  The regions around the celestial poles offer the ability to find and
characterize long-term variables from ground-based observatories. We used
multi-year Evryscope data to search for high-amplitude (~5% or greater)
variable objects among 160,000 bright stars (Mv < 14.5) near the South
Celestial Pole. We developed a machine learning based spectral classifier to
identify eclipse and transit candidates with M-dwarf or K-dwarf host stars -
and potential low-mass secondary stars or gas giant planets. The large
amplitude transit signals from low-mass companions of smaller dwarf host stars
lessens the photometric precision and systematics removal requirements
necessary for detection, and increases the discoveries from long-term
observations with modest light curve precision. The Evryscope is a robotic
telescope array that observes the Southern sky continuously at 2-minute
cadence, searching for stellar variability, transients, transits around exotic
stars and other observationally challenging astrophysical variables. In this
study, covering all stars 9 < Mv < 14.5, in declinations -75 to -90 deg, we
recover 346 known variables and discover 303 new variables, including 168
eclipsing binaries. We characterize the discoveries and provide the amplitudes,
periods, and variability type. A 1.7 Jupiter radius planet candidate with a
late K-dwarf primary was found and the transit signal was verified with the
PROMPT telescope network. Further followup revealed this object to be a likely
grazing eclipsing binary system with nearly identical primary and secondary K5
stars. Radial velocity measurements from the Goodman Spectrograph on the 4.1
meter SOAR telescope of the likely-lowest-mass targets reveal that six of the
eclipsing binary discoveries are low-mass (.06 - .37 solar mass) secondaries
with K-dwarf primaries, strong candidates for precision mass-radius
measurements.
