University of California, Santa Cruz

About: University of California, Santa Cruz is a education organization based out in Santa Cruz, California, United States. It is known for research contribution in the topics: Galaxy & Population. The organization has 15541 authors who have published 44120 publications receiving 2759983 citations. The organization is also known as: UCSC & UC, Santa Cruz.

Decision theoretic generalizations of the PAC model for neural net and other learning applications

Abstract: We describe a generalization of the PAC learning model that is based on statistical decision theory. In this model the learner receives randomly drawn examples, each example consisting of an instance x in X and an outcome y in Y , and tries to find a hypothesis h : X --< A , where h in H , that specifies the appropriate action a in A to take for each instance x , in order to minimize the expectation of a loss l(y,a). Here X, Y, and A are arbitrary sets, l is a real-valued function, and examples are generated according to an arbitrary joint distribution on X times Y . Special cases include the problem of learning a function from X into Y , the problem of learning the conditional probability distribution on Y given X (regression), and the problem of learning a distribution on X (density estimation). We give theorems on the uniform convergence of empirical loss estimates to true expected loss rates for certain hypothesis spaces H , and show how this implies learnability with bounded sample size, disregarding computational complexity. As an application, we give distribution-independent upper bounds on the sample size needed for learning with feedforward neural networks. Our theorems use a generalized notion of VC dimension that applies to classes of real-valued functions, adapted from Pollard''s work, and a notion of *capacity* and *metric dimension* for classes of functions that map into a bounded metric space. (Supersedes 89-30 and 90-52.) [Also in "Information and Computation", Vol. 100, No.1, September 1992]

The Oxford Nanopore MinION: delivery of nanopore sequencing to the genomics community

Abstract: Nanopore DNA strand sequencing has emerged as a competitive, portable technology. Reads exceeding 150 kilobases have been achieved, as have in-field detection and analysis of clinical pathogens. We summarize key technical features of the Oxford Nanopore MinION, the dominant platform currently available. We then discuss pioneering applications executed by the genomics community.

A high-resolution map of human evolutionary constraint using 29 mammals.

Abstract: The comparison of related genomes has emerged as a powerful lens for genome interpretation. Here we report the sequencing and comparative analysis of 29 eutherian genomes. We confirm that at least 5.5% of the human genome has undergone purifying selection, and locate constrained elements covering ∼4.2% of the genome. We use evolutionary signatures and comparisons with experimental data sets to suggest candidate functions for ∼60% of constrained bases. These elements reveal a small number of new coding exons, candidate stop codon readthrough events and over 10,000 regions of overlapping synonymous constraint within protein-coding exons. We find 220 candidate RNA structural families, and nearly a million elements overlapping potential promoter, enhancer and insulator regions. We report specific amino acid residues that have undergone positive selection, 280,000 non-coding elements exapted from mobile elements and more than 1,000 primate- and human-accelerated elements. Overlap with disease-associated variants indicates that our findings will be relevant for studies of human biology, health and disease.

Electromagnetic counterparts of compact object mergers powered by the radioactive decay of r‐process nuclei

Abstract: The most promising astrophysical sources of kHz gravitational waves (GWs) are the inspiral and merger of binary neutron star(NS)/black hole systems. Maximizing the scientific return of a GW detection will require identifying a coincident electromagnetic (EM) counterpart. One of the most likely sources of isotropic EM emission from compact object mergers is a supernova-like transient powered by the radioactive decay of heavy elements synthesized in ejecta from the merger. We present the first calculations of the optical transients from compact object mergers that self-consistently determine the radioactive heating by means of a nuclear reaction network; using this heating rate, we model the light curve with a one-dimensional Monte Carlo radiation transfer calculation. For an ejecta mass ~ 10 -2 M ⊙ (10 -3 M ⊙ ) the resulting light-curve peaks on a time-scale ~1 d at a V-band luminosity vL v ~ 3 x 10 41 (10 41 )erg s -1 [M V = -15(-14)]; this corresponds to an effective 'f' parameter ~3 × 10- 6 in the Li-Paczynski toy model. We argue that these results are relatively insensitive to uncertainties in the relevant nuclear physics and to the precise early-time dynamics and ejecta composition. Since NS merger transients peak at a luminosity that is a factor of ~10 3 higher than a typical nova, we propose naming these events 'kilo-novae'. Because of the rapid evolution and low luminosity of NS merger transients, EM counterpart searches triggered by GW detections will require close collaboration between the GW and astronomical communities. NS merger transients may also be detectable following a short-duration gamma-ray burst or 'blindly' with present or upcoming optical transient surveys. Because the emission produced by NS merger ejecta is powered by the formation of rare r-process elements, current optical transient surveys can directly constrain the unknown origin of the heaviest elements in the Universe.