The stochastic block model (SBM) is a random graph model with planted clusters. It is widely
employed as a canonical model to study clustering and community detection, and provides …

The combination of the compactness of networks, featuring small diameters, and their
complex architectures results in a variety of critical effects dramatically different from those in …

New phase transition phenomena have recently been discovered for the stochastic block
model, for the special case of two non-overlapping symmetric communities. This gives raise …

There is an increasing interest in quantum algorithms for problems of integer programming
and combinatorial optimization. Classical solvers for such problems employ relaxations …

The rationality principle postulates that decision-makers always choose the best action
available to them. It underlies most modern theories of decision-making. The principle does …

The algorithm selection problem [Rice 1976] seeks to answer the question: Which algorithm
is likely to perform best for my problem? Recognizing the problem as a learning task in the …

Handbook of Knowledge Representation describes the essential foundations of Knowledge
Representation, which lies at the core of Artificial Intelligence (AI). The book provides an up …

In the last few decades, evolutionary algorithms have emerged as a revolutionary approach
for solving search and optimization problems involving multiple conflicting objectives …

An instance of a random constraint satisfaction problem defines a random subset 𝒮 (the set
of solutions) of a large product space XN (the set of assignments). We consider two …

We introduce a new approach to proving that a sequence of deterministic linear codes
achieves capacity on an erasure channel under maximum a posteriori decoding. Rather …