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