搜索结果: 1-14 共查到“知识库 Supervised Learning”相关记录14条 . 查询时间(0.054 秒)
Profiled SCA with a New Twist: Semi-supervised Learning
Side-channel attacks Profiled scenario Machine learning
2017/11/13
Profiled side-channel attacks represent the most powerful category of side-channel attacks. In this context, the attacker gains ac- cess of a profiling device to build a precise model which is used to...
Hybrid Reinforcement/Supervised Learning of Dialogue Policies from Fixed Data Sets
data set Computing language
2015/9/6
We propose a method for learning dialogue management policies from a fixed data set. The method
addresses the challenges posed by Information State Update (ISU)-based dialogue systems, which
r...
A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning
Inferring Label Sampling Mechanisms Semi-Supervised Learning
2015/8/21
We consider the situation in semi-supervised learning, where the “label sampling” mechanism stochastically depends on the true response (as well as potentially on the features). We suggest a method of...
A Supervised Learning Approach to Acronym Identification
acronym identification supervised learning
2015/8/3
This paper addresses the task of finding acronym-definition pairs in text. Most of the previous work on the topic is about systems that involve manually generated rules or regular expressions. In this...
Cross-lingual Projected Expectation Regularization for Weakly Supervised Learning
Cross-lingual Projected Expectation Regularization Weakly Supervised Learning
2015/6/12
We consider a multilingual weakly supervised learning scenario where knowledge from annotated corpora in a resource-rich language is transferred via bitext to guide the learning in other languages. Pa...
Automating Crowd-supervised Learning for Spoken Language Systems
Crowd-supervised Learning Spoken Language Systems
2015/3/9
Automating Crowd-supervised Learning for Spoken Language Systems.
Generalized Expectation Criteria for Lightly Supervised Learning
generalized expectation lightly supervised
2014/12/18
Machine learning has facilitated many recent advances in natural language processing and information extraction. Unfortunately, most machine learning methods rely on costly labeled data, which impedes...
Weakly Supervised Learning for Unconstrained Face Processing
deep learning face alignment face recognition machine learning unsupervised alignment unsupervised learning
2014/12/18
Machine face recognition has traditionally been studied under the assumption of a carefully controlled image acquisition process. By controlling image acquisition, variation due to factors such as pos...
Automating Crowd-supervised Learning for Spoken Language Systems
Automating Crowd-supervised Learning Spoken Language Systems
2014/11/27
Spoken language systems often rely on static speech recognizers. When the underlying models are improved on-the-fly,training is usually performed using unsupervised methods. In this work, we explore a...
Hiding Sensitive XML Association Rules With Supervised Learning Technique
XML Document Association Rules Bayesian Network PPDM Model NP-Hard K2 Algorithm
2013/1/28
In the privacy preservation of association rules, sensitivity analysis should be reported after the quantification of items in terms of their occurrence. The traditional methodologies, used for preser...
Genetic Classification of Populations using Supervised Learning
Genetic Classification Populations Supervised Learning
2011/1/5
There are many instances in genetics in which we wish to determine whether two candidate populations are distinguishable on the basis of their genetic structure. Examples include populations which are...
Safe Feature Elimination in Sparse Supervised Learning
Sparse classi cation sparse regression LASSO feature elimination
2010/12/16
We investigate fast methods that allow to quickly eliminate variables (features) in supervised
learning problems involving a convex loss function and a l1-norm penalty, leading to a potentially subst...
Visual Tracking via Weakly Supervised Learning from Multiple Imperfect Oracles
Visual Tracking Weakly Supervised Multiple Imperfect Oracles
2010/12/21
Long-term persistent tracking in ever-changing environments is a challenging task, which often requires addressing difficult object appearance update problems.To solve them, most top-performing method...
Semi-supervised Learning for Image Annotation Based on Conditional Random Fields（图）
Image Annotation Conditional Random Fields
2015/1/24
Automatic image annotation (AIA) has been proved to be an effective and promising solution to automatically deduce the high-level semantics from low-level visual features. Due to the inherent ambiguit...