  The optical, full-phase photometric variations of a short-period planet
provide a unique view of the planet's atmospheric composition and dynamics. The
number of planets with optical phase curve detections, however, is currently
too small to study them as an aggregate population, motivating an extension of
the search to non-transiting planets. Here we present an algorithm for the
detection of non-transiting, short-period giant planets in the Kepler field.
The procedure uses the phase curves themselves as evidence for the planets'
existence. We employ a supervised learning algorithm to recognize the salient
time-dependent properties of synthetic phase curves; we then search for
detections of signals that match these properties. After demonstrating the
algorithm's capabilities, we classify 142,630 FGK Kepler stars without
confirmed planets or KOIs and, for each one, assign a probability of a phase
curve of a non-transiting planet being present. We identify 60 high-probability
non-transiting hot Jupiter candidates. We also derive constraints on the
candidates' albedos and offsets of the phase curve maxima. These targets are
strong candidates for follow-up radial velocity confirmation and
characterization. Once confirmed, the atmospheric information content in the
phase curves may be studied in yet greater detail.
