University of California, Irvine

About: University of California, Irvine is a education organization based out in Irvine, California, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 47031 authors who have published 113602 publications receiving 5521832 citations. The organization is also known as: UC Irvine & UCI.

The impact of information systems on organizations and markets

Abstract: The adoption of information technology (IT) in organizations has been growing at a rapid pace. The use of the technology has evolved from the automation of structured processes to systems that are truly revolutionary in that they introduce change into fundamental business procedures. Indeed, it is believed that “More than being helped by computers, companies will live by them, shaping strategy and structure to fit new information technology [25].” While the importance of the relationship between information technology and organizational change is evidenced by the considerable literature on the subject,1 there is a lack of comprehensive analysis of these issues from the economic perspective. The aim of this article is to develop an economic understanding of how information systems affect some key measures of organization structure.

Planting misinformation in the human mind: A 30-year investigation of the malleability of memory

Abstract: The misinformation effect refers to the impairment in memory for the past that arises after exposure to misleading information. The phenomenon has been investigated for at least 30 years, as investigators have addressed a number of issues. These include the conditions under which people are especially susceptible to the negative impact of misinformation, and conversely when are they resistant. Warnings about the potential for misinformation sometimes work to inhibit its damaging effects, but only under limited circumstances. The misinformation effect has been observed in a variety of human and nonhuman species. And some groups of individuals are more susceptible than others. At a more theoretical level, investigators have explored the fate of the original memory traces after exposure to misinformation appears to have made them inaccessible. This review of the field ends with a brief discussion of the newer work involving misinformation that has explored the processes by which people come to believe falsely that they experienced rich complex events that never, in fact, occurred.

Nanopore analytics: sensing of single molecules

Abstract: In nanopore analytics, individual molecules pass through a single nanopore giving rise to detectable temporary blockades in ionic pore current. Reflecting its simplicity, nanopore analytics has gained popularity and can be conducted with natural protein as well as man-made polymeric and inorganic pores. The spectrum of detectable analytes ranges from nucleic acids, peptides, proteins, and biomolecular complexes to organic polymers and small molecules. Apart from being an analytical tool, nanopores have developed into a general platform technology to investigate the biophysics, physicochemistry, and chemistry of individual molecules (critical review, 310 references).

Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition

Abstract: We analyze stochastic gradient descent for optimizing non-convex functions. In many cases for non-convex functions the goal is to find a reasonable local minimum, and the main concern is that gradient updates are trapped in saddle points. In this paper we identify strict saddle property for non-convex problem that allows for efficient optimization. Using this property we show that from an arbitrary starting point, stochastic gradient descent converges to a local minimum in a polynomial number of iterations. To the best of our knowledge this is the first work that gives global convergence guarantees for stochastic gradient descent on non-convex functions with exponentially many local minima and saddle points. Our analysis can be applied to orthogonal tensor decomposition, which is widely used in learning a rich class of latent variable models. We propose a new optimization formulation for the tensor decomposition problem that has strict saddle property. As a result we get the first online algorithm for orthogonal tensor decomposition with global convergence guarantee.

Age Differences in Future Orientation and Delay Discounting

Abstract: Age differences in future orientation are examined in a sample of 935 individuals between 10 and 30 years using a delay discounting task as well as a new self-report measure. Younger adolescents consistently demonstrate a weaker orientation to the future than do individuals aged 16 and older, as reflected in their greater willingness to accept a smaller reward delivered sooner than a larger one that is delayed, and in their characterizations of themselves as less concerned about the future and less likely to anticipate the consequences of their decisions. Planning ahead, in contrast, continues to develop into young adulthood. Future studies should distinguish between future orientation and impulse control, which may have different neural underpinnings and follow different developmental timetables.