A binary matrix factorization algorithm for protein complex prediction
نویسندگان
چکیده
منابع مشابه
Additional File 1 for “A Binary Matrix Factorization Algorithm for Protein Complex Prediction”
This file is appended with the paper titled ”A Binary Matrix Factorization Algorithm for Protein Complex Prediction” as a supplementary document. In this file, all evaluation results on 42 percentage pairs of random additions and deletions are given. Also, a theoretical analysis on the computational efficiency and performance of the proposed BYY-BMF algorithm is presented. Some parts of theoret...
متن کاملMatrix Factorization for Collaborative Prediction
Netflix, an online video rental company, recently announced a contest to spur interest in building better recommendation systems. Users of Netflix are able to rank movies on an integer scale from 1 to 5. A rating of 1 indicates that the user “hated it”, while 5 indicates they “loved it”. The objective of a recommendation system, or collaborative filter, is to provide users with new recommendati...
متن کاملMatrix factorization with binary components
Motivated by an application in computational biology, we consider low-rank matrix factorization with {0, 1}-constraints on one of the factors and optionally convex constraints on the second one. In addition to the non-convexity shared with other matrix factorization schemes, our problem is further complicated by a combinatorial constraint set of size 2m·r, where m is the dimension of the data p...
متن کاملImproved Local Search for Binary Matrix Factorization
Rank K Binary Matrix Factorization (BMF) approximates a binary matrix by the product of two binary matrices of lower rank, K, using either L1 or L2 norm. In this paper, we first show that the BMFwithL2 norm can be reformulated as an Unconstrained Binary Quadratic Programming (UBQP) problem. We then review several local search strategies that can be used to improve the BMF solutions obtained by ...
متن کاملA fast algorithm for general matrix factorization
Matrix factorization algorithms are emerging as popular tools in many applications, especially dictionary learning method for recovering biomedical image data from noisy and ill-conditioned measurements. We introduce a novel dictionary learning algorithm based on augmented Lagrangian (AL) approach to learn dictionaries from exemplar data and it can be extended to general matrix factorization pr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Proteome Science
سال: 2011
ISSN: 1477-5956
DOI: 10.1186/1477-5956-9-s1-s18