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Exceeding the Dataflow Limit via Value Prediction
"... advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works, must be obtained from the IEEE. Contact: Manager, Copyright and Permissions/ ..."
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advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works, must be obtained from the IEEE. Contact: Manager, Copyright and Permissions/
Exceeding the Dataflow Limit via Value Prediction
"... advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works, must be obtained from the IEEE. Contact: Manager, Copyright and Permissions/ ..."
Abstract
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advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works, must be obtained from the IEEE. Contact: Manager, Copyright and Permissions/
The synchronous dataflow programming language LUSTRE
 Proceedings of the IEEE
, 1991
"... This paper describes the language Lustre, which is a dataflow synchronous language, designed for programming reactive systems  such as automatic control and monitoring systems  as well as for describing hardware. The dataflow aspect of Lustre makes it very close to usual description tools in t ..."
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Cited by 647 (53 self)
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This paper describes the language Lustre, which is a dataflow synchronous language, designed for programming reactive systems  such as automatic control and monitoring systems  as well as for describing hardware. The dataflow aspect of Lustre makes it very close to usual description tools
Interprocedural dataflow analysis via graph reachability
, 1994
"... The paper shows how a large class of interprocedural dataflowanalysis problems can be solved precisely in polynomial time by transforming them into a special kind of graphreachability problem. The only restrictions are that the set of dataflow facts must be a finite set, and that the dataflow fun ..."
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Cited by 454 (34 self)
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The paper shows how a large class of interprocedural dataflowanalysis problems can be solved precisely in polynomial time by transforming them into a special kind of graphreachability problem. The only restrictions are that the set of dataflow facts must be a finite set, and that the dataflow
Predictive reward signal of dopamine neurons
 Journal of Neurophysiology
, 1998
"... Schultz, Wolfram. Predictive reward signal of dopamine neurons. is called rewards, which elicit and reinforce approach behavJ. Neurophysiol. 80: 1–27, 1998. The effects of lesions, receptor ior. The functions of rewards were developed further during blocking, electrical selfstimulation, and drugs ..."
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Cited by 717 (12 self)
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environmental stimuli with appe Despite their importance, rewards do not influence the brain titive value, predict and detect rewards and signal alerting and motivating events. By failing to discriminate between different
Regression Shrinkage and Selection Via the Lasso
 Journal of the Royal Statistical Society, Series B
, 1994
"... We propose a new method for estimation in linear models. The "lasso" minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant. Because of the nature of this constraint it tends to produce some coefficients that are exactl ..."
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Cited by 4055 (51 self)
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We propose a new method for estimation in linear models. The "lasso" minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant. Because of the nature of this constraint it tends to produce some coefficients
Solving multiclass learning problems via errorcorrecting output codes
 JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
, 1995
"... Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass l ..."
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Cited by 730 (8 self)
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Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass
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 696 (15 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
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