Abhishek K. Umrawal

Orcid: 0000-0003-4460-7499

According to our database1, Abhishek K. Umrawal authored at least 20 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
CyNetDiff: A Python Library for Accelerated Implementation of Network Diffusion Models.
Proc. VLDB Endow., August, 2024

CyNetDiff - A Python Library for Accelerated Implementation of Network Diffusion Models.
CoRR, 2024

Fractional Budget Allocation for Influence Maximization under General Marketing Strategies.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023
A Community-Aware Framework for Social Influence Maximization.
IEEE Trans. Emerg. Top. Comput. Intell., August, 2023

Leveraging the Community Structure of a Social Network for Maximizing the Spread of Influence.
SIGMETRICS Perform. Evaluation Rev., April, 2023

Simple is Better and Large is Not Enough: Towards Ensembling of Foundational Language Models.
CoRR, 2023

Leveraging Causal Graphs for Blocking in Randomized Experiments.
Proceedings of the Conference on Causal Learning and Reasoning, 2023

Fractional Budget Allocation for Influence Maximization.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022
A Genetic Algorithm-based Framework for Learning Statistical Power Manifold.
CoRR, 2022

A Community-Aware Framework for Social Influence Maximization.
CoRR, 2022

An explore-then-commit algorithm for submodular maximization under full-bandit feedback.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021
FlexPool: A Distributed Model-Free Deep Reinforcement Learning Algorithm for Joint Passengers and Goods Transportation.
IEEE Trans. Intell. Transp. Syst., 2021

Stochastic Top <i>K</i>-Subset Bandits with Linear Space and Non-Linear Feedback with Applications to Social Influence Maximization.
Trans. Data Sci., 2021

A Causality-based Graphical Test to obtain an Optimal Blocking Set for Randomized Experiments.
CoRR, 2021

On Parameter Estimation in Unobserved Components Models subject to Linear Inequality Constraints.
CoRR, 2021

Stochastic Top-K Subset Bandits with Linear Space and Non-Linear Feedback.
Proceedings of the Algorithmic Learning Theory, 2021

DeepFreight: A Model-free Deep-reinforcement-learning-based Algorithm for Multi-transfer Freight Delivery.
Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling, 2021

DART: Adaptive Accept Reject Algorithm for Non-Linear Combinatorial Bandits.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
DART: aDaptive Accept RejecT for non-linear top-K subset identification.
CoRR, 2020

FlexPool: A Distributed Model-Free Deep Reinforcement Learning Algorithm for Joint Passengers & Goods Transportation.
CoRR, 2020


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