Abstract Model complexity is a fundamental problem in deep learning. In this paper, we
conduct a systematic overview of the latest studies on model complexity in deep learning …

Quantum learning theory is a new and very active area of research at the intersection of
quantum computing and machine learning. Important breakthroughs in the past two years …

This beginning graduate textbook describes both recent achievements and classical results
of computational complexity theory. Requiring essentially no background apart from …

We use quantum walks to construct a new quantum algorithm for element distinctness and
its generalization. For element distinctness (the problem of finding two equal items among N …

We examine the number of queries to input variables that a quantum algorithm requires to
compute Boolean functions on {0, 1} N in the black-box model. We show that the exponential …

In this paper, we show that every (2^n-1+1)-vertex induced subgraph of the n-dimensional
cube graph has maximum degree at least n. This is the best possible result, and it improves …

We show the following hold, unconditionally unless otherwise stated, relative to a random
oracle:—There are NP search problems solvable by quantum polynomial-time (QPT) …

Boolean circuit complexity is the combinatorics of computer science and involves many
intriguing problems that are easy to state and explain, even for the layman. This book is a …

Blockchain has recently gained momentum. Startups, enterprises, banks, and government
agencies around the world are exploring the use of blockchain for broad applications …

Unmanned aerial vehicles (UAVs) are an emerging technology in the 5G-and-beyond
systems with the promise of assisting cellular communications and supporting IoT …