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 ...
Learnability of the Superset Label Learning Problem In the Superset Label Learning (SLL) problem, weak supervision is provided in the form of a of labels that contains the true label. If the classifier predicts a label outside of the superset, it commits a . Most existing SLL algorithms l....
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...
(1995). Boosting a weak learning algorithm by majority. To appear in Information 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....
They have been used in many areas, including combinatorial optimization, machine learning, and economics. In this work we study submodular functions from a learning theoretic angle. We provide algorithms for learning submodular functions, as well as lower bounds on their learnability. In doing so, ...
- 《Machine Learning》 被引量: 127发表: 1993年 Determining the shape of a convex n-sided polygon by using 2n+k tactile probes Itai, Learnability by fixed distributions, in: D. Haussler and L. Pitt, eds., Proceedings of the 1988 Workshop on Computational Learning Theory (Morgan... HJ ...
In this article, PAC-learning theory is applied to model inference, which concerns the problem of inferring theories from facts in first order logic. It is argued that uniform sample PAC-learnabilityDOI: 10.1007/3-540-57868-4_60 被引量: 4 年份...
Carin-ALN is an interesting new rule learning bias for ILP. By allowing description logic terms as predicates of literals in datalog rules, it extends the ... JU Kietz - International Conference on Machine Learning, Fifteenth Conference on Inductive Logic Programming: International Conference on Indu...
The Fourier transform of Boolean functions has received considerable attention in the last few years in the computational learning theory community, and ha... YISHAY MANSOUR,SIGAL SAHAR - 《Machine Learning》 被引量: 26发表: 2000年 Optimal Learning via the Fourier Transform for Sums of Independent...
Statistics - Machine LearningQuantum machine learning has received significant attention in recent years, and promising progress has been made in the development of quantum algorithms to speed up traditional machine learning tasks. In this work, however, we focus on investigating the information-...