… Throughout the paper, when referring to a monotonic classifier, this signifies a fully monotonic
classifier. In addition, the interaction with a classifier is restricted to computing the value of …

… To achieve the goal, we utilize techniques for learning monotone Boolean functions. While
there … the problem of interactive learning of a monotone Boolean function from the complexity …

… of inferring the interaction network and the underlying functions simultaneously, accurately,
and … From application of our automated Boolean function learning method (results shown in …

… Second, for the broad class of Fourier-sparse boolean functions, we show a multi-round (IP-…
class Td, in which each function is a concatenation of d monotone increasing thresholds. A …

… interaction between mutations in model genes (gain of Notch … monotonic whenever each
of its local functions is monotonic (… To test the impact of alternative Boolean functions, we …

… learning to measure the performance of a learning algorithm. In the classical single-agent
setting, online learning considers the following repeated interaction … selects a loss function ft(·), …

… as the deviation from a continuous additive regression function, then their … interaction via
the noncontinuous Boolean functions in the LSS model, and we derive consistent interaction …

… However, the mechanism of this interaction – the underlying game that specifies how a
player’s … learning (and online learning in particular), which aims to develop single-agent online …

… of canalization: any Boolean function can be written as a … the canalizing layers of a Boolean
function. First, we show that the … monotonic relationship appears for n ≥ 3 : there exist fewer …

… The transition functions, derived interaction graph, and state transition graphs according to
… evaluation of all the possible transition functions by learning from conflicts: whenever it finds …