1,353 research outputs found
Marriage record of Boaz, George R. and Messenger, Carrie M.
No full textMarriage license for George R. Boaz and Carrie M. Messenger. R.H. Barnett was the officiant
Keep That Card in Mind: Card Guessing with Limited Memory
No full textA card guessing game is played between two players, Guesser and Dealer. At the beginning of the game, the Dealer holds a deck of n cards (labeled 1, ..., n). For n turns, the Dealer draws a card from the deck, the Guesser guesses which card was drawn, and then the card is discarded from the deck. The Guesser receives a point for each correctly guessed card.
With perfect memory, a Guesser can keep track of all cards that were played so far and pick at random a card that has not appeared so far, yielding in expectation ln n correct guesses, regardless of how the Dealer arranges the deck. With no memory, the best a Guesser can do will result in a single guess in expectation.
We consider the case of a memory bounded Guesser that has m < n memory bits. We show that the performance of such a memory bounded Guesser depends much on the behavior of the Dealer. In more detail, we show that there is a gap between the static case, where the Dealer draws cards from a properly shuffled deck or a prearranged one, and the adaptive case, where the Dealer draws cards thoughtfully, in an adversarial manner. Specifically:
1) We show a Guesser with O(log² n) memory bits that scores a near optimal result against any static Dealer.
2) We show that no Guesser with m bits of memory can score better than O(√m) correct guesses against a random Dealer, thus, no Guesser can score better than min {√m, ln n}, i.e., the above Guesser is optimal.
3) We show an efficient adaptive Dealer against which no Guesser with m memory bits can make more than ln m + 2 ln log n + O(1) correct guesses in expectation.
These results are (almost) tight, and we prove them using compression arguments that harness the guessing strategy for encoding
Supplemental material for Differences in Working Memory Capacity Affect Online Spoken Word Recognition: Evidence From Eye Movements
No full textSupplemental Material for Differences in Working Memory Capacity Affect Online Spoken Word Recognition: Evidence From Eye Movements by Gal Nitsan, Arthur Wingfield, Limor Lavie and Boaz M Ben-David in Trends in Hearing</p
Classical Algorithms and Quantum Limitations for Maximum Cut on High-Girth Graphs
No full textWe study the performance of local quantum algorithms such as the Quantum Approximate Optimization Algorithm (QAOA) for the maximum cut problem, and their relationship to that of randomized classical algorithms.
1) We prove that every (quantum or classical) one-local algorithm (where the value of a vertex only depends on its and its neighbors' state) achieves on D-regular graphs of girth > 5 a maximum cut of at most 1/2 + C/√D for C = 1/√2 ≈ 0.7071. This is the first such result showing that one-local algorithms achieve a value that is bounded away from the true optimum for random graphs, which is 1/2 + P_*/√D + o(1/√D) for P_* ≈ 0.7632 [Dembo et al., 2017].
2) We show that there is a classical k-local algorithm that achieves a value of 1/2 + C/√D - O(1/√k) for D-regular graphs of girth > 2k+1, where C = 2/π ≈ 0.6366. This is an algorithmic version of the existential bound of [Lyons, 2017] and is related to the algorithm of [Aizenman et al., 1987] (ALR) for the Sherrington-Kirkpatrick model. This bound is better than that achieved by the one-local and two-local versions of QAOA on high-girth graphs [M. B. Hastings, 2019; Marwaha, 2021].
3) Through computational experiments, we give evidence that the ALR algorithm achieves better performance than constant-locality QAOA for random D-regular graphs, as well as other natural instances, including graphs that do have short cycles.
While our theoretical bounds require the locality and girth assumptions, our experimental work suggests that it could be possible to extend them beyond these constraints. This points at the tantalizing possibility that O(1)-local quantum maximum-cut algorithms might be pointwise dominated by polynomial-time classical algorithms, in the sense that there is a classical algorithm outputting cuts of equal or better quality on every possible instance. This is in contrast to the evidence that polynomial-time algorithms cannot simulate the probability distributions induced by local quantum algorithms
Public Participation in Health Care: Exploring the Co-Production of Knowledge
No full textThis eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contac
sj-docx-1-pss-10.1177_09567976211042008 – Supplemental material for Safe and Sound: The Effects of Experimentally Priming the Sense of Attachment Security on Pure-Tone Audiometric Thresholds Among Young and Older Adults
No full textSupplemental material, sj-docx-1-pss-10.1177_09567976211042008 for Safe and Sound: The Effects of Experimentally Priming the Sense of Attachment Security on Pure-Tone Audiometric Thresholds Among Young and Older Adults by Shir Nagar, Mario Mikulincer, Gal Nitsan and Boaz M. Ben-David in Psychological Science</p
Supplemental Material - COVID-19 Booster Vaccination Bellwethers: Factors Predictive of Older Adults’ Adoption of the Second Booster COVID-19 Vaccine in Israel: A Longitudinal Study
No full textSupplemental Material for COVID-19 Booster Vaccination Bellwethers: Factors Predictive of Older Adults’ Adoption of the Second Booster COVID-19 Vaccine in Israel: A Longitudinal Study by Bernadette Boaz M. Ben-David, Shoshi Keisari, Tali Regev, and Yuval Palgi in Journal of Applied Gerontology</p
Enhancing the evidence base for health impact assessment
No full textHealth impact assessment differs from other purposes for which evidence is collated in a number of ways, including:the focus on complex interventions or policy and their diverse effects on determinants of health;the need for evidence on the reversibility of adverse factors damaging to health;the diversity of the evidence in terms of relevant disciplines, study designs, quality criteria and sources of information;the broad range of stakeholders involved;the short timescale and limited resources generally available;the pragmatic need to inform decision makers regardless of the quality of the evidence.These have implications for commissioning and conducting reviews. Methods must be developed to: facilitate comprehensive searching across a broad range of disciplines and information sources; collate appropriate quality criteria to assess a range of study designs; synthesise different kinds of evidence; and facilitate timely stakeholder involvement. Good practice standards for reviews are needed to reduce the risk of poor quality recommendations. Advice to decision makers must make explicit limitations resulting from absent, conflicting, or poor quality evidence
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