Wei Lu

According to our database, Wei Lu authored at least 13 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

FRAP: Faithful and Realistic Text-to-Image Generation with Adaptive Prompt Weighting.

Liyao Jiang, Negar Hassanpour, Mohammad Salameh, Mohan Sai Singamsetti, Fengyu Sun, Wei Lu, Di Niu

CoRR, 2024

2023

A General-Purpose Transferable Predictor for Neural Architecture Search.

Fred X. Han, Keith G. Mills, Fabian Chudak, Parsa Riahi, Mohammad Salameh, Jialin Zhang, Wei Lu, Shangling Jui, Di Niu

Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

AutoGO: Automated Computation Graph Optimization for Neural Network Evolution.

Mohammad Salameh, Keith G. Mills, Negar Hassanpour, Fred X. Han, Shuting Zhang, Wei Lu, Shangling Jui, Chunhua Zhou, Fengyu Sun, Di Niu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

AIO-P: Expanding Neural Performance Predictors beyond Image Classification.

Keith G. Mills, Di Niu, Mohammad Salameh, Weichen Qiu, Fred X. Han, Puyuan Liu, Jialin Zhang, Wei Lu, Shangling Jui

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

GENNAPE: Towards Generalized Neural Architecture Performance Estimators.

Keith G. Mills, Fred X. Han, Jialin Zhang, Fabian Chudak, Ali Safari Mamaghani, Mohammad Salameh, Wei Lu, Shangling Jui, Di Niu

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

A Memory-Bounded Best-First Beam Search and Its Application to Scheduling Halide Programs.

Chao Gao, Jingwei Chen, Tong Mo, Tanvir Sajed, Shangling Jui, Min Qin, Laiyuan Gong, Wei Lu

Proceedings of the Fifteenth International Symposium on Combinatorial Search, 2022

Sample Average Approximation for Stochastic Optimization with Dependent Data: Performance Guarantees and Tractability.

Yafei Wang, Bo Pan, Wei Tu, Peng Liu, Bei Jiang, Chao Gao, Wei Lu, Shangling Jui, Linglong Kong

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

L$^{2}$NAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning.

Keith G. Mills, Fred X. Han, Mohammad Salameh, Seyed Saeed Changiz Rezaei, Linglong Kong, Wei Lu, Shuo Lian, Shangling Jui, Di Niu

CoRR, 2021

Exploring Neural Architecture Search Space via Deep Deterministic Sampling.

Keith G. Mills, Mohammad Salameh, Di Niu, Fred X. Han, Seyed Saeed Changiz Rezaei, Hengshuai Yao, Wei Lu, Shuo Lian, Shangling Jui

IEEE Access, 2021

Generative Adversarial Neural Architecture Search.

Seyed Saeed Changiz Rezaei, Fred X. Han, Di Niu, Mohammad Salameh, Keith G. Mills, Shuo Lian, Wei Lu, Shangling Jui

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Bansor: Improving Tensor Program Auto-Scheduling with Bandit Based Reinforcement Learning.

Chao Gao, Tong Mo, Taylor Zowtuk, Tanvir Sajed, Laiyuan Gong, Hanxuan Chen, Shangling Jui, Wei Lu

Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence, 2021

Profiling Neural Blocks and Design Spaces for Mobile Neural Architecture Search.

Keith G. Mills, Fred X. Han, Jialin Zhang, Seyed Saeed Changiz Rezaei, Fabian Chudak, Wei Lu, Shuo Lian, Shangling Jui, Di Niu

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

L2NAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning.

Keith G. Mills, Fred X. Han, Mohammad Salameh, Seyed Saeed Changiz Rezaei, Linglong Kong, Wei Lu, Shuo Lian, Shangling Jui, Di Niu

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021