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a field trial of privacy nudges for facebook || 2048723827 || alessandro acquisti || 2006 a query theory perspective of privacy decision making || 2562688705 || alessandro acquisti || 2016 an experiment in hiring discrimination via online social networks || 1119948448 || alessandro acquisti || 2018 beyond the privacy paradox objective versus relative risk in privacy decision making || 2336321440 || alessandro acquisti || 2011 beyond the turk an empirical comparison of alternative platforms for crowdsourcing online behavioral research || 1445579003 || alessandro acquisti || 2014 building the security behavior observatory an infrastructure for long term monitoring of client machines || 2055620204 || alessandro acquisti || 2000 choice architecture framing and cascaded privacy choices || 2337976014 || alessandro acquisti || 2001 do or do not there is no try user engagement may not improve security outcomes || 2411354024 || alessandro acquisti || 2011 empirical analysis of data breach litigation || 1960191312 || alessandro acquisti || 2013 engineering information disclosure norm shaping designs || 2407481741 || alessandro acquisti || 2017 follow my recommendations a personalized privacy assistant for mobile app permissions || 2415016544 || alessandro acquisti || 2000 framing and the malleability of privacy choices || 2562123916 || alessandro acquisti || 2003 heads or tails a reachability bias in binary choice || 1523515082 || alessandro acquisti || 2008 i cheated but only a little partial confessions to unethical behavior || 2150562299 || alessandro acquisti || 2017 i read my twitter the next morning and was astonished a conversational perspective on twitter regrets || 2155071529 || alessandro acquisti || 2017 i would like to i shouldn t i wish i exploring behavior change goals for social networking sites || 2093680229 || alessandro acquisti || 2004 inducing customers to try new goods || 2053535430 || alessandro acquisti || 2003 misplaced confidences privacy and the control paradox || 2143953012 || alessandro acquisti || 2011 not all privacy is created equal the welfare impact of targeted advertising || 2605539038 || alessandro acquisti || 2006 privacy manipulation and acclimation in a location sharing application || 2112032833 || alessandro acquisti || 2004 privacy nudges for social media an exploratory facebook study || 145299914 || alessandro acquisti || 2000 self reported social network behavior accuracy predictors and implications for the privacy paradox || 2054638531 || alessandro acquisti || 2013 sleights of privacy framing disclosures and the limits of transparency || 2069636936 || alessandro acquisti || 2008 the impact of privacy regulation and technology incentives the case of health information exchanges || 2176928290 || alessandro acquisti || 2019 the impact of reversibility on the decision to disclose personal information || 2529828229 || alessandro acquisti || 2014 the impact of timing on the salience of smartphone app privacy notices || 1981568085 || alessandro acquisti || 2014 the welfare and allocative impact of targeted advertising || 2205026508 || alessandro acquisti || 2013 tweets are forever a large scale quantitative analysis of deleted tweets || 2032695641 || alessandro acquisti || 2003 what is privacy worth || 1967317786 || alessandro acquisti || 2006 your location has been shared 5 398 times a field study on mobile app privacy nudging || 2123307077 || alessandro acquisti || 2010 a contingency view of transferring and adapting best practices within online communities || 2292280558 || aniket kittur || 2002 distributed analogical idea generation with multiple constraints || 2290943337 || aniket kittur || 2015 supporting mobile sensemaking through intentionally uncertain highlighting || 2533819458 || aniket kittur || 2013 exploring the value of information delivered to drivers || 2500375913 || anind dey || 2013 using multiple contexts to detect and form opportunistic groups || 2030456950 || anind dey || 2009 a quasi experimental estimate of the impact of p2p transportation platforms on urban consumer patterns || 2745131988 || beibei li || 2007 bike sharing and car trips in the city the case of healthy ride pittsburgh || 2585656250 || beibei li || 2009 digitizing offline shopping behavior towards mobile marketing || 2202849354 || beibei li || 2019 examining the impact of contextual ambiguity on search advertising keyword performance a topic model approach || 232477822 || beibei li || 2015 impact of car specifications prices and incentives for electric vehicles in norway choices of heterogeneous consumers || 2528075027 || beibei li || 2019 learning individual behavior using sensor data the case of gps traces and taxi drivers || 2364071307 || beibei li || 2003 mobile targeting using customer trajectory patterns || 2610291238 || beibei li || 2003 modeling user engagement in mobile content consumption with tapstream data and field experiment || 2529452593 || beibei li || 2013 nudging mobile customers with real time social dynamics || 2611355462 || beibei li || 2007 perils of uncertainty the impact of contextual ambiguity on search advertising keyword performance || 18143179 || beibei li || 2005 the impact of copycats on an original mobile app s demand empirical analysis and a method for detecting copycat apps || 1942772871 || beibei li || 2000 the impact of mobile channel adoption on customer omni channel banking behavior || 2596649803 || beibei li || 2019 understanding user economic behavior in the city using large scale geotagged and crowdsourced data || 2338895451 || beibei li || 2014 zoom in ios clones examining the antecedents and consequences of mobile app copycats || 160458139 || beibei li || 2011 cross disciplinary consultancy to bridge public health technical needs and analytic developers asyndromic surveillance use case || 2259258356 || daniel neill || 2004 fast generalized subset scan for anomalous pattern detection || 2146022760 || daniel neill || 2011 fast kronecker inference in gaussian processes with non gaussian likelihoods || 1917966882 || daniel neill || 2001 gaussian processes for independence tests with non iid data in causal inference || 2273081434 || daniel neill || 2016 graph structure learning from unlabeled data for early outbreak detection || 2601121662 || daniel neill || 2015 graph structure learning from unlabeled data for event detection || 2575532943 || daniel neill || 2007 identifying emerging novel outbreaks in textual emergency department data || 1961666882 || daniel neill || 2000 identifying significant predictive bias in classifiers || 2558177882 || daniel neill || 2001 lass 0 sparse non convex regression by local search || 2266653482 || daniel neill || 2016 machine learning approaches for early drg classification and resource allocation || 2178355895 || daniel neill || 2019 multidimensional tensor scan for drug overdose surveillance || 2610624362 || daniel neill || 2013 non parametric scan statistics for disease outbreak detection on twitter || 2112964778 || daniel neill || 2016 non parametric scan statistics for event detection and forecasting in heterogeneous social media graphs || 2038943544 || daniel neill || 2007 scalable gaussian processes for characterizing multidimensional change surfaces || 2281833786 || daniel neill || 2010 semantic scan detecting subtle spatially localized events in text streams || 2258204935 || daniel neill || 2007 starscan a novel scan statistic for irregularly shaped spatial clusters || 2144756869 || daniel neill || 2002 the role of social influence in security feature adoption || 2084885239 || jason hong || 2013 using text mining to infer the purpose of permission use in mobile apps || 1998862130 || jason hong || 2012 a spellchecker for dyslexia || 1998834343 || jeffrey bigham || 2001 coding varied behavior types using the crowd || 2296547012 || jeffrey bigham || 2019 the effects of automatic speech recognition quality on human transcription latency || 2505877856 || jeffrey bigham || 2010 fostering engagement with personal informatics systems || 2412436369 || jodi forlizzi || 2000 playtesting with a purpose || 2530983154 || jodi forlizzi || 2012 planning adaptive mobile experiences when wireframing || 2417717420 || john zimmerman || 2019 testing theories of transfer using error rate learning curves || 2406413179 || kenneth koedinger || 2004 rush targeted time limited coupons via purchase forecasts || 2744890480 || leman akoglu || 2014 ties that bind characterizing classes by attributes and social ties || 2585125256 || leman akoglu || 2009 identifying thematic roles from neural representations measured by functional magnetic resonance imaging || 2441780790 || marcel just || 2013 a bayesian model to predict content creation with two sided peer influence in content platforms || 223854805 || ramayya krishnan || 2013 a quantitative analysis of decision process in social groups using human trajectories || 1928311886 || ramayya krishnan || 2008 adaptive collective routing using gaussian process dynamic congestion models || 2146333962 || ramayya krishnan || 2012 comparing peer influences in large social networks an empirical study on caller ringback tone || 2548482986 || ramayya krishnan || 2006 contrasting multiple social network autocorrelations for binary outcomes with applications to technology adoption || 2156402754 || ramayya krishnan || 2015 forgotten third parties analyzing the contingent association between unshared third parties knowledge overlap and knowledge transfer relationships with outsiders || 1902444984 || ramayya krishnan || 2012 hydra large scale social identity linkage via heterogeneous behavior modeling || 2055345291 || ramayya krishnan || 2011 latent homophily or social influence an empirical analysis of purchase within a social network || 2133265130 || ramayya krishnan || 2019 on product level uncertainty and online purchase behavior an empirical analysis || 2099686863 || ramayya krishnan || 2011 on risk management with information flows in business processes || 2147841110 || ramayya krishnan || 2003 predicting bundles of spatial locations from learning revealed preference data || 2243328796 || ramayya krishnan || 2011 todmis mining communities from trajectories || 2163347789 || ramayya krishnan || 2006 understanding sequential decisions via inverse reinforcement learning || 2021472139 || ramayya krishnan || 2017 vait a visual analytics system for metropolitan transportation || 2010900220 || ramayya krishnan || 2001 adapting collaboration dialogue in response to intelligent tutoring system feedback || 607229976 || vincent aleven || 2001 toward combining individual and collaborative learning within an intelligent tutoring system || 593520158 || vincent aleven || 2003 using an intelligent tutoring system to support collaborative as well as individual learning || 54435281 || vincent aleven || 2018

Figure 3: Probabilities for the second car model (Part 2) Part 2: Bayesian Networks In a different model of the car, the alternator (A) can stop working due to an electric fault (E) or due to the breaking of the drive belt (D). The failure of the alternator causes complete discharge of the battery (B) that supplies current to the radio (R) and lights (L). The battery, the lights and the radio may also stop working for internal reasons. 1. Draw the Bayesian network that represents the model of the car, show- ing the variables and the dependence/ independence relationships between them. 2. Use the obtained network and the probabilities listed in Figure 3 to com- pute the probability of: 0 Phil, 6, a, b, -'r, -l) o P(-ud, s, -u&, b, r, I) Part 3: Exact Inference in Bayesian Networks To make a probability inference query means to compute the posterior prob- ability distribution for a set of query variables given some observed event. X denotes the query wariable, E denotes the set of evidence variables E1, ..., E\A company is interested in implementing some A / B testing on its website in order to improve sales. In order to do this they rst need to look at what their current website usage is. Let X.- represent the number of customers who visit the webpage in a given hour. Assume X1,X2, ...,Xn W PoissonOl). Let's use a Bayesian approach to make some inference about A. Use A ~ Exponentialm) as a prior distri bution. Where is the mean parameter. So f (A) = [lacM3 for /\\ 2 0. Derive the posterior distribution of A. Identify what wellknown distribution the posterior follows, and be sure to identify it's parameters. Note: the parameters of the posterior should be expressed as a function of the sample mean, sample size, ,6 and numbers (exclusively). Problem 2. Below is the Bayesian network for the WetGrass problem. Some prior probabilities and conditional probability tables are given. All variables are Boolean variables that can take values true (t) or false (t). 2.a Calculate the value for the joint probability (show your work): P(C=f, R=f, S=t, W=t) 2.!) You observe that W=t and S=f. Perform inference to obtain the posteriori probability that the weather is cloudy, that is: PIEC = t|W = LS = 1"). Show your work