Quantum machine learning: a classical perspective
Recently, increased computational power and data availability, as well as algorithmic
advances, have led machine learning (ML) techniques to impressive results in regression …
advances, have led machine learning (ML) techniques to impressive results in regression …
A faster interior point method for semidefinite programming
Semidefinite programs (SDPs) are a fundamental class of optimization problems with
important recent applications in approximation algorithms, quantum complexity, robust …
important recent applications in approximation algorithms, quantum complexity, robust …
[HTML][HTML] Network of time-multiplexed optical parametric oscillators as a coherent Ising machine
Finding the ground states of the Ising Hamiltonian maps to various combinatorial
optimization problems in biology, medicine, wireless communications, artificial intelligence …
optimization problems in biology, medicine, wireless communications, artificial intelligence …
Principles of quantum communication theory: A modern approach
This is a preliminary version of a book in progress on the theory of quantum communication.
We adopt an information-theoretic perspective throughout and give a comprehensive …
We adopt an information-theoretic perspective throughout and give a comprehensive …
A deterministic almost-linear time algorithm for minimum-cost flow
We give a deterministic m^1+o(1) time algorithm that computes exact maximum flows and
minimum-cost flows on directed graphs with m edges and polynomially bounded integral …
minimum-cost flows on directed graphs with m edges and polynomially bounded integral …
A faster cutting plane method and its implications for combinatorial and convex optimization
In this paper we improve upon the running time for finding a point in a convex set given a
separation oracle. In particular, given a separation oracle for a convex set K⊂ R n that is …
separation oracle. In particular, given a separation oracle for a convex set K⊂ R n that is …
[图书][B] Optimization for machine learning
An up-to-date account of the interplay between optimization and machine learning,
accessible to students and researchers in both communities. The interplay between …
accessible to students and researchers in both communities. The interplay between …
Community structure in large networks: Natural cluster sizes and the absence of large well-defined clusters
J Leskovec, KJ Lang, A Dasgupta… - Internet …, 2009 - Taylor & Francis
A large body of work has been devoted to defining and identifying clusters or communities in
social and information networks, ie, in graphs in which the nodes represent underlying …
social and information networks, ie, in graphs in which the nodes represent underlying …
The multiplicative weights update method: a meta-algorithm and applications
Algorithms in varied fields use the idea of maintaining a distribution over a certain set and
use the multiplicative update rule to iteratively change these weights. Their analyses are …
use the multiplicative update rule to iteratively change these weights. Their analyses are …
Statistical properties of community structure in large social and information networks
J Leskovec, KJ Lang, A Dasgupta… - Proceedings of the 17th …, 2008 - dl.acm.org
A large body of work has been devoted to identifying community structure in networks. A
community is often though of as a set of nodes that has more connections between its …
community is often though of as a set of nodes that has more connections between its …