NIPS
2007
14 years 1 months ago
2007
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...
NIPS
2007
14 years 1 months ago
2007
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...
NIPS
2007
14 years 1 months ago
2007
NIPS
2007
14 years 1 months ago
2007
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...
NIPS
2007
14 years 1 months ago
2007
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...
NIPS
2007
14 years 1 months ago
2007
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...
NIPS
2007
14 years 1 months ago
2007
This paper studies boosting algorithms that make a single pass over a set of base classifiers. We first analyze a one-pass algorithm in the setting of boosting with diverse base...
NIPS
2007
14 years 1 months ago
2007
We propose a novel method for linear dimensionality reduction of manifold modeled data. First, we show that with a small number M of random projections of sample points in RN belo...
NIPS
2007
14 years 1 months ago
2007
In many applications, one has to actively select among a set of expensive observations before making an informed decision. Often, we want to select observations which perform well...
NIPS
2007
14 years 1 months ago
2007
Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...