C ompetition for the cytoplasmic tail of an integrin allows cells to read different matrix densities, say Millon-Frémillon et al. The tail region of β1 integrin is tiny—only 47 amino acids long. That doesn’t leave much room for the binding of cytoplasmic accessory proteins that help control the integrin’s activation state. When talin holds this position, it fl ips open integrin as a fi rst step...

Coordinate descent algorithms solve optimization problems by successively performing approximate minimization along coordinate directions or coordinate hyperplanes. They have been used in applications for many years, and their popularity continues to grow because of their usefulness in data analysis, machine learning, and other areas of current interest. This paper describes the fundamentals of...

Background: Genome sequences and genome annotation data have become available at ever increasing rates in response to the rapid progress in sequencing technologies. As a consequence the demand for methods supporting comparative, evolutionary analysis is also growing. In particular, efficient tools to visualize -omics data simultaneously for multiple species are sorely lacking. A first and cruci...

In this paper we study the problem of learning the gradient function with application to variable selection and determining variable covariation. Firstly, we propose a novel unifying framework for coordinate gradient learning from the perspective of multi-task learning. Various variable selection algorithms can be regarded as special instances of this framework. Secondly, we formulate the dual ...

Coordinate metrology generates important software issues. After measurement data are collected in the form of position vectors, the data analysis software must derive the necessary information from the set of points. Uncertainty is an important issue in this data analysis. When extreme fit approaches are employed for form error evaluation, the uncertainty is closely related to the sampling of m...

In this paper we present a novel randomized block coordinate descent method for the minimization of a convex composite objective function. The method uses (approximate) partial second-order (curvature) information, so that the algorithm performance is more robust when applied to highly nonseparable or ill conditioned problems. We call the method Robust Coordinate Descent (RCD). At each iteratio...

This paper derives equations for generalized Lorentz coordinate transformation based on a simple principle that only the wave equation must be form invariant and valid in both coordinate systems. The usual requirement that the speed of light is a universal constant and thus has an identical value in any inertial coordinate systems is removed. This leads to some interesting conclusions and possi...

Kandogan introduced the concept of star coordinate projection in 2000 [1]. To illustrate the idea behind 2DSCP, consider an example data point of dimension 8 given by 0.98]. 0.95 0.06 0.869 0.01 0.43 37 . 0 [ = A The dimensional anchors for 2DSCP are shown in Fig. 1. The dimensional anchors multiplied by the dimension values for data point ‘A’ are shown in Fig. 2. As shown in Fig. 2, each...

We propose a new selection rule for the coordinate selection in coordinate descent methods for huge-scale optimization. The efficiency of this novel scheme is provably better than the efficiency of uniformly random selection, and can reach the efficiency of steepest coordinate descent (SCD), enabling an acceleration of a factor of up to n, the number of coordinates. In many practical applicatio...

We propose a novel stochastic gradient method—semi-stochastic coordinate descent (S2CD)— for the problem of minimizing a strongly convex function represented as the average of a large number of smooth convex functions: f(x) = 1 n ∑ i fi(x). Our method first performs a deterministic step (computation of the gradient of f at the starting point), followed by a large number of stochastic steps. The...