Sparse, noisy Boolean functions

نویسندگان

  • Sach Mukherjee
  • Terence P. Speed
چکیده

This paper addresses the question of making inferences regarding Boolean functions under conditions of (i) noise, or stochastic variation in observed data, and (ii) sparsity, by which we mean that the number of inputs or predictors far exceeds the arity of the underlying Boolean function. We put forward a simple probability model for such observations, and discuss model selection, parameter estimation and prediction. We present results on synthetic data and on a proteomic dataset from a study in cancer systems biology.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Sparse combinatorial inference with an application in cancer biology

MOTIVATION Combinatorial effects, in which several variables jointly influence an output or response, play an important role in biological systems. In many settings, Boolean functions provide a natural way to describe such influences. However, biochemical data using which we may wish to characterize such influences are usually subject to much variability. Furthermore, in high-throughput biologi...

متن کامل

2 Learning Monotone Boolean Functions

Last time we finished the discussion about KM algorithm and its application. We also covered sparse Fourier representations and k-juntas of parities. In the end we started to talk about learning monotone Boolean functions and influence of such functions. Today We will first finish discussion about learning monotone Boolean functions. Then we will also talk about learning k-juntas of halfspaces....

متن کامل

Learning Sparse Polynomial Functions

We study the question of learning a sparse multivariate polynomial over the real domain. In particular, for some unknown polynomial f(~x) of degree-d and k monomials, we show how to reconstruct f , within error , given only a set of examples x̄i drawn uniformly from the n-dimensional cube (or an n-dimensional Gaussian distribution), together with evaluations f(x̄i) on them. The result holds even ...

متن کامل

Low degree almost Boolean functions are sparse juntas

Nisan and Szegedy showed that low degree Boolean functions are juntas. Kindler and Safra showed that low degree functions which are almost Boolean are close to juntas. Their result holds with respect to μp for every constant p. When p is allowed to be very small, new phenomena emerge. For example, the function y1 + · · · + yε/p (where yi ∈ {0, 1}) is close to Boolean but not close to a junta. W...

متن کامل

Recursive Decomposition of Sparse Incompletely-Specified Functions

A sparse function is one with only a few onset and offset minterms, compared to the entire input space. The paper examines effective use of the don’t cares to synthesize a small logic network. An algorithm is proposed, implemented and tested on known functions where only a small sample of care minterms is given. The algorithm is top-down recursive looking for decompositions based on two-input B...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007