D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems

no code implementations • 28 Nov 2019 • Taoxing Pan, Jun Liu, Jie Wang

To the best of our knowledge, D-SPIDER-SFO achieves the state-of-the-art performance for solving nonconvex optimization problems on decentralized networks in terms of the computational cost.

Technical Report of Team GraphMIRAcles in the WikiKG90M-LSC Track of OGB-LSC @ KDD Cup 2021

no code implementations • 12 Jul 2021 • Jianyu Cai, Jiajun Chen, Taoxing Pan, Zhanqiu Zhang, Jie Wang

To address this challenge, we propose a framework that integrates three components -- a basic model ComplEx-CMRC, a rule miner AMIE 3, and an inference model to predict missing links.

Knowledge Distillation Knowledge Graphs +1

Efficient Exploration in Resource-Restricted Reinforcement Learning

no code implementations • 14 Dec 2022 • Zhihai Wang, Taoxing Pan, Qi Zhou, Jie Wang

In many real-world applications of reinforcement learning (RL), performing actions requires consuming certain types of resources that are non-replenishable in each episode.

Efficient Exploration reinforcement-learning +1