128 citations · 197 across the 5 of their papers we have counts for
9 papers
Extreme Multi-label Learning for Semantic Matching in Product Search
Wei-Cheng Chang, Daniel Jiang, Hsiang-Fu Yu +9
We consider the problem of semantic matching in product search: given a customer query, retrieve all semantically related products from a huge catalog of size 100 million, or more.…
BoolNet: Minimizing The Energy Consumption of Binary Neural Networks
Nianhui Guo, Joseph Bethge, Haojin Yang +4
Recent works on Binary Neural Networks (BNNs) have made promising progress in narrowing the accuracy gap of BNNs to their 32-bit counterparts. However, the accuracy gains are often…
Machine Learning for Electronic Design Automation: A Survey
Guyue Huang, Jingbo Hu, Yifan He +13
With the down-scaling of CMOS technology, the design complexity of very large-scale integrated (VLSI) is increasing. Although the application of machine learning (ML) techniques in…
Enabling Efficient and Flexible FPGA Virtualization for Deep Learning in the Cloud
Shulin Zeng, Guohao Dai, Hanbo Sun +5
FPGAs have shown great potential in providing low-latency and energy-efficient solutions for deep neural network (DNN) inference applications. Currently, the majority of FPGA-based…
Taming Pretrained Transformers for Extreme Multi-label Text Classification
Wei-Cheng Chang, Hsiang-Fu Yu, Kai Zhong +2
We consider the extreme multi-label text classification (XMC) problem: given an input text, return the most relevant labels from a large label collection. For example, the input te…
Binary Classification with Karmic, Threshold-Quasi-Concave Metrics
Bowei Yan, Oluwasanmi Koyejo, Kai Zhong +1
Complex performance measures, beyond the popular measure of accuracy, are increasingly being used in the context of binary classification. These complex performance measures are ty…