By Kamalika Chaudhuri, CLAUDIO GENTILE, Sandra Zilles

This booklet constitutes the complaints of the twenty sixth foreign convention on Algorithmic studying concept, ALT 2015, held in Banff, AB, Canada, in October 2015, and co-located with the 18th overseas convention on Discovery technological know-how, DS 2015. The 23 complete papers provided during this quantity have been conscientiously reviewed and chosen from forty four submissions. furthermore the e-book includes 2 complete papers summarizing the invited talks and a couple of abstracts of invited talks. The papers are geared up in topical sections named: inductive inference; studying from queries, educating complexity; computational studying thought and algorithms; statistical studying conception and pattern complexity; on-line studying, stochastic optimization; and Kolmogorov complexity, algorithmic info theory.

Show description

Read Online or Download Algorithmic Learning Theory: 26th International Conference, ALT 2015, Banff, AB, Canada, October 4-6, 2015, Proceedings PDF

Similar data mining books

Big Data Imperatives: Enterprise Big Data Warehouse, BI Implementations and Analytics

Substantial facts Imperatives, makes a speciality of resolving the foremost questions about everyone’s brain: Which facts issues? Do you've sufficient information quantity to justify the utilization? the way you are looking to procedure this quantity of information? How lengthy do you really want to maintain it energetic on your research, advertising and marketing, and BI functions?

Biometric System and Data Analysis: Design, Evaluation, and Data Mining

Biometric method and information research: layout, evaluate, and knowledge Mining brings jointly points of information and desktop studying to supply a complete consultant to guage, interpret and comprehend biometric facts. This expert e-book obviously ends up in issues together with info mining and prediction, broadly utilized to different fields yet no longer carefully to biometrics.

Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data

Data, facts Mining, and desktop studying in Astronomy: a pragmatic Python consultant for the research of Survey information (Princeton sequence in glossy Observational Astronomy)As telescopes, detectors, and pcs develop ever extra strong, the quantity of knowledge on the disposal of astronomers and astrophysicists will input the petabyte area, supplying exact measurements for billions of celestial items.

Computational Intelligence in Data Mining - Volume 1: Proceedings of the International Conference on CIDM, 20-21 December 2014

The contributed quantity goals to explicate and deal with the problems and demanding situations for the seamless integration of 2 middle disciplines of desktop technological know-how, i. e. , computational intelligence and information mining. information Mining goals on the automated discovery of underlying non-trivial wisdom from datasets via making use of clever research ideas.

Additional info for Algorithmic Learning Theory: 26th International Conference, ALT 2015, Banff, AB, Canada, October 4-6, 2015, Proceedings

Example text

There are priced-learnable classes which are not iteratively learnable. The current work introduces the basic definitions and results for priced learning. This work also introduces various variants of priced learning. e. languages and an unknown language L from this class, the learner observes an infinite list containing all and only the elements of L. The order and multiplicity of the elements of L in the list may be arbitrary. As the learner is observing the members of the list, it outputs a sequence of hypotheses about what the input language might be.

In our simplified topic model for documents, the latent variable h is interpreted as the (sole) topic of a given document, and it is assumed to take only a finite number of distinct values. Let k be the number of distinct topics in the corpus, d be the number of distinct words in the vocabulary, and ≥ 3 be the number of words in each document. The generative process for a document is as follows: the document’s topic is drawn according to the discrete distribution specified by the probability vector w := (w1 , w2 , .

X}; however, the learner can no longer recover the exact value of x from its memory. The idea of priced learning is to relax the severe constraints placed on iterative learning. In priced learning, a price is charged for each update of the memory and it is required that during the learning process, the overall costs incurred is finite. In the case that this price charged is always the same constant c for each memory update, the corresponding notion would be exactly that of iterative learning.

Download PDF sample

Rated 4.71 of 5 – based on 34 votes