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394,566
Predicting the Semantic Orientation of Adjectives
, 1997
"... We identify and validate from a large corpus constraints from conjunctions on the positive or negative semantic orientation of the conjoined adjectives. A loglinear regression model uses these constraints to predict whether conjoined adjectives are of same or different orientations, achiev ..."
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Cited by 473 (5 self)
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We identify and validate from a large corpus constraints from conjunctions on the positive or negative semantic orientation of the conjoined adjectives. A loglinear regression model uses these constraints to predict whether conjoined adjectives are of same or different orientations, achiev
Constrained model predictive control: Stability and optimality
 AUTOMATICA
, 2000
"... Model predictive control is a form of control in which the current control action is obtained by solving, at each sampling instant, a finite horizon openloop optimal control problem, using the current state of the plant as the initial state; the optimization yields an optimal control sequence and t ..."
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Cited by 738 (16 self)
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Model predictive control is a form of control in which the current control action is obtained by solving, at each sampling instant, a finite horizon openloop optimal control problem, using the current state of the plant as the initial state; the optimization yields an optimal control sequence
Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
 ARTIF. INTELL
, 1992
"... This paper describes a simple heuristic approach to solving largescale constraint satisfaction and scheduling problems. In this approach one starts with an inconsistent assignment for a set of variables and searches through the space of possible repairs. The search can be guided by a valueorderin ..."
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Cited by 457 (6 self)
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This paper describes a simple heuristic approach to solving largescale constraint satisfaction and scheduling problems. In this approach one starts with an inconsistent assignment for a set of variables and searches through the space of possible repairs. The search can be guided by a value
LinkSharing and Resource Management Models for Packet Networks
, 1995
"... This paper discusses the use of linksharing mechanisms in packet networks and presents algorithms for hierarchical linksharing. Hierarchical linksharing allows multiple agencies, protocol families, or traflic types to share the bandwidth on a tink in a controlled fashion. Linksharing and realt ..."
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Cited by 618 (12 self)
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complementary, constraints at a gateway that can be implemented with a unified set of mechanisms. White it is not possible to completely predict the requirements that might evolve in the Internet over the next decade, we argue that controlled linksharing is an essential component that can provide gateways
Control of Systems Integrating Logic, Dynamics, and Constraints
 Automatica
, 1998
"... This paper proposes a framework for modeling and controlling systems described by interdependent physical laws, logic rules, and operating constraints, denoted as Mixed Logical Dynamical (MLD) systems. These are described by linear dynamic equations subject to linear inequalities involving real and ..."
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Cited by 413 (50 self)
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This paper proposes a framework for modeling and controlling systems described by interdependent physical laws, logic rules, and operating constraints, denoted as Mixed Logical Dynamical (MLD) systems. These are described by linear dynamic equations subject to linear inequalities involving real
Reconciling Schemas of Disparate Data Sources: A MachineLearning Approach
 In SIGMOD Conference
, 2001
"... A dataintegration system provides access to a multitude of data sources through a single mediated schema. A key bottleneck in building such systems has been the laborious manual construction of semantic mappings between the source schemas and the mediated schema. We describe LSD, a system that empl ..."
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Cited by 424 (50 self)
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of information either in the source schemas or in their data. Once the learners have been trained, LSD nds semantic mappings for a new data source by applying the learners, then combining their predictions using a metalearner. To further improve matching accuracy, we extend machine learning techniques so
A hidden Markov model for predicting transmembrane helices in protein sequences
 In Proceedings of the 6th International Conference on Intelligent Systems for Molecular Biology (ISMB
, 1998
"... A novel method to model and predict the location and orientation of alpha helices in membrane spanning proteins is presented. It is based on a hidden Markov model (HMM) with an architecture that corresponds closely to the biological system. The model is cyclic with 7 types of states for helix core, ..."
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Cited by 373 (9 self)
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and constraints involved. Models were estimated both by maximum likelihood and a discriminative method, and a method for reassignment of the membrane helix boundaries were developed. In a cross validated test on single sequences, our transmembrane HMM, TMHMM, correctly predicts the entire topology for 77
What memory is for
, 1997
"... Let’s start from scratch in thinking about what memory is for, and consequently, how it works. Suppose that memory and conceptualization work in the service of perception and action. In this case, conceptualization is the encoding of patterns of possible physical interaction with a threedimensiona ..."
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Cited by 396 (5 self)
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what it means to be related) is determined by how separate patterns of actions can be combined given the constraints of our bodies. I call this combination “mesh. ” To avoid hallucination, conceptualization would normally be driven by the environment, and patterns of action from memory would play a
Posterior Predictive Assessment of Model Fitness Via Realized Discrepancies
 Statistica Sinica
, 1996
"... Abstract: This paper considers Bayesian counterparts of the classical tests for goodness of fit and their use in judging the fit of a single Bayesian model to the observed data. We focus on posterior predictive assessment, in a framework that also includes conditioning on auxiliary statistics. The B ..."
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Cited by 348 (39 self)
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the details of the posterior predictive approach in two problems: estimation in a model with inequality constraints on the parameters, and estimation in a mixture model. In all three examples, standard test statistics (either a χ 2 or a likelihood ratio) are not pivotal: the difficulty is not just how
Selforganisation in a perceptual network
 IEEE Computer
, 1988
"... young animal or child perceives and identifies features in its envi, roument in an apparently effortless way. No presently known algorithms even approach this flexible, generalpurpose perceptual capability. Discovering the principles that may underlie perceptual processing is important both for neu ..."
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Cited by 364 (0 self)
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; and (3) that can lead to profitable experimental programs, testable predictions, and applications to synthetic perception as well as neuroscientific understanding? I believe the answer is yes, and that the use of theoretical neural networks that embody biologicallymotivated rules and constraints is a
Results 1  10
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