Browsing FAS Scholarly Articles by Title
Now showing items 8747-8766 of 18292
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Learning and Decision-Making for Intention Reconciliation
(Association for Computing Machinery, 2002)Rational, autonomous agents must be able to revise their commitments in the light of new opportunities. They must decide when to default on commitments to the group in order to commit to potentially more valuable outside ... -
Learning and Equilibrium
(Annual Reviews, 2009)The theory of learning in games studies how, which and what kind of equilibria might arise as a consequence of a long-run non-equilibrium process of learning, adaptation and/or imitation. If agents’ strategies are completely ... -
Learning and Solving Many-Player Games Through a Cluster-Based Representation
(Association for Uncertainty in Artificial Intelligence, 2008)In addressing the challenge of exponential scaling with the number of agents we adopt a cluster-based representation to approximately solve asymmetric games of very many players. A cluster groups together agents with a ... -
A learning approach to improving sentence-level MT evaluation
(European Association for Machine Translation, 2004)The problem of evaluating machine translation (MT) systems is more challenging than it may first appear, as diverse translations can often be considered equally correct. The task is even more difficult when practical ... -
Learning from Private Information in Noisy Repeated Games
(Elsevier, 2011)We study the perfect type-contingently public ex-post equilibrium (PTXE) of repeated games where players observe imperfect public signals of the actions played, and both the payoff functions and the map from actions to ... -
Learning From The Crisis: A Talk in Honor of Lucas Papademos
(European Central Bank, 2012) -
Learning From The Crisis: What Can Central Banks Do?
(Academic Foundation in association with Reserve Bank of India, 2010) -
Learning from the Crowd: Observational Learning in Crowdsourcing Communities
(ACM, 2016)Crowd work provides solutions to complex problems effectively, efficiently, and at low cost. Previous research showed that feedback, particularly correctness feedback can help crowd workers improve their performance; yet ... -
Learning from the Past
(Cambridge University Press, 2002) -
Learning Generic Prior Models for Visual Computation
(Institute of Electrical and Electronics Engineers, 1997)This paper presents a novel theory for learning generic prior models from a set of observed natural images based on a minimax entropy theory that the authors studied in modeling textures. We start by studying the statistics ... -
Learning in the Life of a French Nobleman: Nicolas De Livre, Friend of Jean Bodin
Starting with Donald Kelley's Foundations of Modern Historical Scholarship (1970), a number of important studies over the last thirty years have painted a rich picture of the cultural activities and self-conceptions of ... -
Learning is Change in Knowledge: Knowledge-based Security for Dynamic Policies
(2012)In systems that handle confidential information, the security policy to enforce on information frequently changes: new users join the system, old users leave, and sensitivity of data changes over time. It is challenging, ... -
Learning Mathematics in a Visuo-Spatial Format: A Randomized, Controlled Trial of Mental Abacus Instruction
(Center for Open Science, 2016-09-08)Mental abacus (MA) is a technique of performing fast, accurate arithmetic using a mental image of an abacus; experts exhibit astonishing calculation abilities. Over 3 years, 204 elementary school students (age range at ... -
Learning More by Crossing Levels: Evidence from Airplanes, Hospitals, and Orchestras
(John Wiley & Sons, Ltd., 2003)Scholars generally conduct research at a single level of analysis (such as the individual, the group, or the organization level), although they often turn to the next-lower level for explanatory mechanisms. I suggest that ... -
Learning Neural Templates for Text Generation
(Association for Computational Linguistics, 2018-10)While neural, encoder-decoder models have had significant empirical success in text generation, there remain several unaddressed problems with this style of generation. Encoder-decoder models are largely (a) uninterpretable, ... -
Learning Outcome-Discriminative Dynamics in Multivariate Physiological Cohort Time Series
(Institute of Electrical and Electronics Engineers, 2013)Model identification for physiological systems is complicated by changes between operating regimes and measurement artifacts. We present a solution to these problems by assuming that a cohort of physiological time series ... -
Learning Silhouette Features for Control of Human Motion
(Association for Computing Machinery, 2005)We present a vision-based performance interface for controlling animated human characters. The system interactively combines information about the user's motion contained in silhouettes from three viewpoints with domain ... -
Learning Social Preferences in Games
(Assocation for the Advancement of Artifical Intelligence, 2004)This paper presents a machine-learning approach to modeling human behavior in one-shot games. It provides a framework for representing and reasoning about the social factors that affect people’s play. The model predicts ... -
Learning Structural Element Patch Models with Hierarchical Palettes
(Institute of Electrical and Electronics Engineers, 2012)Image patches can be factorized into 'shapelets' that describe segmentation patterns called structural elements (stels), and palettes that describe how to paint the shapelets. We introduce local palettes for patches, global ...