is the leading alternative, other approaches include distance-based methods that use transformed or inferred distances, for example, logdet/paralinear distances (see Nevertheless, ML methodology enjoys far from universal acceptance. Objections to ML include the following: Concern about the validity and exact

' decisions about effort. One channel is information. In a private-good context without image concerns and in which the principal is better informed than the agent, the principal chooses a reward level based on several factors, including how the principal views the difficulty 4 or attractiveness

into the partonomy tree (as a “Classification ” branch) in a way that allows us to directly reuse our partonomy similarity algorithm and to permit weighted (or 'fuzzy') taxonomic subsumption with no added effort. Second, leaf nodes can be typed and each type is associated with a local, special

We present deep Keck spectroscopy for a sample of I814 < 22.5 field early-type galaxies selected morphologically in the redshift range 0.56 ≤ z ≤ 1.02 in the Hubble Deep Field North (HDF-N). Using velocity dispersions determined from the Keck spectra in conjunction with structural parameters

We propose a programming model where effects are treated in a disciplined way, and where the potential side-effects of a function are apparent in its type signature. The type and effect of expres-sions can also be inferred automatically, and we describe a polymorphic type inference system based

was observed within 4 days, with between 20% and 52% of the macrofauna displaying evidence of enrichment. However, incorporation levels of both diatom C and cocco N were low (,0.05% and 0.005% of the added C and N). Incorporation of labelled diatoms was similar during both June and September suggesting

. Python is an easy language to learn and also includes modern programming approaches such as objects. It can be used via scripts and also interactively as a command-line program, similar to MATLAB The goals of this first workshop are (1) to have you learn to use PyRosetta both interactively and by writing

We propose a programming model where effects are treated in a disciplined way, and where the potential side-effects of a function are apparent in its type signature. The type and effect of expres-sions can also be inferred automatically, and we describe a polymorphic type inference system based

been advanced to explain the manner in which hu-mans learn to categorize objects. It has been variously suggested that the underlying prin-ciple might be the similarity structure of objects [1], the manipulability of decision bound~ aries [2], or Bayesian inference [3][4]. While many of these theories

Abstract: Online learning initia-tives over the past decade have become increasingly comprehen-sive in their selection of courses and sophisticated in their presen-tation, culminating in the recent announcement of a number of consortium and startup activities that promise to make a university