Posts by Collection

MUAX

Autonomous Learning of Physical Environment through Neural Tree Search

Proposed a MCTS-based reinforcement learning algorithm to perform active slam.

Temporal Graph Attention Network Prediction on Ethereum Transaction Cost and Analysis on ‘The Merge’

Proposed a GNN model based on temporal transaction network to predict Ethereum Transaction Cost

Light Attention Vision Modules for Atari

Propose an attention-based vision policy that can play Atari games based on pixel input.

Reinforcement Learning for Goal-based Wealth Management: A study of behavior improvement through approximation and reward engineering

Proposed a reward engineering method and leveraged function approximation for value function.

Learn to Tour: Operator Design For Feasible Solution Mapping

Published in , 2023

We design learning operators that always map one feasible solution to another, without wasting time exploring the infeasible solution space. Such operators are evaluated and selected as policies to solve PDTSPs in an RL framework.

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Plan and learn to Map for Joint SLAM and Navigation

Published in , 2023

Proposed end-to-end MCTS with encoder-decoder architecture that generates and works on interpretable hidden state.

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Talk on Learn to Tour：Operator Design for Solution Feasibility Mapping

Published: October 15, 2023

session: OR via Reinforcement Learning and Beyond, INFORMS 2023

Graduate Optimization Models and Methods, Teaching Assistant

Graduate course, Columbia University, IEOR, 2023

Take the role of Teaching Assistant for Graduate Optimization Models and Methods, topics include linear programming, the simplex method, duality, nonlinear, integer and dynamic programming. Duties included:

• Graded homework and course project and provided detailed feedback
• Revised solutions
• improved the final project Moving Object Detection coding part.