On the Prior Sensitivity of Thompson Sampling

The empirically successful Thompson Sampling algorithm for stochastic bandits has drawn much interest in understanding its theoretical properties. One important benefit of the algorithm is that it allows domain knowledge to be conveniently encoded as a prior distribution to balance exploration and exploitation more effectively. While it is generally believed that the algorithm's regret is low (high) when the prior is good (bad), little is known about the exact dependence. In this paper, we fully characterize the algorithm's worst-case dependence of regret on the choice of prior, focusing on a special yet representative case. These results also provide insights into the general sensitivity of the algorithm to the choice of priors. In particular, with $p$ being the prior probability mass of the true reward-generating model, we prove $O(\sqrt{T/p})$ and $O(\sqrt{(1-p)T})$ regret upper bounds for the bad- and good-prior cases, respectively, as well as \emph{matching} lower bounds. Our proofs rely on the discovery of a fundamental property of Thompson Sampling and make heavy use of martingale theory, both of which appear novel in the literature, to the best of our knowledge.Comment: Appears in the 27th International Conference on Algorithmic Learning Theory (ALT), 201

Aggression, Social Stress, and the Immune System in Humans and Animal Models

Social stress can lead to the development of psychological problems ranging from exaggerated anxiety and depression to antisocial and violence-related behaviors. Increasing evidence suggests that the immune system is involved in responses to social stress in adulthood. For example, human studies show that individuals with high aggression traits display heightened inflammatory cytokine levels and dysregulated immune responses such as slower wound healing. Similar findings have been observed in patients with depression, and comorbidity of depression and aggression was correlated with stronger immune dysregulation. Therefore, dysregulation of the immune system may be one of the mediators of social stress that produces aggression and/or depression. Similar to humans, aggressive animals also show increased levels of several proinflammatory cytokines, however, unlike humans these animals are more protected from infectious organisms and have faster wound healing than animals with low aggression. On the other hand, subordinate animals that receive repeated social defeat stress have been shown to develop escalated and dysregulated immune responses such as glucocorticoid insensitivity in monocytes. In this review we synthesize the current evidence in humans, non-human primates, and rodents to show a role for the immune system in responses to social stress leading to psychiatric problems such as aggression or depression. We argue that while depression and aggression represent two fundamentally different behavioral and physiological responses to social stress, it is possible that some overlapped, as well as distinct, pattern of immune signaling may underlie both of them. We also argue the necessity of studying animal models of maladaptive aggression induced by social stress (i.e., social isolation) for understanding neuro-immune mechanism of aggression, which may be relevant to human aggression

Simulation-based reachability analysis for nonlinear systems using componentwise contraction properties

A shortcoming of existing reachability approaches for nonlinear systems is the poor scalability with the number of continuous state variables. To mitigate this problem we present a simulation-based approach where we first sample a number of trajectories of the system and next establish bounds on the convergence or divergence between the samples and neighboring trajectories. We compute these bounds using contraction theory and reduce the conservatism by partitioning the state vector into several components and analyzing contraction properties separately in each direction. Among other benefits this allows us to analyze the effect of constant but uncertain parameters by treating them as state variables and partitioning them into a separate direction. We next present a numerical procedure to search for weighted norms that yield a prescribed contraction rate, which can be incorporated in the reachability algorithm to adjust the weights to minimize the growth of the reachable set

Components in time-varying graphs

Real complex systems are inherently time-varying. Thanks to new communication systems and novel technologies, it is today possible to produce and analyze social and biological networks with detailed information on the time of occurrence and duration of each link. However, standard graph metrics introduced so far in complex network theory are mainly suited for static graphs, i.e., graphs in which the links do not change over time, or graphs built from time-varying systems by aggregating all the links as if they were concurrent in time. In this paper, we extend the notion of connectedness, and the definitions of node and graph components, to the case of time-varying graphs, which are represented as time-ordered sequences of graphs defined over a fixed set of nodes. We show that the problem of finding strongly connected components in a time-varying graph can be mapped into the problem of discovering the maximal-cliques in an opportunely constructed static graph, which we name the affine graph. It is therefore an NP-complete problem. As a practical example, we have performed a temporal component analysis of time-varying graphs constructed from three data sets of human interactions. The results show that taking time into account in the definition of graph components allows to capture important features of real systems. In particular, we observe a large variability in the size of node temporal in- and out-components. This is due to intrinsic fluctuations in the activity patterns of individuals, which cannot be detected by static graph analysis.Comment: 12 pages, 4 figures, 3 table

Electrical and structural properties of In-implanted Si1−xGex alloys

We report on the effects of dopant concentration and substrate stoichiometry on the electrical and structural properties of In-implanted Si1−xGex alloys. Correlating the fraction of electrically active In atoms from Hall Effect measurements with the In atomic environment determined by X-ray absorption spectroscopy, we observed the transition from electrically active, substitutional In at low In concentration to electrically inactive metallic In at high In concentration. The In solid-solubility limit has been quantified and was dependent on the Si1−xGex alloy stoichiometry; the solid-solubility limit increased as the Ge fraction increased. This result was consistent with density functional theory calculations of two In atoms in a Si1−xGex supercell that demonstrated that In–In pairing was energetically favorable for x ≲ 0.7 and energetically unfavorable for x ≳ 0.7. Transmission electron microscopy imaging further complemented the results described earlier with the In concentration and Si1−xGex alloy stoichiometry dependencies readily visible. We have demonstrated that low resistivity values can be achieved with In implantation in Si1−xGex alloys, and this combination of dopant and substrate represents an effective doping protocol

Blocking Zika virus vertical transmission.

The outbreak of the Zika virus (ZIKV) has been associated with increased incidence of congenital malformations. Although recent efforts have focused on vaccine development, treatments for infected individuals are needed urgently. Sofosbuvir (SOF), an FDA-approved nucleotide analog inhibitor of the Hepatitis C (HCV) RNA-dependent RNA polymerase (RdRp) was recently shown to be protective against ZIKV both in vitro and in vivo. Here, we show that SOF protected human neural progenitor cells (NPC) and 3D neurospheres from ZIKV infection-mediated cell death and importantly restored the antiviral immune response in NPCs. In vivo, SOF treatment post-infection (p.i.) decreased viral burden in an immunodeficient mouse model. Finally, we show for the first time that acute SOF treatment of pregnant dams p.i. was well-tolerated and prevented vertical transmission of the virus to the fetus. Taken together, our data confirmed SOF-mediated sparing of human neural cell types from ZIKV-mediated cell death in vitro and reduced viral burden in vivo in animal models of chronic infection and vertical transmission, strengthening the growing body of evidence for SOF anti-ZIKV activity

Delays in Leniency Application: Is There Really a Race to the Enforcer's Door?

This paper studies cartels’ strategic behavior in delaying leniency applications, a take-up decision that has been ignored in the previous literature. Using European Commission decisions issued over a 16-year span, we show, contrary to common beliefs and the existing literature, that conspirators often apply for leniency long after a cartel collapses. We estimate hazard and probit models to study the determinants of leniency-application delays. Statistical tests find that delays are symmetrically affected by antitrust policies and macroeconomic fluctuations. Our results shed light on the design of enforcement programs against cartels and other forms of conspiracy

Cell transformation assays for prediction of carcinogenic potential: State of the science and future research needs

Copyright @ 2011 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.Cell transformation assays (CTAs) have long been proposed as in vitro methods for the identification of potential chemical carcinogens. Despite showing good correlation with rodent bioassay data, concerns over the subjective nature of using morphological criteria for identifying transformed cells and a lack of understanding of the mechanistic basis of the assays has limited their acceptance for regulatory purposes. However, recent drivers to find alternative carcinogenicity assessment methodologies, such as the Seventh Amendment to the EU Cosmetics Directive, have fuelled renewed interest in CTAs. Research is currently ongoing to improve the objectivity of the assays, reveal the underlying molecular changes leading to transformation and explore the use of novel cell types. The UK NC3Rs held an international workshop in November 2010 to review the current state of the art in this field and provide directions for future research. This paper outlines the key points highlighted at this meeting