Allo: A Programming Model for Composable Accelerator Design

2 code implementations • 7 Apr 2024 • Hongzheng Chen, Niansong Zhang, Shaojie Xiang, Zhichen Zeng, Mengjia Dai, Zhiru Zhang

For the GPT2 model, the inference latency of the Allo generated accelerator is 1. 7x faster than the NVIDIA A100 GPU with 5. 4x higher energy efficiency, demonstrating the capability of Allo to handle large-scale designs.

Hierarchical Multi-Marginal Optimal Transport for Network Alignment

no code implementations • 6 Oct 2023 • Zhichen Zeng, Boxin Du, Si Zhang, Yinglong Xia, Zhining Liu, Hanghang Tong

To depict high-order relationships across multiple networks, the FGW distance is generalized to the multi-marginal setting, based on which networks can be aligned jointly.

Ensuring User-side Fairness in Dynamic Recommender Systems

no code implementations • 29 Aug 2023 • Hyunsik Yoo, Zhichen Zeng, Jian Kang, Ruizhong Qiu, David Zhou, Zhining Liu, Fei Wang, Charlie Xu, Eunice Chan, Hanghang Tong

In the ever-evolving landscape of user-item interactions, continual adaptation to newly collected data is crucial for recommender systems to stay aligned with the latest user preferences.

Fairness Recommendation Systems +1

Topological Augmentation for Class-Imbalanced Node Classification

no code implementations • 27 Aug 2023 • Zhining Liu, Zhichen Zeng, Ruizhong Qiu, Hyunsik Yoo, David Zhou, Zhe Xu, Yada Zhu, Kommy Weldemariam, Jingrui He, Hanghang Tong

Class imbalance is prevalent in real-world node classification tasks and often biases graph learning models toward majority classes.

Classification Graph Learning +1