Multi-Task and Meta-Learning with Sparse Linear Bandits

Motivated by recent developments on meta-learning with linear contextual bandit tasks, we study the benefit of feature learning in both the multi-task and meta-learning settings. We focus on the case that the task weight vectors are jointly sparse, i.e. they share the same small set of predictive features. Starting from previous work on standard linear regression with the group-lasso estimator we provide novel oracle-inequalities for this estimator when samples are collected by a bandit policy. Subsequently, building on a recent lasso-bandit policy, we investigate its group-lasso variant and analyze its regret bound. We specialize the proposed policy to the multi-task and meta-learning settings, demonstrating its theoretical advantage. We also point out a deficiency in the state-of-the-art lower bound and observe that our method has a smaller upper bound. Preliminary experiments confirm the effectiveness of our approach in practice

Stochastic Bandits with Delay-Dependent Payoffs

Motivated by recommendation problems in music streaming platforms, we propose a nonstationary stochastic bandit model in which the expected reward of an arm depends on the number of rounds that have passed since the arm was last pulled. After proving that finding an optimal policy is NP-hard even when all model parameters are known, we introduce a class of ranking policies provably approximating, to within a constant factor, the expected reward of the optimal policy. We show an algorithm whose regret with respect to the best ranking policy is bounded by Oe 1a kT , where k is the number of arms and T is time. Our algorithm uses only O k ln ln T) switches, which helps when switching between policies is costly. As constructing the class of learning policies requires ordering the arms according to their expectations, we also bound the number of pulls required to do so. Finally, we run experiments to compare our algorithm against UCB on different problem instance

Prospects for Stochastic Background Searches Using Virgo and LSC Interferometers

We consider the question of cross-correlation measurements using Virgo and the LSC Interferometers (LIGO Livingston, LIGO Hanford, and GEO600) to search for a stochastic gravitational-wave background. We find that inclusion of Virgo into the network will substantially improve the sensitivity to correlations above 200 Hz if all detectors are operating at their design sensitivity. This is illustrated using a simulated isotropic stochastic background signal, generated with an astrophysically-motivated spectrum, injected into 24 hours of simulated noise for the LIGO and Virgo interferometers.Comment: 11 pages, uses IOP style files, submitted to CQG for GWDAW11 proceedings; revised in response to referee comment

LIGO End-to-End simulation Program

A time-domain simulation program has been developed to provide an accurate description of interferometric gravitational wave detectors. This is being utilized to build a model of LIGO with the aim of aiding in the shakedown and integration of the interferometer subsystems, and ultimately the optimization of detector sensitivity

Development and function of murine B220+CD11c+NK1.1+ cells identify them as a subset of NK cells

Lymphoid organs contain a B220+CD11c+NK1.1+ cell population that was recently characterized as a novel dendritic cell (DC) subset that functionally overlaps with natural killer (NK) cells and plasmacytoid DCs (PDCs). Using Siglec-H and NK1.1 markers, we unambiguously dissected B220+CD11c+ cells and found that PDCs are the only professional interferon (IFN)-α–producing cells within this heterogeneous population. In contrast, B220+CD11c+NK1.1+ cells are a discrete NK cell subset capable of producing higher levels of IFN-γ than conventional NK cells. Unlike DCs, only a minute fraction of B220+CD11c+NK1.1+ cells in the spleen expressed major histocompatibility complex class II ex vivo or after stimulation with CpG. Consistent with being a NK cell subset, B220+CD11c+NK1.1+ cells depended primarily on interleukin 15 and common cytokine receptor γ chain signaling for their development. In terms of function, expression of distinctive cell surface receptors, and location in lymphoid organs, NK1.1+B220+CD11c+ appear to be the murine equivalent of human CD56bright NK cells

Group Meritocratic Fairness in Linear Contextual Bandits

We study the linear contextual bandit problem where an agent has to select one candidate from a pool and each candidate belongs to a sensitive group. In this setting, candidates⧠rewards may not be directly comparable between groups, for example when the agent is an employer hiring candidates from different ethnic groups and some groups have a lower reward due to discriminatory bias and/or social injustice. We propose a notion of fairness that states that the agent* policy is fair when it selects a candidate with highest relative rank, which measures how good the reward is when compared to candidates from the same group. This is a very strong notion of fairness, since the relative rank is not directly observed by the agent and depends on the underlying reward model and on the distribution of rewards. Thus we study the problem of learning a policy which approximates a fair policy under the condition that the contexts are independent between groups and the distribution of rewards of each group is absolutely continuous. In particular, we design a greedy policy which at each round constructs a ridge regression estimate from the observed context-reward pairs, and then computes an estimate of the relative rank of each candidate using the empirical cumulative distribution function. We prove that, despite its simplicity and the lack of an initial exploration phase, the greedy policy achieves, up to log factors and with high probability, a fair pseudo-regret of order √dT after T rounds, where d is the dimension of the context vectors. The policy also satisfies demographic parity at each round when averaged over all possible information available before the selection. Finally, we use simulated settings and experiments on the US census data to show that our policy achieves sub-linear fair pseudo-regret also in practice

The impact of next and back buttons on time to complete and measurement reliability in computer-based surveys

To assess the impact of including next and back buttons on response burden and measurement reliability of computer-based surveys. A sample of 807 participants (mean age of 53; 64% women, 83% non-Hispanic white; 81% some college or college graduates) from the YouGov Polimetrix panel was administered 56 items assessing performance of social/role activities and 56 items measuring satisfaction with social/role activities. Participants were randomly assigned to either (1) automatic advance to the next question with no opportunity to go back (auto/no back); (2) automatic advance to the next questions with an opportunity to go back (auto/back); (3) next button to go to the next question with no opportunity to go back (next/no back); or (4) next button to go to the next question with an opportunity to go back (next/back). We found no difference in missing data, internal consistency reliability, and domain scores by group. Time to complete the survey was about 50% longer when respondents were required to use a next button to go on. Given the similarity in missing data, reliability and mean scale scores with or without use of the next button, we recommend automatic advancement to the next item with the option to go back to the previous item

Stochastic background from extra-galactic double neutron stars

We present Monte Carlo simulations of the extra galactic population of inspiralling double neutron stars, and estimate its contribution to the astrophysical gravitational wave background, in the frequency range of ground based interferometers, corresponding to the last thousand seconds before the last stable orbit when more than 96 percent of the signal is released. We show that sources at redshift z>0.5 contribute to a truly continuous background which may be detected by correlating third generation interferometers.Comment: 13 pages, 7 figures - proceeding of a talk given at the 11th GWDAW, to appear in CQ

The b→sγγb\to s\gamma\gamma transition in softly broken supersymmetry

We study the effect of supersymmetric contributions to the effective quark transition $b\to s\gamma\gamma$, including leading order QCD effects. We apply the discussion to the decay $B_s\to\gamma\gamma$. Even though one-particle irreducible contributions could play a role, numerical cancelations make the amplitude for the two-photon emission strongly correlated to the $b\to s\gamma$ amplitude which is sharply constrained by experiment. A quite general statement follows: as long as non-standard physics effects appear only in the matching of the Wilson coefficients of the standard effective operator basis, the deviations from the standard model expectations of the decay rates induced by $b\to s\gamma\gamma$ are bound to follow closely the corresponding deviations on $b\to s\gamma$. Effects of new physics are therefore bound to be small.Comment: Latex2e, RevTex, 22 pages, 8 eps figures, comments and references adde

From risk-based health surveillance to health promotion: an evidence-based experience in a health care setting.

Health surveillance’s aim consists in different aspects: (i) to ensure worker’s health, (ii) to comply regulation, (iii) to detect health changes at their onset, (iv) to reduce cost, (v) to provide a fitness for job judgement, (vi) to provide a medical baseline and (vii) to be part of a preventive programme. Some of these aspects are perceived as benefits from the different stakeholders. Employers indicated as benefits worker’s satisfaction improvement, cost reduction, relationship improvement, early detection of health changes5. The study showed some other benefits: an improvement in worker’s satisfaction, an improvement in the relationship between stakeholders (even though based on qualitative data only), an early detection of health changes in few cases and a sickness absence reduction after influenza vaccination programme