We develop logarithmic approximation algorithms for extremely general formulations of multiprocessor multiinterval offline task scheduling to minimize power usage. Here each proce...
We present a unified view of two state-of-theart non-projective dependency parsers, both approximate: the loopy belief propagation parser of Smith and Eisner (2008) and the relaxe...
The paper focuses on the study of solving the large-scale traveling salesman problem (TSP) based on neurodynamic programming. From this perspective, two methods, temporal differenc...
Jia Ma, Tao Yang, Zeng-Guang Hou, Min Tan, Derong ...
We develop a novel mechanism for coordinated, distributed multiagent planning. We consider problems stated as a collection of single-agent planning problems coupled by common soft...
In the typical nonparametric approach to classification in instance-based learning and data mining, random data (the training set of patterns) are collected and used to design a d...
Binay K. Bhattacharya, Kaustav Mukherjee, Godfried...