Lift-Based Bidding in Ad Selection

Real-time bidding (RTB) has become one of the largest online advertising markets in the world. Today the bid price per ad impression is typically decided by the expected value of how it can lead to a desired action event (e.g., registering an account or placing a purchase order) to the advertiser. However, this industry standard approach to decide the bid price does not consider the actual effect of the ad shown to the user, which should be measured based on the performance lift among users who have been or have not been exposed to a certain treatment of ads. In this paper, we propose a new bidding strategy and prove that if the bid price is decided based on the performance lift rather than absolute performance value, advertisers can actually gain more action events. We describe the modeling methodology to predict the performance lift and demonstrate the actual performance gain through blind A/B test with real ad campaigns in an industry-leading Demand-Side Platform (DSP). We also discuss the relationship between attribution models and bidding strategies. We prove that, to move the DSPs to bid based on performance lift, they should be rewarded according to the relative performance lift they contribute.Comment: AAAI 201

Direct Learning-Based Deep Spiking Neural Networks: A Review

The spiking neural network (SNN), as a promising brain-inspired computational model with binary spike information transmission mechanism, rich spatially-temporal dynamics, and event-driven characteristics, has received extensive attention. However, its intricately discontinuous spike mechanism brings difficulty to the optimization of the deep SNN. Since the surrogate gradient method can greatly mitigate the optimization difficulty and shows great potential in directly training deep SNNs, a variety of direct learning-based deep SNN works have been proposed and achieved satisfying progress in recent years. In this paper, we present a comprehensive survey of these direct learning-based deep SNN works, mainly categorized into accuracy improvement methods, efficiency improvement methods, and temporal dynamics utilization methods. In addition, we also divide these categorizations into finer granularities further to better organize and introduce them. Finally, the challenges and trends that may be faced in future research are prospected.Comment: Accepted by Frontiers in Neuroscienc

Loss of AMIGO2 causes dramatic damage to cardiac preservation after ischemic injury

Background: Recent studies have identified amphoterin-induced gene and open reading frame (AMIGO2). The role of AMIGO2 in tumour research is well-studied, but its role in ischemic heart diseases is seldom reported. In the present study, the role of AMIGO2 in myocardial infarction (MI) is under investigation for the first time. Methods: For in vitro studies, cardiomyocytes (CMs) and endothelial cells (ECs) were isolated from both AMIGO2 knockout (KO) and WT mice. The apoptosis of CMs was tested after 48 h of ischemic stimulation. A proliferation test was implemented after 7 days of normoxic incubation and tube forma­tion on ECs. For in vivo studies, the MI model was built in mice hearts. Echocardiographic evaluation was performed at 3 days and 28 days post-MI, while the hemodynamics test was performed at 28 days post-MI. The histological results of the apoptosis, proliferation, angiogenesis and infarct zone assess­ments were determined using terminal deoxynucleotidyl transferase-mediated dUTP nick end-labelling (TUNEL) assay, Ki67 staining, a-SMA/CD31 immunostain and the Masson-Trichrome method, respectively. The expression changes of the Akt pathway and related proteins were confirmed using both quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot. Results: The present results demonstrated that AMIGO2 deficiency caused more CMs suffering apop­tosis, lower proliferation and less angiogenesis in vitro and in vivo. Weaker cardiac function and larger scar formation were detected in AMIGO2 KO mice, and increased expression of active-caspase-3 and decreased expression of PDK1, p-Akt, Bcl-2/Bax and VEGF occurred. Conclusions: Herein the findings indicate that AMIGO2 deficiency plays an attenuated cardio-pro­tective role in ischemic heart disease via inactivation of the PDK1/Pten/Akt pathway

Inequality of Opportunity in Health Care in China: Suggestion on the Construction of the Urban-Rural Integrated Medical Insurance System

This paper investigates the urban-rural inequality of opportunity in health care in China based on the theory of the EOp of Roemer (1998). Following the compensation principle proposed by Fleurbaey and Schokkaert (2011), this paper decomposes the fairness gap in the urban-rural health care utilization. The results shows that the ratios of the fairness gap to are 1.167 during 1997-2000 and 1.744 during 2004-2006. It implies that the degree of the essential inequity is underestimated. Meanwhile, upgrading the urban-rural reimbursement ratios is probably not sufficient to eliminate the inequality of opportunity in health care utilization between urban and rural residents. Under background of urban-rural dualistic social structure and the widening of urban-rural income gap, the pro-disadvantage policies will be more effective to promote the equality of opportunity in health car

Will Low-Income Populations Love Spicy Foods More? Accounting for Tastes

Based on the Theory of Rational Addiction (TORA), this paper identifies the correlation between income and the preference for spicy foods by analysing the China Health and Nutrition Survey (CHNS) data. The results show that compare with high-income residents of same area, the low-income residents prefer to spicy foods in China. The regression results of IV and Lewbel IV all support it. According to the result, the channel of health behaviours and health awareness are possible causal channels for the negative correlation between income and the preference for spicy foods, rather than health capital stock and food selection

Will Low-Income Populations Love Spicy Foods More? Accounting for Tastes

Based on the Theory of Rational Addiction (TORA), this paper identifies the correlation between income and the preference for spicy foods by analysing the China Health and Nutrition Survey (CHNS) data. The results show that compare with high-income residents of same area, the low-income residents prefer to spicy foods in China. The regression results of IV and Lewbel IV all support it. According to the result, the channel of health behaviours and health awareness are possible causal channels for the negative correlation between income and the preference for spicy foods, rather than health capital stock and food selection

Inequality of Opportunity in Health Care in China: Suggestion on the Construction of the Urban-Rural Integrated Medical Insurance System

This paper investigates the urban-rural inequality of opportunity in health care in China based on the theory of the EOp of Roemer (1998). Following the compensation principle proposed by Fleurbaey and Schokkaert (2011), this paper decomposes the fairness gap in the urban-rural health care utilization. The results shows that the ratios of the fairness gap to are 1.167 during 1997-2000 and 1.744 during 2004-2006. It implies that the degree of the essential inequity is underestimated. Meanwhile, upgrading the urban-rural reimbursement ratios is probably not sufficient to eliminate the inequality of opportunity in health care utilization between urban and rural residents. Under background of urban-rural dualistic social structure and the widening of urban-rural income gap, the pro-disadvantage policies will be more effective to promote the equality of opportunity in health car

RMP-Loss: Regularizing Membrane Potential Distribution for Spiking Neural Networks

Spiking Neural Networks (SNNs) as one of the biology-inspired models have received much attention recently. It can significantly reduce energy consumption since they quantize the real-valued membrane potentials to 0/1 spikes to transmit information thus the multiplications of activations and weights can be replaced by additions when implemented on hardware. However, this quantization mechanism will inevitably introduce quantization error, thus causing catastrophic information loss. To address the quantization error problem, we propose a regularizing membrane potential loss (RMP-Loss) to adjust the distribution which is directly related to quantization error to a range close to the spikes. Our method is extremely simple to implement and straightforward to train an SNN. Furthermore, it is shown to consistently outperform previous state-of-the-art methods over different network architectures and datasets.Comment: Accepted by ICCV202