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    NIPS
    2008
    142views Information Technology» more  NIPS 2008»
    Bayesian Synchronous Grammar Induction
    13 years 6 months ago
    Bayesian Synchronous Grammar Induction
    Download  homepages.inf.ed.ac.uk
    We present a novel method for inducing synchronous context free grammars (SCFGs) from a corpus of parallel string pairs. SCFGs can model equivalence between strings in terms of su...
    Phil Blunsom, Trevor Cohn, Miles Osborne
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    NIPS
    2008
    166views Information Technology» more  NIPS 2008»
    Asynchronous Distributed Learning of Topic Models
    13 years 6 months ago
    Asynchronous Distributed Learning of Topic Models
    Download  www.datalab.uci.edu
    Distributed learning is a problem of fundamental interest in machine learning and cognitive science. In this paper, we present asynchronous distributed learning algorithms for two...
    Arthur Asuncion, Padhraic Smyth, Max Welling
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    NIPS
    2008
    135views Information Technology» more  NIPS 2008»
    High-dimensional support union recovery in multivariate regression
    13 years 6 months ago
    High-dimensional support union recovery in multivariate regression
    Download  www.cs.berkeley.edu
    We study the behavior of block 1/ 2 regularization for multivariate regression, where a K-dimensional response vector is regressed upon a fixed set of p covariates. The problem of...
    Guillaume Obozinski, Martin J. Wainwright, Michael...
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    NIPS
    2008
    164views Information Technology» more  NIPS 2008»
    Estimating Robust Query Models with Convex Optimization
    13 years 6 months ago
    Estimating Robust Query Models with Convex Optimization
    Download  research.microsoft.com
    Query expansion is a long-studied approach for improving retrieval effectiveness by enhancing the user's original query with additional related words. Current algorithms for ...
    Kevyn Collins-Thompson
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    NIPS
    2008
    232views Information Technology» more  NIPS 2008»
    Sparse Signal Recovery Using Markov Random Fields
    13 years 6 months ago
    Sparse Signal Recovery Using Markov Random Fields
    Download  www.ece.rice.edu
    Compressive Sensing (CS) combines sampling and compression into a single subNyquist linear measurement process for sparse and compressible signals. In this paper, we extend the th...
    Volkan Cevher, Marco F. Duarte, Chinmay Hegde, Ric...
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    NIPS
    2008
    127views Information Technology» more  NIPS 2008»
    On the Generalization Ability of Online Strongly Convex Programming Algorithms
    13 years 6 months ago
    On the Generalization Ability of Online Strongly Convex Programming Algorithms
    Download  ttic.uchicago.edu
    This paper examines the generalization properties of online convex programming algorithms when the loss function is Lipschitz and strongly convex. Our main result is a sharp bound...
    Sham M. Kakade, Ambuj Tewari
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    NIPS
    2008
    134views Information Technology» more  NIPS 2008»
    QUIC-SVD: Fast SVD Using Cosine Trees
    13 years 6 months ago
    QUIC-SVD: Fast SVD Using Cosine Trees
    Download  fodava.gatech.edu
    The Singular Value Decomposition is a key operation in many machine learning methods. Its computational cost, however, makes it unscalable and impractical for applications involvi...
    Michael P. Holmes, Alexander G. Gray, Charles Lee ...
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    NIPS
    2008
    133views Information Technology» more  NIPS 2008»
    Sparse Online Learning via Truncated Gradient
    13 years 6 months ago
    Sparse Online Learning via Truncated Gradient
    Download  jmlr.csail.mit.edu
    We propose a general method called truncated gradient to induce sparsity in the weights of onlinelearning algorithms with convex loss functions. This method has several essential ...
    John Langford, Lihong Li, Tong Zhang
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    NIPS
    2008
    185views Information Technology» more  NIPS 2008»
    Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data
    13 years 6 months ago
    Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data
    Download  www.computing.edu.au
    Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
    Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svet...
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    NIPS
    2008
    148views Information Technology» more  NIPS 2008»
    Syntactic Topic Models
    13 years 6 months ago
    Syntactic Topic Models
    Download  www.cs.princeton.edu
    We develop the syntactic topic model (STM), a nonparametric Bayesian model of parsed documents. The STM generates words that are both thematically and syntactically constrained, w...
    Jordan L. Boyd-Graber, David M. Blei
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