567 citations · 656 across the 10 of their papers we have counts for
10 papers
HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer
Kaize Ding, Albert Jiongqian Liang, Bryan Perrozi +6
Learning expressive representations for high-dimensional yet sparse features has been a longstanding problem in information retrieval. Though recent deep learning methods can parti…
Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems
Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach +4
Learning high-quality feature embeddings efficiently and effectively is critical for the performance of web-scale machine learning systems. A typical model ingests hundreds of feat…
Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN)
Yin Zhang, Ruoxi Wang, Tiansheng Yao +5
Industry recommender systems usually suffer from highly-skewed long-tail item distributions where a small fraction of the items receives most of the user feedback. This skew hurts…
Surgical Gesture Recognition Based on Bidirectional Multi-Layer Independently RNN with Explainable Spatial Feature Extraction
Dandan Zhang, Ruoxi Wang, Benny Lo
Minimally invasive surgery mainly consists of a series of sub-tasks, which can be decomposed into basic gestures or contexts. As a prerequisite of autonomic operation, surgical ges…
Real-time Surgical Environment Enhancement for Robot-Assisted Minimally Invasive Surgery Based on Super-Resolution
Ruoxi Wang, Dandan Zhang, Qingbiao Li +2
In Robot-Assisted Minimally Invasive Surgery (RAMIS), a camera assistant is normally required to control the position and zooming ratio of the laparoscope, following the surgeon's…
DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems
Ruoxi Wang, Rakesh Shivanna, Derek Z. Cheng +4
Learning effective feature crosses is the key behind building recommender systems. However, the sparse and large feature space requires exhaustive search to identify effective cros…
PBBFMM3D: a parallel black-box algorithm for kernel matrix-vector multiplication
Ruoxi Wang, Chao Chen, Jonghyun Lee +1
Kernel matrix-vector product is ubiquitous in many science and engineering applications. However, a naive method requires operations, which becomes prohibitive for large-s…
Deep & Cross Network for Ad Click Predictions
Ruoxi Wang, Bin Fu, Gang Fu +1
Feature engineering has been the key to the success of many prediction models. However, the process is non-trivial and often requires manual feature engineering or exhaustive searc…
On the numerical rank of radial basis function kernels in high dimension
Ruoxi Wang, Yingzhou Li, Eric Darve
Low-rank approximations are popular methods to reduce the high computational cost of algorithms involving large-scale kernel matrices. The success of low-rank methods hinges on the…
Block Basis Factorization for Scalable Kernel Matrix Evaluation
Ruoxi Wang, Yingzhou Li, Michael W. Mahoney +1
Kernel methods are widespread in machine learning; however, they are limited by the quadratic complexity of the construction, application, and storage of kernel matrices. Low-rank…