creating a new sequence of computation for each possible transition ...
Fan, Jianqing, Gijbels, Irene, Hu, Tien-Chung and Huang, Li-Shan; (1993).An Asymptotic Study of Variable Bandwidth Selectin for Local Polynomial Regression with Application to Density Estimation."
... relative to the theoretical optimal variable bandwidth. Furthermore, we show how to convert a density estimation problem into a regression problem. This inner connection makes it possible to apply the regression techniques for density estimation. The organization of the paper is as follows. In the n ...
... relative to the theoretical optimal variable bandwidth. Furthermore, we show how to convert a density estimation problem into a regression problem. This inner connection makes it possible to apply the regression techniques for density estimation. The organization of the paper is as follows. In the n ...
Open Language Learning for Information Extraction
... parsing, since it is fast and hence, easily applicable to a large corpus of sentences. We post-process the parses using Stanford’s CCprocessed algorithm, which compacts the parse structure for easier extraction (de Marneffe et al., 2006). We randomly sampled 100 sentences from our bootstrapping set ...
... parsing, since it is fast and hence, easily applicable to a large corpus of sentences. We post-process the parses using Stanford’s CCprocessed algorithm, which compacts the parse structure for easier extraction (de Marneffe et al., 2006). We randomly sampled 100 sentences from our bootstrapping set ...
CV - Claremont McKenna College
... Monte Carlo simulation for statistical applications, approximation algorithms, and numerical integration. Design and analysis of new sampling methods that draw variates exactly from high-dimensional target distributions, and more efficient methods for utilizing these samples. ...
... Monte Carlo simulation for statistical applications, approximation algorithms, and numerical integration. Design and analysis of new sampling methods that draw variates exactly from high-dimensional target distributions, and more efficient methods for utilizing these samples. ...
Extending the Applications of Recent Real-time Heuristic Search
... Database precomputation time for large search spaces can be in the order of days (Lawrence and Bulitko 2010), so testing performance on a search space can be an expensive proposition. Therefore, we suggest a more computationally efficient method to predict algorithm performance. Incorporating previou ...
... Database precomputation time for large search spaces can be in the order of days (Lawrence and Bulitko 2010), so testing performance on a search space can be an expensive proposition. Therefore, we suggest a more computationally efficient method to predict algorithm performance. Incorporating previou ...
The Laws of Probability and the Law of the Land
... than mathematical probabilities, have simpler, more primitive, properties.. . . [T]hey cannot be added, subtracted, multiplied, or divided. Although evidence can change the probability of an event, we cannot say, for example, that event A is twice as likely as event B, given relevant evidence. In fa ...
... than mathematical probabilities, have simpler, more primitive, properties.. . . [T]hey cannot be added, subtracted, multiplied, or divided. Although evidence can change the probability of an event, we cannot say, for example, that event A is twice as likely as event B, given relevant evidence. In fa ...
A Study on Swarm Intelligence Techniques in Intrusion Detection
... Among the discovered rules the best one is selected and augmented to the discovered rules. This is done iteratively until a large base of rules is constructed which can be later on used in test sets as criteria for classifying network connections into intrusive or normal. The experimental results sh ...
... Among the discovered rules the best one is selected and augmented to the discovered rules. This is done iteratively until a large base of rules is constructed which can be later on used in test sets as criteria for classifying network connections into intrusive or normal. The experimental results sh ...
Introduction to Biostatitics Summer 2005
... ‘random’ errors that are inherent in all data – A tall order • Statisticians start with – Let X1, X2,…, Xn be i.i.d. (independently and identically distributed) with N (µ,σ) to describe the n observations • Epidemiologists put a context and see if the statistical model fits ...
... ‘random’ errors that are inherent in all data – A tall order • Statisticians start with – Let X1, X2,…, Xn be i.i.d. (independently and identically distributed) with N (µ,σ) to describe the n observations • Epidemiologists put a context and see if the statistical model fits ...
