Results 1  10
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5,194
Static Scheduling of Synchronous Data Flow Programs for Digital Signal Processing
 IEEE TRANSACTIONS ON COMPUTERS
, 1987
"... Large grain data flow (LGDF) programming is natural and convenient for describing digital signal processing (DSP) systems, but its runtime overhead is costly in real time or costsensitive applications. In some situations, designers are not willing to squander computing resources for the sake of pro ..."
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Cited by 598 (37 self)
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special case of Petri nets. This selfcontained paper develops the theory necessary to statically schedule SDF programs on single or multiple processors. A class of static (compile time) scheduling algorithms is proven valid, and specific algorithms are given for scheduling SDF systems onto single
Policy gradient methods for reinforcement learning with function approximation.
 In NIPS,
, 1999
"... Abstract Function approximation is essential to reinforcement learning, but the standard approach of approximating a value function and determining a policy from it has so far proven theoretically intractable. In this paper we explore an alternative approach in which the policy is explicitly repres ..."
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Cited by 439 (20 self)
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that the gradient can be written in a form suitable for estimation from experience aided by an approximate actionvalue or advantage function. Using this result, we prove for the first time that a version of policy iteration with arbitrary differentiable function approximation is convergent to a locally optimal
Probabilistic checking of proofs: a new characterization of NP
 JOURNAL OF THE ACM
, 1998
"... We give a new characterization of NP: the class NP contains exactly those languages L for which membership proofs (a proof that an input x is in L) can be verified probabilistically in polynomial time using logarithmic number of random bits and by reading sublogarithmic number of bits from the proof ..."
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Cited by 414 (26 self)
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We give a new characterization of NP: the class NP contains exactly those languages L for which membership proofs (a proof that an input x is in L) can be verified probabilistically in polynomial time using logarithmic number of random bits and by reading sublogarithmic number of bits from
Informationtheoretic metric learning
 in NIPS 2006 Workshop on Learning to Compare Examples
, 2007
"... We formulate the metric learning problem as that of minimizing the differential relative entropy between two multivariate Gaussians under constraints on the Mahalanobis distance function. Via a surprising equivalence, we show that this problem can be solved as a lowrank kernel learning problem. Spe ..."
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Cited by 359 (15 self)
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. Specifically, we minimize the Burg divergence of a lowrank kernel to an input kernel, subject to pairwise distance constraints. Our approach has several advantages over existing methods. First, we present a natural informationtheoretic formulation for the problem. Second, the algorithm utilizes the methods
Analysis of Functional MRI TimeSeries
 HUMAN BRAIN MAPPING
, 1994
"... A method for detecting significant and regionally specific correlations between sensory input and the brain's physiological response, as measured with functional magnetic resonance imaging (MRI), is presented in this paper. The method involves testing for correlations between sensory input and ..."
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Cited by 274 (10 self)
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A method for detecting significant and regionally specific correlations between sensory input and the brain's physiological response, as measured with functional magnetic resonance imaging (MRI), is presented in this paper. The method involves testing for correlations between sensory input
Optimal Designs for SpaceTime Linear Precoders and Decoders
 IEEE Trans. Signal Processing
, 2001
"... In this paper we introduce a new paradigm for the design of transmitter spacetime coding that we refer to as linear precoding. It leads to simple closed form solutions for transmission over frequency selective multipleinput multipleoutput (MIMO) channels, which are scalable with respect to the nu ..."
Abstract

Cited by 197 (6 self)
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In this paper we introduce a new paradigm for the design of transmitter spacetime coding that we refer to as linear precoding. It leads to simple closed form solutions for transmission over frequency selective multipleinput multipleoutput (MIMO) channels, which are scalable with respect
Aggregating inconsistent information: ranking and clustering
, 2005
"... We address optimization problems in which we are given contradictory pieces of input information and the goal is to find a globally consistent solution that minimizes the number of disagreements with the respective inputs. Specifically, the problems we address are rank aggregation, the feedback arc ..."
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Cited by 226 (17 self)
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We address optimization problems in which we are given contradictory pieces of input information and the goal is to find a globally consistent solution that minimizes the number of disagreements with the respective inputs. Specifically, the problems we address are rank aggregation, the feedback arc
Combinatorial pattern discovery in biological sequences: the TEIRESIAS algorithm
 BIOINFORMATICS
, 1998
"... Motivation: The discovery of motifs in biological sequences is an important problem. Results: This paper presents a new algorithm for the discovery of rigid patterns (motifs) in biological sequences. Our method is combinatorial in nature and able to produce all patterns that appear in at least a (us ..."
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Cited by 231 (14 self)
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(userdefined) minimum number of sequences, yet it manages to be very efficient by avoiding the enumeration of the entire pattern space. Furthermore, the reported patterns are maximal: any reported pattern cannot be made more specific and still keep on appearing at the exact same positions within
How to Go Beyond the BlackBox Simulation Barrier
 In 42nd FOCS
, 2001
"... The simulation paradigm is central to cryptography. A simulator is an algorithm that tries to simulate the interaction of the adversary with an honest party, without knowing the private input of this honest party. Almost all known simulators use the adversary’s algorithm as a blackbox. We present t ..."
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Cited by 228 (13 self)
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The simulation paradigm is central to cryptography. A simulator is an algorithm that tries to simulate the interaction of the adversary with an honest party, without knowing the private input of this honest party. Almost all known simulators use the adversary’s algorithm as a blackbox. We present
Keypoint recognition using randomized trees
 IEEE Trans. Pattern Anal. Mach. Intell
"... In many 3–D objectdetection and poseestimation problems, runtime performance is of critical importance. However, there usually is time to train the system, which we will show to be very useful. Assuming that several registered images of the target object are available, we developed a keypointbas ..."
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Cited by 215 (17 self)
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and tracking even under large perspective and scale variations. While earlier methods require a detector that can be expected to produce very repeatable results in general, which usually is very timeconsuming, we simply find the most repeatable object keypoints for the specific target object during
Results 1  10
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5,194