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    NIPS
    2007
    106views Information Technology» more  NIPS 2007»
    Loop Series and Bethe Variational Bounds in Attractive Graphical Models
    14 years 2 months ago
    Loop Series and Bethe Variational Bounds in Attractive Graphical Models
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    Variational methods are frequently used to approximate or bound the partition or likelihood function of a Markov random field. Methods based on mean field theory are guaranteed ...
    Erik B. Sudderth, Martin J. Wainwright, Alan S. Wi...
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    NIPS
    2007
    160views Information Technology» more  NIPS 2007»
    Discriminative Keyword Selection Using Support Vector Machines
    14 years 2 months ago
    Discriminative Keyword Selection Using Support Vector Machines
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    Many tasks in speech processing involve classification of long term characteristics of a speech segment such as language, speaker, dialect, or topic. A natural technique for dete...
    William M. Campbell, Fred S. Richardson
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    NIPS
    2007
    146views Information Technology» more  NIPS 2007»
    Probabilistic Matrix Factorization
    14 years 2 months ago
    Probabilistic Matrix Factorization
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    Many existing approaches to collaborative filtering can neither handle very large datasets nor easily deal with users who have very few ratings. In this paper we present the Prob...
    Ruslan Salakhutdinov, Andriy Mnih
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    NIPS
    2007
    110views Information Technology» more  NIPS 2007»
    Learning to classify complex patterns using a VLSI network of spiking neurons
    14 years 2 months ago
    Learning to classify complex patterns using a VLSI network of spiking neurons
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    We propose a compact, low power VLSI network of spiking neurons which can learn to classify complex patterns of mean firing rates on–line and in real–time. The network of int...
    Srinjoy Mitra, Giacomo Indiveri, Stefano Fusi
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    NIPS
    2007
    173views Information Technology» more  NIPS 2007»
    A Constraint Generation Approach to Learning Stable Linear Dynamical Systems
    14 years 2 months ago
    A Constraint Generation Approach to Learning Stable Linear Dynamical Systems
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    Stability is a desirable characteristic for linear dynamical systems, but it is often ignored by algorithms that learn these systems from data. We propose a novel method for learn...
    Sajid M. Siddiqi, Byron Boots, Geoffrey J. Gordon
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    NIPS
    2007
    119views Information Technology» more  NIPS 2007»
    Hierarchical Penalization
    14 years 2 months ago
    Hierarchical Penalization
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    Hierarchical penalization is a generic framework for incorporating prior information in the fitting of statistical models, when the explicative variables are organized in a hiera...
    Marie Szafranski, Yves Grandvalet, Pierre Morizet-...
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    NIPS
    2007
    103views Information Technology» more  NIPS 2007»
    Sparse deep belief net model for visual area V2
    14 years 2 months ago
    Sparse deep belief net model for visual area V2
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    Honglak Lee, Chaitanya Ekanadham, Andrew Y. Ng
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    NIPS
    2007
    138views Information Technology» more  NIPS 2007»
    Bayesian Agglomerative Clustering with Coalescents
    14 years 2 months ago
    Bayesian Agglomerative Clustering with Coalescents
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    We introduce a new Bayesian model for hierarchical clustering based on a prior over trees called Kingman’s coalescent. We develop novel greedy and sequential Monte Carlo inferen...
    Yee Whye Teh, Hal Daumé III, Daniel M. Roy
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    NIPS
    2007
    173views Information Technology» more  NIPS 2007»
    HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation
    14 years 2 months ago
    HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation
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    We present a novel paradigm for statistical machine translation (SMT), based on a joint modeling of word alignment and the topical aspects underlying bilingual document-pairs, via...
    Bing Zhao, Eric P. Xing
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    NIPS
    2007
    147views Information Technology» more  NIPS 2007»
    An in-silico Neural Model of Dynamic Routing through Neuronal Coherence
    14 years 2 months ago
    An in-silico Neural Model of Dynamic Routing through Neuronal Coherence
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    We describe a neurobiologically plausible model to implement dynamic routing using the concept of neuronal communication through neuronal coherence. The model has a three-tier arc...
    Devarajan Sridharan, Brian Percival, John V. Arthu...
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