Here we show that machine learning shares this fate. We describe simple scenarios where learnability cannot be proved nor refuted using the standard axioms of mathematics. Our proof is based on the fact the continuum hypothesis cannot be proved nor refuted. We show that, in some cases, a ...
(1995). Boosting a weak learning algorithm by majority. To appear inInformation and Computation. Goldman, S., & Sloan, R. (1994). The power of self-directed learning.Machine Learning Vol. 14 No. 3, 271–294. Google Scholar Haussler, D. (1988).Space efficient learning algorithms. ...
Considering n unbounded parameters, they generate an n-dimensional space (imposing bounds results in a sub-space without relevant changes in our discussion) where each point, together with the immutable part of the estimator function, represents a learning hypothesis H (associated with a specific ...
Machine learning techniques can naturally aid this task, by providing the agent with the rules to be used for making these predictions. For this to happen, however, learning algorithms need to be developed that can deal with missing information in the learning examples in a principled manner, ...
Learning pattern classification-A survey 1998, IEEE Transactions on Information Theory The importance of convexity in learning with squared loss 1998, IEEE Transactions on Information Theory Stealing machine learning models via prediction APIs 2016, Proceedings of the 25th USENIX Security Symposium A discri...
1 Introduction The PAC-model is concerned with learning concepts f (sets of strings from some domain X), grouped together in a concept class F. F is called PAC-learnable if, globally, an algorithm exists that reads in examples (pairs x, y where x C X and y = 0 if x ~ f and y...
Summary: The problem of ranking, in which the goal is to learn a real-valued ranking function that induces a ranking or ordering over an instance space, has recently gained attention in machine learning. We define a model of learnability for ranking functions in a particular setting of the ra...
logic and games corner the imp game: learnability, approximability and adversarial learning beyond 0 1 来自 dx.doi.org 喜欢 0 阅读量: 31 作者:M Brand,DL Dowe DOI: 10.1093/logcom/exw031 收藏 引用 批量引用 报错 分享 全部来源 求助全文 dx.doi.org ...
–Learnabilitymodels–Resultsandimplications–Proofsketches–Learningtime •EmpiricalStudies:Bohannon&Stanowicz’sExperimentonAdultFeedback,andGordon’sAttack Gold’s“IdentificationintheLimit”(1967)Motivations •Q:Howtomodelnaturallanguagesinartificialsystems?–Lowerbound:richenoughtosimulatethelinguisticphenomena ...
machine learningComputational phonology approaches the study of sound patterns in the world's languages from a computational perspective. This article explains this perspective and its relevance to phonology. A restrictive, universal property of phonological patterns – they are regular – is established,...