News Recommender Systems with Feedback

The focus of present research is widely used news recommendation techniques such as “most popular” or “most e-mailed”. In this paper we have introduced an alternative way of recommendation based on feedback. Various notable properties of the feedback based recommendation technique have been also discussed. Through simulation model we show that the recommendation technique used in the present research allows implementers to have a flexibility to make a balance between accuracy and distortion. Analytical results have been established in a special case of two articles using the formulation based on generalized urn models. Finally, we show that news recommender systems can be also studied through two armed bandit algorithms

Analysis of Probabilistic News Recommender Systems

The focus of this research is the N “most popular” (Top-N) news recommender systems (NRS), widely used by media sites (e.g. New York Times, BBC, Wall Street Journal all prominently use this). This common recommendation process is known to have major limitations in terms of creating artificial amplification in the counts of recommended articles and that it is easily susceptible to manipulation. To address these issues, probabilistic NRS has been introduced. One drawback of the probabilistic recommendations is that it potentially chooses articles to recommend that might not be in the current “best” list. However, the probabilistic selection of news articles is highly robust towards common manipulation strategies. This paper compares the two variants of NRS (Top-N and probabilistic) based on (1) accuracy loss (2) distortion in counts of articles due to NRS and (3) comparison of probabilistic NRS with an adapted influence limiter heuristic

Propagating Knowledge Updates to LMs Through Distillation

Modern language models have the capacity to store and use immense amounts of knowledge about real-world entities, but it remains unclear how to update such knowledge stored in model parameters. While prior methods for updating knowledge in LMs successfully inject atomic facts, updated LMs fail to make inferences based on injected facts. In this work, we demonstrate that a context distillation-based approach can both impart knowledge about entities and propagate that knowledge to enable broader inferences. Our approach consists of two stages: transfer set generation and distillation on the transfer set. We first generate a transfer set by prompting a language model to generate continuations from the entity definition. Then, we update the model parameters so that the distribution of the LM (the student) matches the distribution of the LM conditioned on the definition (the teacher) on the transfer set. Our experiments demonstrate that this approach is more effective at propagating knowledge updates than fine-tuning and other gradient-based knowledge-editing methods. Moreover, it does not compromise performance in other contexts, even when injecting the definitions of up to 150 entities at once.Comment: NeurIPS 2023 Camera Read

The crystal structure of p-azo-toluene (CH<SUB>3</SUB>-C<SUB>6</SUB>H<SUB>4</SUB>N)<SUB>2</SUB>

The crystal structure of p-azo-toluene has been determined by single crystal methods. The unit cell is monoclinic with a=12.01 &#197;, b=5.02 &#197;, c=9.32 &#197;, &#946;=90&#176;12'. The space-group is P21/a-C2h5 and there are two molecules per unit cell. Atomic positions were determined by electron density projections making use of 'trial and error' methods. Structure factors were obtained from visually estimated intensities on Weissenberg photographs taken with CuK&#945; radiation. The planar benzene rings are attached by zig-zag C-N=N-C bond with the bond distance -N=N-=1.27 &#197; and the angle N=N-C 134&#176;30'. The plane of the benzene ring makes an angle with the (ac) plane, its orientation is obtained by rotating it about the N-C bond by 10&#176;. The nearest distance between two molecules in the crystal is 3.92 &#197;

The crystal structure of magnesium acetate-tetrahydrate Mg (CH<SUB>3</SUB>COO)<SUB>2</SUB>. 4 H<SUB>2</SUB>O

This article does not have an abstract

Strategies to Reduce Radiation Exposure in Electrophysiology and Interventional Cardiology

Clinical diagnosis sometimes involves the use of medical instruments that employ ionizing radiation. However, ionizing radiation exposure is a workplace hazard that goes undetected and is detrimental to patients and staff in the catheterization laboratory. Every possible effort should be made to reduce the amount of radiation, including scattered radiation. Implementing radiation dose feedback may have a role in reducing exposure. In medicine, it is important to estimate the potential biologic effects on, and the risk to, an individual. In general, implantation of cardiac resynchronization devices is associated with one of the highest operator exposure doses due to the proximity of the operator to the radiation source. All physicians should work on the principle of as low as reasonably achievable. Methods for reducing radiation exposure must be implemented in the catheterization laboratory. In this article, we review the available tools to lower the radiation exposure dose to the operator during diagnostic, interventional, and electrophysiological cardiac procedures

Optimal Placement of Public Electric Vehicle Charging Stations Using Deep Reinforcement Learning

The placement of charging stations in areas with developing charging infrastructure is a critical component of the future success of electric vehicles (EVs). In Albany County in New York, the expected rise in the EV population requires additional charging stations to maintain a sufficient level of efficiency across the charging infrastructure. A novel application of Reinforcement Learning (RL) is able to find optimal locations for new charging stations given the predicted charging demand and current charging locations. The most important factors that influence charging demand prediction include the conterminous traffic density, EV registrations, and proximity to certain types of public buildings. The proposed RL framework can be refined and applied to cities across the world to optimize charging station placement.Comment: 25 pages with 12 figures. Shankar Padmanabhan and Aidan Petratos provided equal contributio

On merger bias and the clustering of quasars

We use the large catalogues of haloes available for the Millennium Simulation to test whether recently merged haloes exhibit stronger large-scale clustering than other haloes of the same mass. This effect could help to understand the very strong clustering of quasars at high redshift. However, we find no statistically significant excess bias for recently merged haloes over the redshift range 2 < z < 5, with the most massive haloes showing an excess of at most ~5%. We also consider galaxies extracted from a semianalytic model built on the Millennium Simulation. At fixed stellar mass, we find an excess bias of ~ 20-30% for recently merged objects, decreasing with increasing stellar mass. The fact that recently-merged galaxies are found in systematically more massive haloes than other galaxies of the same stellar mass accounts for about half of this signal, and perhaps more for high-mass galaxies. The weak merger bias of massive systems suggests that objects of merger-driven nature, such as quasars, do not cluster significantly differently than other objects of the same characteristic mass. We discuss the implications of these results for the interpretation of clustering data with respect to quasar duty cycles, visibility times, and evolution in the black hole-host mass relation.Comment: 10 pages, 9 figures. Submitted to MNRAS. Comments welcom

A tachyonic scalar field with mutually interacting components

We investigate the tachyonic cosmological potential $V(\phi)$ in two different cases of the quasi-exponential expansion of universe and discuss various forms of interaction between the two components---matter and the cosmological constant--- of the tachyonic scalar field, which leads to the viable solutions of their respective energy densities. The distinction among the interaction forms is shown to appear in the $O_{m}(x)$ diagnostic. Further, the role of the high- and low-redshift observations of the Hubble parameter is discussed to determine the proportionality constants and hence the correct form of matter--cosmological constant interaction.Comment: 14 page

Quasar Clustering from SDSS DR5: Dependences on Physical Properties

Using a homogenous sample of 38,208 quasars with a sky coverage of $4000 {\rm deg^2}$ drawn from the SDSS Data Release Five quasar catalog, we study the dependence of quasar clustering on luminosity, virial black hole mass, quasar color, and radio loudness. At $z<2.5$, quasar clustering depends weakly on luminosity and virial black hole mass, with typical uncertainty levels $\sim 10$ for the measured correlation lengths. These weak dependences are consistent with models in which substantial scatter between quasar luminosity, virial black hole mass and the host dark matter halo mass has diluted any clustering difference, where halo mass is assumed to be the relevant quantity that best correlates with clustering strength. However, the most luminous and most massive quasars are more strongly clustered (at the $\sim 2\sigma$ level) than the remainder of the sample, which we attribute to the rapid increase of the bias factor at the high-mass end of host halos. We do not observe a strong dependence of clustering strength on quasar colors within our sample. On the other hand, radio-loud quasars are more strongly clustered than are radio-quiet quasars matched in redshift and optical luminosity (or virial black hole mass), consistent with local observations of radio galaxies and radio-loud type 2 AGN. Thus radio-loud quasars reside in more massive and denser environments in the biased halo clustering picture. Using the Sheth et al.(2001) formula for the linear halo bias, the estimated host halo mass for radio-loud quasars is $\sim 10^{13} h^{-1}M_\odot$, compared to $\sim 2\times 10^{12} h^{-1}M_\odot$ for radio-quiet quasar hosts at $z\sim 1.5$.Comment: Updated version; accepted for publication in Ap