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129,169
SIGNAL RECOVERY BY PROXIMAL FORWARDBACKWARD SPLITTING
 MULTISCALE MODEL. SIMUL. TO APPEAR
"... We show that various inverse problems in signal recovery can be formulated as the generic problem of minimizing the sum of two convex functions with certain regularity properties. This formulation makes it possible to derive existence, uniqueness, characterization, and stability results in a unifi ..."
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Cited by 509 (24 self)
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unified and standardized fashion for a large class of apparently disparate problems. Recent results on monotone operator splitting methods are applied to establish the convergence of a forwardbackward algorithm to solve the generic problem. In turn, we recover, extend, and provide a simplified analysis
An analysis of transformations
 Journal of the Royal Statistical Society. Series B (Methodological
, 1964
"... In the analysis of data it is often assumed that observations y,, y,,...,y, are independently normally distributed with constant variance and with expectations specified by a model linear in a set of parameters 0. In this paper we make the less restrictive assumption that such a normal, homoscedasti ..."
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Cited by 1067 (3 self)
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In the analysis of data it is often assumed that observations y,, y,,...,y, are independently normally distributed with constant variance and with expectations specified by a model linear in a set of parameters 0. In this paper we make the less restrictive assumption that such a normal
Probabilistic Principal Component Analysis
 JOURNAL OF THE ROYAL STATISTICAL SOCIETY, SERIES B
, 1999
"... Principal component analysis (PCA) is a ubiquitous technique for data analysis and processing, but one which is not based upon a probability model. In this paper we demonstrate how the principal axes of a set of observed data vectors may be determined through maximumlikelihood estimation of paramet ..."
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Cited by 709 (5 self)
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Principal component analysis (PCA) is a ubiquitous technique for data analysis and processing, but one which is not based upon a probability model. In this paper we demonstrate how the principal axes of a set of observed data vectors may be determined through maximumlikelihood estimation
Perspectives on Program Analysis
, 1996
"... eing analysed. On the negative side, the semantic correctness of the analysis is seldom established and therefore there is often no formal justification for the program transformations for which the information is used. The semantics based approach [1; 5] is often based on domain theory in the form ..."
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Cited by 685 (35 self)
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, and for neededness analysis it might perform a strictness analysis and use the strictness information for neededness (or make use of the "absence" notion from projection analysis and attempt to discover the di#erence). On the positive side, this usually gives rise to provably correct analyses, although
The algorithmic analysis of hybrid systems
 THEORETICAL COMPUTER SCIENCE
, 1995
"... We present a general framework for the formal specification and algorithmic analysis of hybrid systems. A hybrid system consists of a discrete program with an analog environment. We model hybrid systems as nite automata equipped with variables that evolve continuously with time according to dynamica ..."
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Cited by 778 (71 self)
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We present a general framework for the formal specification and algorithmic analysis of hybrid systems. A hybrid system consists of a discrete program with an analog environment. We model hybrid systems as nite automata equipped with variables that evolve continuously with time according
Analysis of Recommendation Algorithms for ECommerce
, 2000
"... Recommender systems apply statistical and knowledge discovery techniques to the problem of making product recommendations during a live customer interaction and they are achieving widespread success in ECommerce nowadays. In this paper, we investigate several techniques for analyzing largescale pu ..."
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Cited by 523 (22 self)
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scale purchase and preference data for the purpose of producing useful recommendations to customers. In particular, we apply a collection of algorithms such as traditional data mining, nearestneighbor collaborative ltering, and dimensionality reduction on two dierent data sets. The rst data set was derived from
Indexing by latent semantic analysis
 JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE
, 1990
"... A new method for automatic indexing and retrieval is described. The approach is to take advantage of implicit higherorder structure in the association of terms with documents (“semantic structure”) in order to improve the detection of relevant documents on the basis of terms found in queries. The p ..."
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Cited by 3779 (35 self)
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. The particular technique used is singularvalue decomposition, in which a large term by document matrix is decomposed into a set of ca. 100 orthogonal factors from which the original matrix can be approximated by linear combination. Documents are represented by ca. 100 item vectors of factor weights. Queries
Some methods for classification and analysis of multivariate observations
 In 5th Berkeley Symposium on Mathematical Statistics and Probability
, 1967
"... The main purpose of this paper is to describe a process for partitioning an Ndimensional population into k sets on the basis of a sample. The process, which is called 'kmeans, ' appears to give partitions which are reasonably ..."
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Cited by 3055 (3 self)
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The main purpose of this paper is to describe a process for partitioning an Ndimensional population into k sets on the basis of a sample. The process, which is called 'kmeans, ' appears to give partitions which are reasonably
Pointsto Analysis in Almost Linear Time
, 1996
"... We present an interprocedural flowinsensitive pointsto analysis based on type inference methods with an almost linear time cost complexity. To our knowledge, this is the asymptotically fastest nontrivial interprocedural pointsto analysis algorithm yet described. The algorithm is based on a nons ..."
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Cited by 595 (3 self)
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We present an interprocedural flowinsensitive pointsto analysis based on type inference methods with an almost linear time cost complexity. To our knowledge, this is the asymptotically fastest nontrivial interprocedural pointsto analysis algorithm yet described. The algorithm is based on a non
On the Use of Windows for Harmonic Analysis With the Discrete Fourier Transform
 Proc. IEEE
, 1978
"... AhmwThis Pw!r mak = available a concise review of data win compromise consists of applying windows to the sampled daws pad the ^ affect On the Of in the data set, or equivalently, smoothing the spectral samples. '7 of aoise9 m the ptesence of sdroag bar The two operations to which we subject ..."
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Cited by 668 (0 self)
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AhmwThis Pw!r mak = available a concise review of data win compromise consists of applying windows to the sampled daws pad the ^ affect On the Of in the data set, or equivalently, smoothing the spectral samples. '7 of aoise9 m the ptesence of sdroag bar The two operations to which we
Results 1  10
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129,169