Publications (6)
Transforming Noise Distributions with Histogram Matching: Towards a Single Denoiser for All
Sheng Fu, Junchao Zhang, Kailun Yang
Supervised Gaussian denoisers exhibit limited generalization when confronted with out-of-distribution noise, due to the diverse distributional characteristics of different noise ty…
Sequential Multi-Agent Dynamic Algorithm Configuration
Chen Lu, Ke Xue, Lei Yuan +4
Dynamic algorithm configuration (DAC) is a recent trend in automated machine learning, which can dynamically adjust the algorithm's configuration during the execution process and r…
ViDove: A Translation Agent System with Multimodal Context and Memory-Augmented Reasoning
Yichen Lu, Wei Dai, Jiaen Liu +9
LLM-based translation agents have achieved highly human-like translation results and are capable of handling longer and more complex contexts with greater efficiency. However, they…
Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings
Rong-Xi Tan, Ming Chen, Ke Xue +4
The pursuit of universal black-box optimization (BBO) algorithms is a longstanding goal. However, unlike domains such as language or vision, where scaling structured data has drive…
MLCommons Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces
Srinivas Sridharan, Theodor-Adrian Badea, Andy Balogh +26
The fast pace of artificial intelligence~(AI) innovation demands an agile methodology for observation, reproduction and optimization of distributed machine learning~(ML) workload b…
Offline Model-Based Optimization by Learning to Rank
Rong-Xi Tan, Ke Xue, Shen-Huan Lyu +5
Offline model-based optimization (MBO) aims to identify a design that maximizes a black-box function using only a fixed, pre-collected dataset of designs and their corresponding sc…