GREED IS GOOD: ALGORITHMIC RESULTS FOR SPARSE APPROXIMATION JOEL A. TROPP Abstract. This article presents new results on using a greedy algorithm, Orthogonal Matching Pursuit (OMP), to solve the sparse approximation problem over redundant dictionaries. It contains a single su?cient condition under ...
Mathematicians were initially interested in the dividing line between what was and what was not algorithmic. 数学们起初感兴趣的是算法的有与无的界限,然而,简单地知道问题是否有解决的算法并不完事了。 权威例句 Greed is good: algorithmic results for sparse approximation ...
Thorough numerical results are provided to support the obtained\ntheory.doi:10.1214/17-AOS1568Jianqing FanHan LiuQiang SunTong ZhangJianqing Fan, Han Liu, Qiang Sun, and Tong Zhang. TAC for sparse learning: Simultaneous control of algorithmic complexity and statistical error. arXiv preprint arXiv:...
Jaggi, M.: Revisiting Frank–Wolfe: projection-free sparse convex optimization. In: International Conference on Machine Learning, pp. 427–435 (2013) Clarkson, K.: Coresets, sparse greedy approximation, and the Frank–Wolfe algorithm. In: Symposium on Discrete Algorithms, SODA, pp. 922–931 (2...
Algorithmic Meta Theorems for Sparse Graph Classes Algorithmic meta theorems give efficient algorithms for classes of algorithmic problems, instead of just individual problems. They unify families of algori... M Grohe - Computer Science-theory & Applications: International Computer Science Symposium in Rus...
The sparse regression excluded 14 terms, giving \(r=0.7\). The parameter grids appear in SI Appendix, Fig. 10. The results in the table display the SINDy-discovered coefficients of the corresponding terms in (Eqs. 1–3). Full size image The fit between model and data for measles and ...
directed models (Markov random fields). Can be trained similarly as RBMs via MCMC (Hinton & Sejnowski, 1983). Use a variational approximation(变分近似) of the data distribution forfaster training(Salakhutdinov & Hinton, 2009). Similarly, can be used to initialize other networks for downstream ...
Fig. 4 shows our QOC results executed with our custom CPU+GPU implementation for the Morse potential (Eq. (8)), and Fig. 5 shows results for the double-well potential given by(11)V(x)=x464−x24+x3256. In both cases, the optimized electrical fields and power spectra plots are ...
These problem instances tend to have sparse undirected graphs, and have numbers of vertices and edges ranging from 50–1000 and 63–25,000, respectively. The node prizes were randomly drawn from the discrete uniform distribution U[1,10], and for each node j∈V∖{1}, the corresponding ...
Time Series Classification (TSC) involves building predictive models for a discrete target variable from ordered, real valued, attributes. Over recent year