# A composition theorem for decision tree complexity

Feb 18, 2013 - The decision tree model captures the complexity of computing functions f : Xm â Y in a setting where the quantity of interest is the ...

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Jun 14, 2017 - CC] 14 Jun 2017. A Composition .... We refer the reader to Section 2 for formal .... of B. The reader is referred to Section 3 for the details. 3 ...

Jan 10, 2018 - CC] 10 Jan 2018. A Composition Theorem via Conflict Complexity. Swagato Sanyal â. January 11, 2018. Abstract. Let R(Â·) stand for the bounded-error randomized query complexity. We show that for any relation f â {0, 1}n ÃS and part

Apr 6, 2015 - The goal is to compute f(x), while minimizing the number of queries made to the black box. For a function f : {0,1}n â {0,1}, let D(f) denote the deterministic query complexity (or decision tree complexity) of computing f, the minimum

Sep 29, 2013 - Â§Research partially supported by the MTA RAMKI LendÃ¼let Cryptography Research Group, NSERC, the Hun- garian OTKA grant NN-102029 and an exchange ...... Finding the maximum, i.e., maxC ÏÎ±(C) therefore answers the question whether Î±

Jun 30, 2015 - there exists a protocol computing F with communication log. O(1) â¥. â¥. â¥. Ë f. â¥. â¥. â¥0 . However, the Log-Rank conjecture is still difficult for this special class of functions. One nice approach proposed in [Zha09] is to

Dec 7, 2013 - parity kill number of f, the fewest number of parities on the input variables one has to fix in order to âkillâ f, i.e. to make it constant. DTâ[f] is the depth of the shortest parity decision tree which computes f. These complexi

Aug 22, 2000 - which the oracle and the computer exchange several rounds of messages, each round consisting of O(log ... Unlike classical decision trees, a quantum decision tree algorithm can make queries in a quantum ... and by degree of approximati

Oct 19, 2018 - Using our lower bound we determine the exact parity decision tree ... trees model (in which only the value of a variable can be asked in one query) ... described above is not far from being optimal and that the parity ... Dâ(MAJ) = n

Dec 28, 2017 - Abstract. String matching is one of the most fundamental problems in computer science. A natural problem is to find the number of characters that needs to be queried (i.e. the decision tree complexity) in a string in order to determine

Feb 24, 2018 - Incremental Learning, Decision Trees, Classification. ACM Reference Format: Chaitanya Manapragada, Geoffrey I. Webb, and Mahsa Salehi. 2018. Ex- tremely Fast Decision Tree. In Proceedings of ACM conference (KDD'18). ACM,. New York, NY,

Nov 16, 2016 - decision tree is because of its simplicity and easy interpretability as a classification rule. In a decision tree classifier, each non-leaf node is associated with a so called split rule or a decision function which is a function of th

software project. This will help project managers effectively bid on projects and supervise winning projects. Software estimators have been notorious in predicting unrealistic software ... expert judgment such as [10], estimation using analogy such a

independent which makes it very popular on internet. Web services are composed of following platform elements, SOAP(simple object access protocol), UDDI(universal description, discovery and information) and WSDL(web services description language). We

Dec 27, 2013 - homotopy groups, and the image subgroups satisfy ...... must have infinite cup-lengthâand hence X cannot be a rational co-H space. On.

Katholieke Universiteit Leuven, Dept. of Computer Science, Celestijnenlaan 200A, B-3001 Leuven, Belgium ... Cross-validation is a useful and generally ap- ... tâ := optimal test(T). P := partition induced on T by tâ if stop criterion(P) then retu

quence yields the highest cumulative probability. By combining a stack decoder search with a breadth- ... the relative likelihood that each choice is the one which should be selected. 2.1 What is a Decision Tree? .... cal estimates, i.e. relative-fre

Jan 9, 2013 - is suited for signals where each locus can be affected by distinct consecutive aberrations (e.g. several consecutive point .... shown in several studies that few subclones acquire an evolutionary advantage and outgrow the other subclone

We propose to add specific noise to the numeric attributes after exploring the decision tree of the original data. The obfuscated data then is presented to the second party for decision tree analysis. The decision tree obtained on the original data a

Dec 6, 2017 - Tree shifts were introduced by Aubrun and BÃ©al [1â5] as interesting objects of study, since they are more complicated than one-dimensional subshifts while preserving some directionality, but perhaps not so hard to analyze as multidim

IJCSI International Journal of Computer Science Issues, Volume 12, Issue 5, September 2015 ... department at Taibah University (TU), Al-Madinah Al-.

Nov 4, 2016 - analysis shows that this algorithm can learn a near optimal decision tree, since it can find the best ... In recent years, with the emergence of very big training data (which cannot be held in one single ... (1993)], which require the t

rganizations in the modern business world collect ... and Engineering, National Institute of Technology Warangal A.P. ..... He then obtained his Master of.

All available attributes are shown in Table II. The âSIdâ attribute, is included, here, in order to help the advisor in determining which academic plan of study was followed by ... course . - is the weight of the gained grade of a course . IJCSI

Oct 20, 2001 - NIMIA-SC2001 - 2001 NATO Advanced Study Institute on Neural Networks for Instrumentation, Measurement .... Then we discuss in detail a training procedure known as a Pocket Algorithm and shortly a Ther- ...... of EEG Data Room in Sudden