ar X iv : 0 81 0 . 23 11 v 1 [ cs . A I ] 1 3 O ct 2 00 8 Non - Negative Matrix Factorization , Convexity and Isometry ∗

نویسندگان

  • Nikolaos Vasiloglou
  • Alexander G. Gray
  • David V. Anderson
چکیده

In this paper we explore avenues for improving the reliability of dimensionality reduction methods such as Non-Negative Matrix Factorization (NMF) as interpretive exploratory data analysis tools. We first explore the difficulties of the optimization problem underlying NMF, showing for the first time that non-trivial NMF solutions always exist and that the optimization problem is actually convex, by using the theory of Completely Positive Factorization. We subsequently explore four novel approaches to finding globallyoptimal NMF solutions using various ideas from convex optimization. We then develop a new method, isometric NMF (isoNMF), which preserves non-negativity while also providing an isometric embedding, simultaneously achieving two properties which are helpful for interpretation. Though it results in a more difficult optimization problem, we show experimentally that the resulting method is scalable and even achieves more compact spectra than standard NMF.

برای دانلود 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

ar X iv : 0 81 0 . 46 11 v 1 [ cs . L G ] 25 O ct 2 00 8 Learning Isometric Separation Maps ∗

Maximum Variance Unfolding (MVU) and its variants have been very successful in embedding data-manifolds in lower dimensionality spaces, often revealing the true intrinsic dimensions. In this paper we show how to also incorporate supervised class information into an MVU-like method without breaking its convexity. We call this method the Isometric Separation Map and we show that the resulting ker...

متن کامل

ar X iv : 0 71 0 . 35 19 v 1 [ cs . C C ] 1 8 O ct 2 00 7 P - matrix recognition is co - NP - complete

This is a summary of the proof by G.E. Coxson [1] that P-matrix recognition is co-NP-complete. The result follows by a reduction from the MAX CUT problem using results of S. Poljak and J. Rohn [5].

متن کامل

ar X iv : 0 81 0 . 50 56 v 1 [ cs . C C ] 2 8 O ct 2 00 8 P is not equal to NP . Sten - Åke

SAT 6∈ P is true, and provable in a simply consistent extension B of a first order theory B of computing, with a single finite axiom B characterizing a universal Turing machine. Therefore P 6 = NP is true, and provable in a simply consistent extension B of 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

برای دانلود 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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009