An out-patient note-book may be made valuable when there is time and efficient assistance to record cases; but single-handed, and with a large number of patients, this is not always possible. Nevertheless, I venture to hope that the following imperfect notes, pf two or three cases out of many, may be useful in drawing attention to one of the minor ailments of life, under cover of which there ma...

Four advanced breeding lines of wheat which had appeared to be resistant to stripe rust in the past years along with a susceptible variety, Bolani, were intercrossed in all combinations of a half-diallel design. Seedlings were grown in greenhouse until the first leaves fully expanded and then inoculated with two pathotypes (races) 6E134A+ and 134E148A+, separately. Days to the first pustule eru...

We consider a multi-armed bandit problem where the reward distributions are indexed by two sets –one for arms, one for type– and can be partitioned into a small number of clusters according to the type. First, we consider the setting where all reward distributions are known and all types have the same underlying cluster, the type’s identity is, however, unknown. Second, we study the case where ...

We present a method that can evaluate a RANSAC hypothesis in constant time, i.e. independent of the size of the data. A key observation here is that correct hypotheses are tightly clustered together in the latent parameter domain. In a manner similar to the generalized Hough transform we seek to find this cluster, only that we need as few as two votes for a successful detection. Rapidly locatin...

Latent variables often play an important role in improving the quality of the learned Bayesian networks and understanding the nature of interactions in the model. The dimensionality of latent variables has significant effect on the representation quality and complexity of the model. The maximum possible dimensionality of a latent variable is a Cartesian product of the state space of its Markov ...

A large body of recent work has focused on methods for identifying lowdimensional latent structure in multi-neuron spike train data. Most such methods have employed either linear latent dynamics or linear (or log-linear) mappings from a latent space to spike rates. Here we propose a doubly nonlinear latent variable model for population spike trains that can identify nonlinear low-dimensional st...