Search Results for author: Guru Venkataramani

Found 5 papers, 2 papers with code

MAC-PO: Multi-Agent Experience Replay via Collective Priority Optimization

no code implementations21 Feb 2023 Yongsheng Mei, Hanhan Zhou, Tian Lan, Guru Venkataramani, Peng Wei

To this end, we propose MAC-PO, which formulates optimal prioritized experience replay for multi-agent problems as a regret minimization over the sampling weights of transitions.

Decision Making Multi-agent Reinforcement Learning +3

Exploiting Partial Common Information Microstructure for Multi-Modal Brain Tumor Segmentation

1 code implementation6 Feb 2023 Yongsheng Mei, Guru Venkataramani, Tian Lan

Our experimental results on the Multi-modal Brain Tumor Segmentation Challenge (BraTS) datasets outperform those of state-of-the-art segmentation baselines, with validation Dice similarity coefficients of 0. 920, 0. 897, 0. 837 for the whole tumor, tumor core, and enhancing tumor on BraTS-2020.

Brain Tumor Segmentation Image Segmentation +2

On the Convergence of Heterogeneous Federated Learning with Arbitrary Adaptive Online Model Pruning

1 code implementation27 Jan 2022 Hanhan Zhou, Tian Lan, Guru Venkataramani, Wenbo Ding

In this paper, we present a unifying framework for heterogeneous FL algorithms with {\em arbitrary} adaptive online model pruning and provide a general convergence analysis.

Federated Learning Open-Ended Question Answering

PT-VTON: an Image-Based Virtual Try-On Network with Progressive Pose Attention Transfer

no code implementations23 Nov 2021 Hanhan Zhou, Tian Lan, Guru Venkataramani

The virtual try-on system has gained great attention due to its potential to give customers a realistic, personalized product presentation in virtualized settings.

Pose Transfer Virtual Try-on

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