We introduce definitions of computable PAC learning for binary classific...
In this paper, we propose conjugate energy-based models (CEBMs), a new c...
As machine learning is increasingly used in essential systems, it is
imp...
We present a machine-checked, formal proof of PAC learnability of the co...
Recent work has explored transforming data sets into smaller, approximat...
Increasingly, practitioners apply neural networks to complex problems in...
It is time-consuming and error-prone to implement inference procedures f...