26 citations · 34 across the 5 of their papers we have counts for
5 papers
Addressing Weak Decision Boundaries in Image Classification by Leveraging Web Search and Generative Models
Preetam Prabhu Srikar Dammu, Yunhe Feng, Chirag Shah
Machine learning (ML) technologies are known to be riddled with ethical and operational problems, however, we are witnessing an increasing thrust by businesses to deploy them in se…
FZ-GPU: A Fast and High-Ratio Lossy Compressor for Scientific Computing Applications on GPUs
Boyuan Zhang, Jiannan Tian, Sheng Di +5
Today's large-scale scientific applications running on high-performance computing (HPC) systems generate vast data volumes. Thus, data compression is becoming a critical technique…
Towards Generating Robust, Fair, and Emotion-Aware Explanations for Recommender Systems
Bingbing Wen, Yunhe Feng, Yongfeng Zhang +1
As recommender systems become increasingly sophisticated and complex, they often suffer from lack of fairness and transparency. Providing robust and unbiased explanations for recom…
COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression
Sian Jin, Chengming Zhang, Xintong Jiang +5
Training wide and deep neural networks (DNNs) require large amounts of storage resources such as memory because the intermediate activation data must be saved in the memory during…
Optimizing Error-Bounded Lossy Compression for Scientific Data on GPUs
Jiannan Tian, Sheng Di, Xiaodong Yu +7
Error-bounded lossy compression is a critical technique for significantly reducing scientific data volumes. With ever-emerging heterogeneous high-performance computing (HPC) archit…