2,899 research outputs found
On the Impact of Forgetting on Learning Machines
People tend not to have perfect memories when it comes to learning, or to anything else for that matter. Most formal studies of learning, however, assume a perfect memory. Some approaches have restricted the number of items that could be retained. We introduce a complexity theoretic accounting of memory utilization by learning machines. In our new model, memory is measured in bits as a function of the size of the input. There is a hierarchy of learnability based on increasing memory allotment. The lower bound results are proved using an unusual combination of pumping and mutual recursion theorem arguments. For technical reasons, it was necessary to consider two types of memory: long and short term
Stellar Populations in the Phoenix Dwarf (dIrr/dSph) Galaxy as Observed by HST/WFPC2
We present HST/WFPC2 photometry of the central regions of the Phoenix dwarf.
Accurate photometry allows us to: 1) confirm the existence of the horizontal
branch previously detected by ground-based observations, and use it to
determine a distance to Phoenix, 2) clearly detect the existence of multiple
ages in the stellar population of Phoenix, 3) determine a mean metallicity of
the old red giant branch stars in Phoenix, and suggest that Phoenix has evolved
chemically over its lifetime, 4) extract a rough star formation history for the
central regions which suggests that Phoenix has been forming stars roughly
continuously over its entire lifetime.Comment: Accepted by AJ, 22 pages including 6 figures + 1 figure in JPEG
forma
Transitioning from Transmedia to Transreality Storyboarding to Improve the Co-Creation of the Experience Space
Transmedia storytelling is a digital based marketing approach in present day consumer markets. Typically applied to spanning or segueing stories or experiences across media such as film, books, comics and video-games to reach broader target audiences, often triggering a narrative, into which customers can participate and co-create the narrative. Common aims at customer engagement have been through shared stories on present day social media. However, for the creative-consumer, sharing on social media falls short of fully immersive storytelling ecology. Creatives (traditional designers and consumers) would benefit through tools and processes for incrementally expanding dimensions, mediums, fidelity, and shared interactions and senses across multiple media and interactive realities. This paper presents use cases of Transreality Storyboarding Framework (TSF), a design framework that affords creation of experience spaces for consumer-product engagement. Further, we propose a TSF app, to allow non-expert designers/everyday-consumers to contribute to storytelling, participation and production of product experience spaces
Fast state-space methods for inferring dendritic synaptic connectivity
We present fast methods for filtering voltage measurements and performing optimal inference of the location and strength of synaptic connections in large dendritic trees. Given noisy, subsampled voltage observations we develop fast l[subscript 1]-penalized regression methods for Kalman state-space models of the neuron voltage dynamics. The value of the l[subscript 1]-penalty parameter is chosen using cross-validation or, for low signal-to-noise ratio, a Mallows’ C[subscript p]-like criterion. Using low-rank approximations, we reduce the inference runtime from cubic to linear in the number of dendritic compartments. We also present an alternative, fully Bayesian approach to the inference problem using a spike-and-slab prior. We illustrate our results with simulations on toy and real neuronal geometries. We consider observation schemes that either scan the dendritic geometry uniformly or measure linear combinations of voltages across several locations with random coefficients. For the latter, we show how to choose the coefficients to offset the correlation between successive measurements imposed by the neuron dynamics. This results in a “compressed sensing” observation scheme, with an important reduction in the number of measurements required to infer the synaptic weights.National Science Foundation (U.S.) (CAREER Grant)McKnight Foundation (Scholar Award)National Science Foundation (U.S.) (Grant IIS-0904353)Columbia College. Rabi Scholars Progra
Speech and language therapy versus placebo or no intervention for speech problems in Parkinson's disease
Parkinson's disease patients commonly suffer from speech and vocal problems including dysarthric speech, reduced loudness and loss of articulation. These symptoms increase in frequency and intensity with progression of the disease). Speech and language therapy (SLT) aims to improve the intelligibility of speech with behavioural treatment techniques or instrumental aids
Two-axis magnetic field sensor
A ferromagnetic thin-film based magnetic field sensor with first and second sensitive direction sensing structures each having a nonmagnetic intermediate layer with two major surfaces on opposite sides thereof having a magnetization reference layer on one and an anisotropic ferromagnetic material sensing layer on the other having a length in a selected length direction and a smaller width perpendicular thereto and parallel to the relatively fixed magnetization direction. The relatively fixed magnetization direction of said magnetization reference layer in each is oriented in substantially parallel to the substrate but substantially perpendicular to that of the other. An annealing process is used to form the desired magnetization directions
The World as an Interface: Exploring the Ethical Challenges of the Emerging Metaverse
Mixed reality is emerging as the next phase of personal computing. Once Apple Glass is released augmented and mixed reality will go mainstream and the impact on our behaviour will be as dramatic as when the iPhone was released. In parallel, what used to be 2D webpages are becoming 3D worlds, collectively forming a meta universe of virtual or mixed reality domains -the ‘Metaverse’. Mixed reality is precisely where the best affordances of the digital and analogue worlds should work together to create entirely new interactive learning, social and economic opportunities. In this paper we reflect on how the physical world will itself become an interface making reality even more machine-readable, click-able, and searchable. We further propose how society will need to ensure that the appropriate boundary management is in place to allow us as co-creators of the metaverse to protect our ethical rights of privacy, integrity, and autonomy
Learning via Queries with Teams and Anomalies
Most work in the field of inductive inference regards the learning machine to be a passive recipient of data. In a prior paper the passive approach was compared to an active form of learning where the machine is allowed to ask questions. In this paper we continue the study of machines that ask questions by comparing such machines to teams of passive machines. This yields, via work of Pitt and Smith, a comparison of active learning with probabilistic learning. Also considered are query inference machines that learn an approximation of what is desired. The approximation differs from the desired result in finitely many anomalous places
Clustering in 18O - absolute determination of branching ratios via high-resolution particle spectroscopy
The determination of absolute branching ratios for high-energy states in light nuclei is an important and useful tool for probing the underlying nuclear structure of individual resonances: for example, in establishing the tendency of an excited state towards
α
-cluster structure. Difficulty arises in measuring these branching ratios due to similarities in available decay channels, such as (
18
O,
n
) and (
18
O,
2
n
), as well as differences in geometric efficiencies due to population of bound excited levels in daughter nuclei. Methods are presented using Monte Carlo techniques to overcome these issues
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