On the Convergence to a Global Solution of Shuffling-Type Gradient Algorithms

Stochastic gradient descent (SGD) algorithm is the method of choice in many machine learning tasks thanks to its scalability and efficiency in dealing with large-scale problems. In this paper, we focus on the shuffling version of SGD which matches the mainstream practical heuristics. We show the convergence to a global solution of shuffling SGD for a class of non-convex functions under over-parameterized settings. Our analysis employs more relaxed non-convex assumptions than previous literature. Nevertheless, we maintain the desired computational complexity as shuffling SGD has achieved in the general convex setting.Comment: The 37th Conference on Neural Information Processing Systems (NeurIPS 2023

Interdisciplinary eHealth for the care of people living with traumatic brain injury: A systematic review

© 2017 Taylor & Francis Group, LLC. Objective: To identify literature which discusses the barriers and enablers of eHealth technology and which evaluates its role in facilitating interdisciplinary team work for the care of people with a traumatic brain injury (TBI). Design: Systematic review. Data sources: Studies were identified by searching CINAHL, Embase, Medline, PsycINFO, Scopus, and Web of Science. Study selection: Studies included in the review were required to feature an eHealth intervention which assisted interdisciplinary care for people with TBI. Data extraction: Descriptive data for each study described the eHealth intervention, interdisciplinary team, outcomes, and barriers and facilitators in implementing eHealth interventions. Results: The search resulted in 1389 publications, of which 35 were retrieved and scanned in full. Six studies met all the inclusion criteria for the review. Four different eHealth interventions were identified: (i) an electronic goals systems, (ii) telerehabilitation, (iii) videoconferencing, and (iv) a point-of-care team-based information system. Various barriers and facilitators were identified in the use of eHealth. Conclusion: eHealth interventions have been reported to support interdisciplinary teams for the care of TBI. However, there is a substantial gap in existing literature regarding the barriers and enablers which characterize a successful interdisciplinary eHealth model for people with TBI

Multiple column high-throughput e-beam inspection (EBI)

Single-column e-beam systems are used in production for the detection of electrical defects, but are too slow to be used for the detection of small physical defects, and can't meet future inspection requirements. This paper presents a multiple-column e-beam technology for high throughput wafer inspection. Multibeam has developed all-electrostatic columns for high-resolution imaging. The elimination of magnetic coils enables the columns to be small; e-beam deflection is faster in the absence of magnetic hysteresis. Multiple miniature-columns are assembled in an array. An array of 100 columns covers the entire surface of a 300mm wafer, affording simultaneous cross-wafer sampling. Column performance simulations and system architecture are presented. Also provided are examples of high throughput, more efficient, multiple-column wafer inspection