Efficient modeling of latent information in supervised learning using gaussian processes
Often in machine learning, data are collected as a combination of multiple conditions, eg, the
voice recordings of multiple persons, each labeled with an ID. How could we build a model
that captures the latent information related to these conditions and generalize to a new one
with few data? We present a new model called Latent Variable Multiple Output Gaussian
Processes (LVMOGP) that allows to jointly model multiple conditions for regression and
generalize to a new condition with a few data points at test time. LVMOGP infers the …
voice recordings of multiple persons, each labeled with an ID. How could we build a model
that captures the latent information related to these conditions and generalize to a new one
with few data? We present a new model called Latent Variable Multiple Output Gaussian
Processes (LVMOGP) that allows to jointly model multiple conditions for regression and
generalize to a new condition with a few data points at test time. LVMOGP infers the …
Efficient modeling of latent information in supervised learning using gaussian processes
A Lopez, Z Dai, ND Lawrence - Advances in Neural …, 2017 - eprints.whiterose.ac.uk
Often in machine learning, data are collected as a combination of multiple conditions, eg, the
voice recordings of multiple persons, each labeled with an ID. How could we build a model
that captures the latent information related to these conditions and generalize to a new one
with few data? We present a new model called Latent Variable Multiple Output Gaussian
Processes (LVMOGP) that allows to jointly model multiple conditions for regression and
generalize to a new condition with a few data points at test time. LVMOGP infers the …
voice recordings of multiple persons, each labeled with an ID. How could we build a model
that captures the latent information related to these conditions and generalize to a new one
with few data? We present a new model called Latent Variable Multiple Output Gaussian
Processes (LVMOGP) that allows to jointly model multiple conditions for regression and
generalize to a new condition with a few data points at test time. LVMOGP infers the …
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