11 papers
AKG kernel Agent: A Multi-Agent Framework for Cross-Platform Kernel Synthesis
Jinye Du, Quan Yuan, Zuyao Zhang +16
Modern AI models demand high-performance computation kernels. The growing complexity of LLMs, multimodal architectures, and recommendation systems, combined with techniques like sp…
VDSAgents: A PCS-Guided Multi-Agent System for Veridical Data Science Automation
Yunxuan Jiang, Silan Hu, Xiaoning Wang +2
Large language models (LLMs) become increasingly integrated into data science workflows for automated system design. However, these LLM-driven data science systems rely solely on t…
A Unified Zeroth-Order Optimization Framework via Oblivious Randomized Sketching
Haishan Ye, Xiangyu Chang, Xi Chen
We propose a new framework for analyzing zeroth-order optimization (ZOO) from the perspective of \emph{oblivious randomized sketching}.In this framework, commonly used gradient est…
Can a One-Point Feedback Zeroth-order Algorithm Achieve Linear Dimension Dependent Sample Complexity?
Haishan Ye, Xiangyu Chang
We revisit the one-point feedback zeroth-order (ZO) optimization problem, a classical setting in derivative-free optimization where only a single noisy function evaluation is avail…
PPFL: A Personalized Federated Learning Framework for Heterogeneous Population
Hao Di, Yi Yang, Haishan Ye +1
Personalization aims to characterize individual preferences and is widely applied across many fields. However, conventional personalized methods operate in a centralized manner, po…
AdapFair: Ensuring Adaptive Fairness for Machine Learning Operations
Yinghui Huang, Zihao Tang, Xiangyu Chang
The biases and discrimination of machine learning algorithms have attracted significant attention, leading to the development of various algorithms tailored to specific contexts. H…