activity
20212026
most citedEfficient Resource Allocation with Fairness Constraints in Restless Multi-Armed Bandits

4 citations · 12 across the 9 of their papers we have counts for

collaborators

9 papers

cs.AI2026

Efficient Unsupervised Environment Design through Hierarchical Policy Representation Learning

Dexun Li, Sidney Tio, Pradeep Varakantham

Unsupervised Environment Design (UED) has emerged as a promising approach to developing general-purpose agents through automated curriculum generation. Popular UED methods focus on…

cs.AI2024★ 1 cited

EduQate: Generating Adaptive Curricula through RMABs in Education Settings

Sidney Tio, Dexun Li, Pradeep Varakantham

There has been significant interest in the development of personalized and adaptive educational tools that cater to a student's individual learning progress. A crucial aspect in de…

cs.LG2023

Enhancing the Hierarchical Environment Design via Generative Trajectory Modeling

Dexun Li, Pradeep Varakantham

Unsupervised Environment Design (UED) is a paradigm for automatically generating a curriculum of training environments, enabling agents trained in these environments to develop gen…

cs.AI2023★ 2 cited

Diversity Induced Environment Design via Self-Play

Dexun Li, Wenjun Li, Pradeep Varakantham

Recent work on designing an appropriate distribution of environments has shown promise for training effective generally capable agents. Its success is partly because of a form of a…

cs.AI2023★ 2 cited

Generalization through Diversity: Improving Unsupervised Environment Design

Wenjun Li, Pradeep Varakantham, Dexun Li

Agent decision making using Reinforcement Learning (RL) heavily relies on either a model or simulator of the environment (e.g., moving in an 8x8 maze with three rooms, playing Ches…

cs.LG2022

Hidden State Approximation in Recurrent Neural Networks Using Continuous Particle Filtering

Dexun Li

Using historical data to predict future events has many applications in the real world, such as stock price prediction; the robot localization. In the past decades, the Convolution…

cs.LG2022★ 1 cited

Towards Soft Fairness in Restless Multi-Armed Bandits

Dexun Li, Pradeep Varakantham

Restless multi-armed bandits (RMAB) is a framework for allocating limited resources under uncertainty. It is an extremely useful model for monitoring beneficiaries and executing ti…

cs.LG2022★ 4 cited

Efficient Resource Allocation with Fairness Constraints in Restless Multi-Armed Bandits

Dexun Li, Pradeep Varakantham

Restless Multi-Armed Bandits (RMAB) is an apt model to represent decision-making problems in public health interventions (e.g., tuberculosis, maternal, and child care), anti-poachi…

cs.AI2021★ 2 cited

CLAIM: Curriculum Learning Policy for Influence Maximization in Unknown Social Networks

Dexun Li, Meghna Lowalekar, Pradeep Varakantham

Influence maximization is the problem of finding a small subset of nodes in a network that can maximize the diffusion of information. Recently, it has also found application in HIV…