Sun, 27 Jul 2008 06:12:57 BST CiteULike: Tag expectation http://www.citeulike.org/tag/expectation CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/zf137/article/989971 <i>Signal Processing Magazine, IEEE, Vol. 13, No. 6. (1996), pp. 47-60.</i><br /><br />A common task in signal processing is the estimation of the parameters of a probability distribution function. Perhaps the most frequently encountered estimation problem is the estimation of the mean of a signal in noise. In many parameter estimation problems the situation is more complicated because direct access to the data necessary to estimate the parameters is impossible, or some of the data are missing. Such difficulties arise when an outcome is a result of an accumulation of simpler outcomes, or when outcomes are clumped together, for example, in a binning or histogram operation. There may also be data dropouts or clustering in such a way that the number of underlying data points is unknown (censoring and/or truncation). The EM (expectation-maximization) algorithm is ideally suited to problems of this sort, in that it produces maximum-likelihood (ML) estimates of parameters when there is a many-to-one mapping from an underlying distribution to the distribution governing the observation. The EM algorithm is presented at a level suitable for signal processing practitioners who have had some exposure to estimation theory The expectation-maximization algorithm TK Moon doi:10.1109/79.543975 Signal Processing Magazine, IEEE, Vol. 13, No. 6. (1996), pp. 47-60. 2006-12-12T17:14:33-00:00 1996 Signal Processing Magazine, IEEE 13 6 47 60 expectation maximization mixture poisson http://www.citeulike.org/user/varung/article/658282 <i>Proceedings of the IEEE, Vol. 86, No. 11. (1998), pp. 2210-2239.</i><br /><br />The deterministic annealing approach to clustering and its extensions has demonstrated substantial performance improvement over standard supervised and unsupervised learning methods in a variety of important applications including compression, estimation, pattern recognition and classification, and statistical regression. The application-specific cost is minimized subject to a constraint on the randomness of the solution, which is gradually lowered. We emphasize the intuition gained from analogy to statistical physics. Alternatively the method is derived within rate-distortion theory, where the annealing process is equivalent to computation of Shannon's rate-distortion function, and the annealing temperature is inversely proportional to the slope of the curve. The basic algorithm is extended by incorporating structural constraints to allow optimization of numerous popular structures including vector quantizers, decision trees, multilayer perceptrons, radial basis functions, and mixtures of experts Deterministic annealing for clustering, compression, classification, regression, and related optimization problems K Rose Proceedings of the IEEE, Vol. 86, No. 11. (1998), pp. 2210-2239. 2006-05-19T19:52:50-00:00 1998 Proceedings of the IEEE 86 11 2210 2239 annealing deterministic expectation maximization search http://www.citeulike.org/user/tvdbulck/article/117535 <i>(1977)</i><br /><br />A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and convergence of the algorithm is derived. Many examples are sketched, including missing value situations, applications to grouped, censored or truncated data, finite mixture models, variance component estimation, hyperparameter estimation, iteratively reweighted least squares and factor analysis. Maximum Likelihood from Incomplete Data via the EM Algorithm AP Dempster NM Laird DB Rubin doi:10.2307/2984875 (1977) 2005-03-08T19:21:34-00:00 1977 algorithm convergence em expectation maximization http://www.citeulike.org/user/tvdbulck/article/117580 <i>The Annals of Statistics, Vol. 11, No. 1. (1983), pp. 95-103.</i><br /><br />Two convergence aspects of the EM algorithm are studied: (i) does the EM algorithm find a local maximum or a stationary value of the (incomplete-data) likelihood function? (ii) does the sequence of parameter estimates generated by EM converge? Several convergence results are obtained under conditions that are applicable to many practical situations. Two useful special cases are: (a) if the unobserved complete-data specification can be described by a curved exponential family with compact parameter space, all the limit points of any EM sequence are stationary points of the likelihood function; (b) if the likelihood function is unimodal and a certain differentiability condition is satisfied, then any EM sequence converges to the unique maximum likelihood estimate. A list of key properties of the algorithm is included. On the Convergence Properties of the EM Algorithm Jeff Wu The Annals of Statistics, Vol. 11, No. 1. (1983), pp. 95-103. 2005-03-08T22:13:04-00:00 1983 The Annals of Statistics 11 1 95 103 algorithm bayes bayesian convergence em expectation maximization http://www.citeulike.org/user/ttaga/article/2245717 <i>Cognitive Therapy and Research, Vol. 16, No. 3. (1 June 1992), pp. 329-348.</i><br /><br />Self-efficacy, Bandura's concept of a central cognitive mediating belief, has been widely researched and found to play an important role in the initiation, persistence, and achievement of a variety of behaviors. Self-efficacy can be viewed as one aspect of expectancy-value theory, but little research has been conducted to identify the relationship between measures of self-efficacy and outcome expectation across performance trials. This paper illustrates the importance of multiple trials in the investigation of self-efficacy, outcome expectation, outcome value, and performance. Using an item-writing task, subjects' self-efficacy, outcome expectations, and outcome value ratings were measured across a 10-week period. While self-efficacy was initially related to performance, in later trials it was past behavior that accounted for most of the explained variance in item-writing performance. It appears that investigating these variables across multiple trials is essential if a comprehensive view of the relationship between self-efficacy, outcome expectation, outcome value, and behavior is to be gained. Results and alterative explanations are discussed in light of both self-efficacy theory and cognitive information process. An investigation of the patterns of self-efficacy, outcome expectation, outcome value, and performance across trials Thomas Sexton Bruce Tuckman Kevin Crehan doi:10.1007/BF01183285 Cognitive Therapy and Research, Vol. 16, No. 3. (1 June 1992), pp. 329-348. 2008-01-17T15:27:54-00:00 1992 Cognitive Therapy and Research 16 3 329 348 expectation multiple outcome performance self-efficacy trials value http://www.citeulike.org/user/stefanherzog/article/771076 <i>Organizational Behavior and Human Decision Processes, Vol. 100, No. 2. (July 2006), pp. 193-201.</i><br /><br />We used simple economic games to examine pro-social behavior and the lengths that people will take to avoid engaging in it. Over two studies, we found that about one-third of participants were willing to "exit" a $10 dictator game and take $9 instead. The exit option left the receiver nothing, but also ensured that the receiver never knew that a dictator game was to be played. Because most social utility models are defined over monetary outcomes, they cannot explain choosing the ($9, $0) exit outcome over the dominating $10 dictator game, since the game includes outcomes of ($10, $0) and ($9, $1). We also studied exiting using a "private" dictator game. In the private game, the receiver never knew about the game or from where any money was received. Gifts in this game were added innocuously to a payment for a separate task. Almost no dictators exited from the private game, indicating that receivers' beliefs are the key factor in the decision to exit. When, as in the private game, the receivers' beliefs and expectations cannot be manipulated by exit, exit is seldom taken. We conclude that giving often reflects a desire not to violate others' expectations rather than a concern for others' welfare per se. We discuss the implications of our results for understanding ethical decisions and for testing and modeling social preferences. An adequate specification of social preferences should include "psychological" payoffs that directly incorporate beliefs about actions into the utility function. What you don't know won't hurt me: Costly (but quiet) exit in dictator games Jason Dana Daylian Cain Robyn Dawes doi:10.1016/j.obhdp.2005.10.001 Organizational Behavior and Human Decision Processes, Vol. 100, No. 2. (July 2006), pp. 193-201. 2006-07-24T12:03:54-00:00 2006 Organizational Behavior and Human Decision Processes 100 2 193 201 dictator-game exit expectation norms http://www.citeulike.org/user/stefanherzog/article/214190 <i>Organizational Behavior and Human Decision Processes, Vol. 97, No. 2. (July 2005), pp. 152-160.</i><br /><br />People experience regret when they realize that they would have been better off had they decided differently. Hence, a central element in regret is the comparability of a decision outcome with the outcomes forgone. Up to now, however, the comparison process that is so essential to the experience of regret has not been the subject of psychological research. In this article, we tune in on the comparison dependency of regret. We argue that factors that reduce the tendency to compare attenuate regret, and demonstrate that uncertainty about counterfactual outcomes (Experiment 1), and incomparability of counterfactual and factual outcomes (Experiments 2 and 3) produce such effects. On the psychology of 'if only': Regret and the comparison between factual and counterfactual outcomes Eric van Dijk Marcel Zeelenberg doi:10.1016/j.obhdp.2005.04.001 Organizational Behavior and Human Decision Processes, Vol. 97, No. 2. (July 2005), pp. 152-160. 2005-05-30T13:16:30-00:00 2005 Organizational Behavior and Human Decision Processes 97 2 152 160 anticipation choice comparison counterfactuals decision-making emotion expectation regret http://www.citeulike.org/user/stefanherzog/article/214054 <i>Journal of Experimental Social Psychology, Vol. 41, No. 4. (July 2005), pp. 438-446.</i><br /><br />In an often-cited study about counterfactuals, Medvec, Madey, and Gilovich (1995) found that bronze medalists appeared happier than silver medalists in television coverage of the 1992 Summer Olympics. Medvec et al. argued that bronze medalists compared themselves to 4th place finishers, whereas silver medalists compared themselves to gold medalists. These counterfactuals were the most salient because they were either qualitatively different (gold vs. silver) or categorically different (medal vs. no medal) from what actually occurred. Drawing on archival data and experimental studies, we show that Olympic athletes (among others) are more likely to make counterfactual comparisons based on their prior expectations, consistent with decision affect theory. Silver medalists are more likely to be disappointed because their personal expectations are higher than those of bronze medalists. We provide a test between expectancy-based versus category-based processing and discuss circumstances that trigger each type of processing. Expectations and emotions of Olympic athletes Peter Mcgraw Barbara Mellers Philip Tetlock doi:10.1016/j.jesp.2004.09.001 Journal of Experimental Social Psychology, Vol. 41, No. 4. (July 2005), pp. 438-446. 2005-05-30T09:12:42-00:00 2005 Journal of Experimental Social Psychology 41 4 438 446 counterfactuals emotion expectation http://www.citeulike.org/user/stefanherzog/article/233187 <i>Science, Vol. 308, No. 5729. (17 June 2005), pp. 1798-1801.</i><br /><br />Activity in several areas of the human brain and the monkey brain increases when a subject anticipates events associated with a reward, implicating a role for bias of decision and action. However, in real life, events do not always appear as expected, and we must choose an undesirable action. More than half of the neurons in the monkey centromedian (CM) thalamus were selectively activated when a small-reward action was required but a large-reward option was anticipated. Electrical stimulation of the CM after a large-reward action request substituted a brisk performance with a sluggish performance. These results suggest involvement of the CM in a mechanism complementary to decision and action bias. Complementary Process to Response Bias in the Centromedian Nucleus of the Thalamus Takafumi Minamimoto Yukiko Hori Minoru Kimura doi:10.1126/science.1109154 Science, Vol. 308, No. 5729. (17 June 2005), pp. 1798-1801. 2005-06-21T09:34:17-00:00 2005 Science 308 5729 1798 1801 expectation monkey reward thalamus http://www.citeulike.org/user/shupsy/article/2183506 <i>Biological Psychiatry, Vol. 63, No. 2. (15 January 2008), pp. 222-230.</i><br /><br />Background Human expectation of psychoactive drugs significantly alters drug effects and behavioral responses. However, their neurophysiological mechanisms are not clear. This study investigates how cocaine expectation modulates human brain responses to acute cocaine administration.Methods Twenty-six right-handed non-treatment-seeking regular cocaine abusers participated in this study. Changes in blood oxygenation level-dependent (BOLD) signals were measured, and online behavioral ratings during cocaine expectation and acute cocaine administration were recorded.Results Distinct regional characteristics in BOLD responses to expected and unexpected cocaine infusions were observed in the medial orbitofrontal gyrus (Brodmann area [BA] 11), frontal pole (BA 10), and anterior cingulate gyrus regions. Active engagement in the amygdala and the lateral orbitofrontal cortex (OFC; BA 47) by unexpected but not expected cocaine infusion was discovered. Cocaine expectation did not change BOLD responses to acute cocaine administration in a set of subcortical substrates, the nucleus accumbens, ventral putamen, ventral tegmental area, and thalamus.Conclusions These results suggest that cocaine expectation modulates neural-sensitivity adaptation between the expected events and the actual outcomes but did not modulate the pharmacological characteristics of cocaine. In addition, the amygdala-lateral OFC circuitry plays an important role in mediating stimulus-outcome relations and contextual factors of drug abuse. Expectation modulates human brain responses to acute cocaine: A functional magnetic resonance imaging study P Kufahl Z Li R Risinger C Rainey L Piacentine G Wu A Bloom Z Yang SJ Li doi:10.1016/j.biopsych.2007.03.021 Biological Psychiatry, Vol. 63, No. 2. (15 January 2008), pp. 222-230. 2007-12-31T13:54:40-00:00 2008 Biological Psychiatry 63 2 222 230 amygdala cocaine expectation mri orbitofrontal-cortex http://www.citeulike.org/user/ricmilne/article/2906077 <i>Research Policy, Vol. 36, No. 4. (May 2007), pp. 566-589.</i><br /><br />This paper argues that despite being widely promoted by academics and consultants, the empirical evidence does not support the existence of a biotech revolution. Nor does the data support the widely held expectations that biotechnology is having a revolutionary impact on healthcare or economic development. The revolutionary model is therefore a misleading basis for policy making as it over-estimates the speed and extent of any changes in productivity or the quality of therapeutics. Instead, the evidence suggests biotechnology is following a well-established incremental pattern of technological change and [`]creative accumulation' that builds upon, rather than disrupts, previous drug development heuristics. The myth of the biotech revolution: An assessment of technological, clinical and organisational change Michael Hopkins Paul Martin Paul Nightingale Alison Kraft Surya Mahdi doi:10.1016/j.respol.2007.02.013 Research Policy, Vol. 36, No. 4. (May 2007), pp. 566-589. 2008-06-18T19:39:14-00:00 2007 Research Policy 36 4 566 589 biotechnology expectation innovation http://www.citeulike.org/user/oamg/article/1679005 <i>Neuron, Vol. 55, No. 6. (20 September 2007), pp. 970-984.</i><br /><br />Summary Animals and humans learn to approach and acquire pleasant stimuli and to avoid or defend against aversive ones. However, both pleasant and aversive stimuli can elicit arousal and attention, and their salience or intensity increases when they occur by surprise. Thus, adaptive behavior may require that neural circuits compute both stimulus valence--or value--and intensity. To explore how these computations may be implemented, we examined neural responses in the primate amygdala to unexpected reinforcement during learning. Many amygdala neurons responded differently to reinforcement depending upon whether or not it was expected. In some neurons, this modulation occurred only for rewards or aversive stimuli, but not both. In other neurons, expectation similarly modulated responses to both rewards and punishments. These different neuronal populations may subserve two sorts of processes mediated by the amygdala: those activated by surprising reinforcements of both valences--such as enhanced arousal and attention--and those that are valence-specific, such as fear or reward-seeking behavior. Expectation Modulates Neural Responses to Pleasant and Aversive Stimuli in Primate Amygdala Marina Belova Joseph Paton Sara Morrison Daniel Salzman doi:10.1016/j.neuron.2007.08.004 Neuron, Vol. 55, No. 6. (20 September 2007), pp. 970-984. 2007-09-20T13:17:19-00:00 2007 Neuron 55 6 970 984 amygdala expectation primate http://www.citeulike.org/user/mrosenki/article/2823355 <i>(2000), pp. 46-47.</i><br /><br />This thesis seeks to address the incorporation of a low-level cognitive ability into reactive, behavior-based artificial intelligence architectures. Specifically, it addresses the need to generate short-term, observation-based expectations about the world and react appropriately to the violation of those expectations. In it I discuss the motivation for incorporating expectations into a reactive behavior-based architecture, outline the qualitative properties of expectations and the conditions... Observation-Based Expectation Generation and Response for Believable Reactive Agents Christopher Kline Bruce Blumberg (2000), pp. 46-47. 2008-05-22T16:14:57-00:00 2000 46 47 ACM Press expectation observation http://www.citeulike.org/user/mjaz/article/126963 <i>Nature, Vol. 431, No. 7011. (21 October 2004), pp. 993-996.</i> Neural correlates of mental rehearsal in dorsal premotor cortex Paul Cisek John Kalaska doi:10.1038/nature03005 Nature, Vol. 431, No. 7011. (21 October 2004), pp. 993-996. 2005-03-14T22:18:08-00:00 2004 Nature 431 7011 993 996 awakebehaving dpremotor expectation implied memory mental monkeys rehersal task http://www.citeulike.org/user/mbregman/article/2364342 <i>Cognitive Psychology, Vol. 41, No. 3. (November 2000), pp. 254-311.</i><br /><br />Seven experiments examine the influence of contextual timing manipulations on prospective time judgments. Subjects judged durations of standard vs comparison time intervals in the context of a preceding induction (context) sequence. In some experiments, the rate of the induction sequence was systematically manipulated relative to the range of to-be-judged standard time intervals; in others, the induction sequence was omitted. Time judgments were strongly influenced by the rate of an induction sequence with best performance occurring when the standard time interval ended as expected, given context rate. An expectancy profile, in the form of an inverted U, indicated that time estimation accuracy declined systematically as a standard interval differed from a context rate. A similar expectancy profile emerged when the context rate was based on a harmonic subdivision (one-half) of an expected standard interval. Results are discussed in terms of various stimulus-based models of prospective time judgments, including those which appeal to attentional periodicities and entrainment. Expectancy, Attention, and Time Ralph Barnes Mari Jones doi:10.1006/cogp.2000.0738 Cognitive Psychology, Vol. 41, No. 3. (November 2000), pp. 254-311. 2008-02-12T01:20:51-00:00 2000 Cognitive Psychology 41 3 254 311 attention expectation time http://www.citeulike.org/user/mbregman/article/2954215 <i>Computer Music Journal, Vol. 30, No. 2. (June 2006), pp. 63-83.</i> Spectral Anticipations Shlomo Dubnov doi:10.1162/comj.2006.30.2.63 Computer Music Journal, Vol. 30, No. 2. (June 2006), pp. 63-83. 2008-07-02T22:20:08-00:00 2006 Computer Music Journal 0148-9267 30 2 63 83 MIT Press auditory expectation http://www.citeulike.org/user/mbregman/article/239100 <i>Psychonomic Bulletin & Review, Vol. 12, No. 2. (April 2005), pp. 328-334.</i> Attentional Preparation Based on Temporal Expectancy Modulates Processing at the Perceptual Level Angel Correa Juan Lupianez Pio Tudela Psychonomic Bulletin & Review, Vol. 12, No. 2. (April 2005), pp. 328-334. 2005-06-27T21:17:17-00:00 2005 Psychonomic Bulletin & Review 1069-9384 12 2 328 334 Psychonomic Society Publications attention expectation rhythm http://www.citeulike.org/user/goochy1974/article/312590 <i>(1999), pp. 229-238.</i> The role of expectations in human-computer interaction Joseph Bonito Judee Burgoon Bjorn Bengtsson doi:10.1145/320297.320324 (1999), pp. 229-238. 2005-09-07T10:04:25-00:00 1999 229 238 ACM Press expectation http://www.citeulike.org/user/fbaroni/article/477546 <i>Neuron, Vol. 46, No. 4. (19 May 2005), pp. 681-692.</i><br /><br />SummaryUncertainty in various forms plagues our interactions with the environment. In a Bayesian statistical framework, optimal inference and prediction, based on unreliable observations in changing contexts, require the representation and manipulation of different forms of uncertainty. We propose that the neuromodulators acetylcholine and norepinephrine play a major role in the brain's implementation of these uncertainty computations. Acetylcholine signals expected uncertainty, coming from known unreliability of predictive cues within a context. Norepinephrine signals unexpected uncertainty, as when unsignaled context switches produce strongly unexpected observations. These uncertainty signals interact to enable optimal inference and learning in noisy and changeable environments. This formulation is consistent with a wealth of physiological, pharmacological, and behavioral data implicating acetylcholine and norepinephrine in specific aspects of a range of cognitive processes. Moreover, the model suggests a class of attentional cueing tasks that involve both neuromodulators and shows how their interactions may be part-antagonistic, part-synergistic. Uncertainty, Neuromodulation, and Attention Angela Yu Peter Dayan doi:10.1016/j.neuron.2005.04.026 Neuron, Vol. 46, No. 4. (19 May 2005), pp. 681-692. 2006-01-23T11:38:22-00:00 2005 Neuron 46 4 681 692 attention expectation neuromodulation http://www.citeulike.org/user/danpopovici/article/360843 <i>The American Statistician, Vol. 51, No. 1. (1997), pp. 29-31.</i><br /><br />The EM algorithm is a method for producing a sequence of parameter estimates that, under mild regularity conditions, converges to the MLE. The EM algorithm is well regarded, in part because of two monotonicity properties: convergence to the MLE is monotone, and the value of the likelihood function increases with each iteration. A graphical illustration of the EM algorithm makes these properties intuitively apparent in the one-parameter case. In addition, a well-known result regarding the rate of convergence of the algorithm can be inferred. A Graphical Illustration of the EM Algorithm William Navidi The American Statistician, Vol. 51, No. 1. (1997), pp. 29-31. 2005-10-21T17:03:33-00:00 1997 The American Statistician 51 1 29 31 expectation graphical maximization http://www.citeulike.org/user/danpopovici/article/361175 <i>(1997)</i><br /><br />We describe the maximum-likelihood parameter estimation problem and how the ExpectationMaximization (EM) algorithm can be used for its solution. We first describe the abstract form of the EM algorithm as it is often given in the literature. We then develop the EM parameter estimation procedure for two applications: 1) finding the parameters of a mixture of Gaussian densities, and 2) finding the parameters of a hidden Markov model (HMM) (i.e., the Baum-Welch algorithm) for both discrete and... A Gentle Tutorial on the EM Algorithm and its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models J Bilmes (1997) 2005-10-22T03:31:57-00:00 1997 em expectation hmm introduction maximization tutorial http://www.citeulike.org/user/ansobol/article/455237 <i>(3 Jan 2006)</i><br /><br />We introduce a notion of nonlinear expectation --$G$--expectation-- generated by a nonlinear heat equation with infinitesimal generator $G$. We first discuss the notion of $G$--standard normal distribution. With this nonlinear distribution we can introduce our $G$--expectation under which the canonical process is a $G$--Brownian motion. We then establish the related stochastic calculus, especially stochastic integrals of Itô's type with respect to our $G$--Brownian motion and derive the related Itô's formula. We have also give the existence and uniqueness of stochastic differential equation under our $G$--expectation. As compared with our previous framework of $g$--expectations, the theory of $G$--expectation is intrinsic in the sense that it is not based on a given (linear) probability space. $G$--Expectation, $G$--Brownian Motion and Related Stochastic Calculus of Itô's type Shige Peng (3 Jan 2006) 2006-01-04T13:31:19-00:00 2006 brownian-motion expectation nonlinear probability viscosity-solution