Auto Graph Encoder-Decoder for Model Compression and Network Acceleration. - Sixing Yu; Arya Mazaheri; Ali Jannesari (CoRR, 2020)

Auto Graph Encoder-Decoder for Neural Network Pruning. - Sixing Yu; Arya Mazaheri; Ali Jannesari (ICCV, 2021)

GNN-RL Compression: Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning. - Sixing Yu; Arya Mazaheri; Ali Jannesari (CoRR, 2021)

Adaptive Dynamic Pruning for Non-IID Federated Learning. - Sixing Yu; Phuong Nguyen; Ali Anwar 001; Ali Jannesari (CoRR, 2021)

SPATL: Salient Parameter Aggregation and Transfer Learning for Heterogeneous Clients in Federated Learning. - Sixing Yu; Phuong Nguyen; Waqwoya Abebe; Ali Anwar 001; Ali Jannesari (CoRR, 2021)

Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning. - Sixing Yu; Arya Mazaheri; Ali Jannesari (ICML, 2022)

SPATL: Salient Parameter Aggregation and Transfer Learning for Heterogeneous Federated Learning. - Sixing Yu; Phuong Nguyen; Waqwoya Abebe; Wei Qian; Ali Anwar 001; Ali Jannesari (SC, 2022)

Resource-aware Federated Learning using Knowledge Extraction and Multi-model Fusion. - Sixing Yu; Wei Qian; Ali Jannesari (CoRR, 2022)

Resource-Aware Heterogeneous Federated Learning using Neural Architecture Search. - Sixing Yu; Phuong Nguyen; Waqwoya Abebe; Justin Stanley; J. Pablo Muñoz; Ali Jannesari (CoRR, 2022)

Towards Seamless Management of AI Models in High-Performance Computing. - Sixing Yu; Murali Emani; Chunhua Liao; Pei-Hung Lin; Tristan Vanderbruggen; Xipeng Shen; Ali Jannesari (CoRR, 2022)

Heterogeneous Federated Learning using Dynamic Model Pruning and Adaptive Gradient. - Sixing Yu; Phuong Nguyen; Ali Anwar 001; Ali Jannesari (CCGrid, 2023)

Enhancing Heterogeneous Federated Learning with Knowledge Extraction and Multi-Model Fusion. - Duy Phuong Nguyen; Sixing Yu; J. Pablo Muñoz; Ali Jannesari (SC Workshops, 2023)

Bridging the Gap Between Foundation Models and Heterogeneous Federated Learning. - Sixing Yu; J. Pablo Muñoz; Ali Jannesari (CoRR, 2023)

Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models. - Sixing Yu; Juan Pablo Muñoz; Ali Jannesari (LREC/COLING, 2024)

Resource-Aware Heterogeneous Federated Learning with Specialized Local Models. - Sixing Yu; J. Pablo Muñoz; Ali Jannesari (Euro-Par (1), 2024)

PipeInfer: Accelerating LLM Inference using Asynchronous Pipelined Speculation. - Branden Butler; Sixing Yu; Arya Mazaheri; Ali Jannesari (SC, 2024)

The Landscape and Challenges of HPC Research and LLMs. - Le Chen; Nesreen K. Ahmed; Akash Dutta; Arijit Bhattacharjee; Sixing Yu; Quazi Ishtiaque Mahmud; Waqwoya Abebe; Hung Phan; Aishwarya Sarkar; Branden Butler; Niranjan Hasabnis; Gal Oren 001; et al. (CoRR, 2024)

SuperSAM: Crafting a SAM Supernetwork via Structured Pruning and Unstructured Parameter Prioritization. - Waqwoya Abebe; Sadegh Jafari; Sixing Yu; Akash Dutta; Jan Strube 001; Nathan R. Tallent; Luanzheng Guo; J. Pablo Muñoz; Ali Jannesari (CoRR, 2025)