activity
20212024
most citedLoad-balanced Gather-scatter Patterns for Sparse Deep Neural Networks

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.RO2024

Distributed Invariant Kalman Filter for Object-level Multi-robot Pose SLAM

Haoying Li, Qingcheng Zeng, Haoran Li +2

Cooperative localization and target tracking are essential for multi-robot systems to implement high-level tasks. To this end, we propose a distributed invariant Kalman filter base…

cs.AI2024

FM3Q: Factorized Multi-Agent MiniMax Q-Learning for Two-Team Zero-Sum Markov Game

Guangzheng Hu, Yuanheng Zhu, Haoran Li +1

Many real-world applications involve some agents that fall into two teams, with payoffs that are equal within the same team but of opposite sign across the opponent team. The so-ca…

cs.AI2023

General Method for Solving Four Types of SAT Problems

Anqi Li, Congying Han, Tiande Guo +2

Existing methods provide varying algorithms for different types of Boolean satisfiability problems (SAT), lacking a general solution framework. Accordingly, this study proposes a u…

math.OC2023

Policy Optimization of Finite-Horizon Kalman Filter with Unknown Noise Covariance

Haoran Li, Yuan-Hua Ni

This paper is on learning the Kalman gain by policy optimization method. Firstly, we reformulate the finite-horizon Kalman filter as a policy optimization problem of the dual syste…

cs.LG20211 cited

Load-balanced Gather-scatter Patterns for Sparse Deep Neural Networks

Fei Sun, Minghai Qin, Tianyun Zhang +6

Deep neural networks (DNNs) have been proven to be effective in solving many real-life problems, but its high computation cost prohibits those models from being deployed to edge de…