434 research outputs found
Model Extraction Warning in MLaaS Paradigm
Cloud vendors are increasingly offering machine learning services as part of
their platform and services portfolios. These services enable the deployment of
machine learning models on the cloud that are offered on a pay-per-query basis
to application developers and end users. However recent work has shown that the
hosted models are susceptible to extraction attacks. Adversaries may launch
queries to steal the model and compromise future query payments or privacy of
the training data. In this work, we present a cloud-based extraction monitor
that can quantify the extraction status of models by observing the query and
response streams of both individual and colluding adversarial users. We present
a novel technique that uses information gain to measure the model learning rate
by users with increasing number of queries. Additionally, we present an
alternate technique that maintains intelligent query summaries to measure the
learning rate relative to the coverage of the input feature space in the
presence of collusion. Both these approaches have low computational overhead
and can easily be offered as services to model owners to warn them of possible
extraction attacks from adversaries. We present performance results for these
approaches for decision tree models deployed on BigML MLaaS platform, using
open source datasets and different adversarial attack strategies
L'CO/LFIR Relations with CO Rotational Ladders of Galaxies Across the Herschel SPIRE Archive
We present a catalog of all CO (J=4-3 through J=13-12)), [CI], [NII] lines
available from extragalactic spectra from the Herschel SPIRE Fourier Transform
Spectrometer (FTS) archive combined with observations of the low-J CO lines
from the literature and from the Arizona Radio Observatory. This work examines
the relationships between LFIR, L'CO, and LCO/LCO(1-0). We also present a new
method for estimating probability distribution functions (PDFs) from marginal
signal-to-noise ratio Herschel} FTS spectra, which takes into account the
instrumental "ringing" and the resulting highly correlated nature of the
spectra. The slopes of log(LFIR) vs. log(L'CO) are linear for all mid- to
high-J CO lines and slightly sublinear if restricted to (U)LIRGs. The mid- to
high-J CO luminosity relative to CO J=1-0 increases with increasing LFIR,
indicating higher excitement of the molecular gas, though these ratios do not
exceed ~ 180. For a given bin in LFIR, the luminosities relative to CO J=1-0
remain relatively flat from J=6-5 through J=13-12, across three orders of
magnitude of LFIR. A single component theoretical photon-dominated region (PDR)
model cannot match these flat SLED shapes, though combinations of PDR models
with mechanical heating added qualitatively match the shapes, indicating the
need for further comprehensive modeling of the excitation processes of warm
molecular gas in nearby galaxies.Comment: 17 pages, 4 figures (including appendix), accepted by ApJ. Full
tables will be in VizieR upon publication, email first author for tables in
the meantim
BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs
Foundation models (FMs) are able to leverage large volumes of unlabeled data
to demonstrate superior performance across a wide range of tasks. However, FMs
developed for biomedical domains have largely remained unimodal, i.e.,
independently trained and used for tasks on protein sequences alone, small
molecule structures alone, or clinical data alone. To overcome this limitation
of biomedical FMs, we present BioBridge, a novel parameter-efficient learning
framework, to bridge independently trained unimodal FMs to establish multimodal
behavior. BioBridge achieves it by utilizing Knowledge Graphs (KG) to learn
transformations between one unimodal FM and another without fine-tuning any
underlying unimodal FMs. Our empirical results demonstrate that BioBridge can
beat the best baseline KG embedding methods (on average by around 76.3%) in
cross-modal retrieval tasks. We also identify BioBridge demonstrates
out-of-domain generalization ability by extrapolating to unseen modalities or
relations. Additionally, we also show that BioBridge presents itself as a
general purpose retriever that can aid biomedical multimodal question answering
as well as enhance the guided generation of novel drugs
Mid-J CO Emission in Nearby Seyfert Galaxies
We study for the first time the complete sub-millimeter spectra (450 GHz to
1550 GHz) of a sample of nearby active galaxies observed with the SPIRE Fourier
Transform Spectrometer (SPIRE/FTS) onboard Herschel. The CO ladder (from Jup =
4 to 12) is the most prominent spectral feature in this range. These CO lines
probe warm molecular gas that can be heated by ultraviolet photons, shocks, or
X-rays originated in the active galactic nucleus or in young star-forming
regions. In these proceedings we investigate the physical origin of the CO
emission using the averaged CO spectral line energy distribution (SLED) of six
Seyfert galaxies. We use a radiative transfer model assuming an isothermal
homogeneous medium to estimate the molecular gas conditions. We also compare
this CO SLED with the predictions of photon and X-ray dominated region (PDR and
XDR) models.Comment: Proceedings of the Torus Workshop 2012 held at the University of
Texas at San Antonio, 5-7 December 2012. C. Packham, R. Mason, and A.
Alonso-Herrero (eds.); 6 pages, 3 figure
MMTF: The Maryland-Magellan Tunable Filter
This paper describes the Maryland-Magellan Tunable Filter (MMTF) on the
Magellan-Baade 6.5-meter telescope. MMTF is based on a 150-mm clear aperture
Fabry-Perot (FP) etalon that operates in low orders and provides transmission
bandpass and central wavelength adjustable from ~5 to ~15 A and from ~5000 to
over ~9200 A, respectively. It is installed in the Inamori Magellan Areal
Camera and Spectrograph (IMACS) and delivers an image quality of ~0.5" over a
field of view of 27' in diameter (monochromatic over ~10'). This versatile and
easy-to-operate instrument has been used over the past three years for a wide
variety of projects. This paper first reviews the basic principles of FP
tunable filters, then provides a detailed description of the hardware and
software associated with MMTF and the techniques developed to observe with this
instrument and reduce the data. The main lessons learned in the course of the
commissioning and implementation of MMTF are highlighted next, before
concluding with a brief outlook on the future of MMTF and of similar facilities
which are soon coming on line.Comment: 38 pages, 12 figures, 3 tables, now accepted for publication to the
Astronomical Journa
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