In this paper, we define a family of syntactic kernels for automatic relational learning from pairs of natural language sentences. We provide an efficient computation of such mode...
Large-scale logistic regression arises in many applications such as document classification and natural language processing. In this paper, we apply a trust region Newton method t...
We address classification problems for which the training instances are governed by a distribution that is allowed to differ arbitrarily from the test distribution--problems also ...
We propose an analytic moment-based filter for nonlinear stochastic dynamic systems modeled by Gaussian processes. Exact expressions for the expected value and the covariance matr...
Marc Peter Deisenroth, Marco F. Huber, Uwe D. Hane...
We present an on-line learning framework tailored towards real-time learning from observed user behavior in search engines and other information retrieval systems. In particular, ...