11 citations · 15 across the 13 of their papers we have counts for
4 papers · 1 filter
Random Offset Block Embedding Array (ROBE) for CriteoTB Benchmark MLPerf DLRM Model : 1000 Compression and 3.1 Faster Inference
Aditya Desai, Li Chou, Anshumali Shrivastava
Deep learning for recommendation data is one of the most pervasive and challenging AI workload in recent times. State-of-the-art recommendation models are one of the largest models…
Beyond Convolutions: A Novel Deep Learning Approach for Raw Seismic Data Ingestion
Zhaozhuo Xu, Aditya Desai, Menal Gupta +3
Traditional seismic processing workflows (SPW) are expensive, requiring over a year of human and computational effort. Deep learning (DL) based data-driven seismic workflows (DSPW)…
Semantically Constrained Memory Allocation (SCMA) for Embedding in Efficient Recommendation Systems
Aditya Desai, Yanzhou Pan, Kuangyuan Sun +2
Deep learning-based models are utilized to achieve state-of-the-art performance for recommendation systems. A key challenge for these models is to work with millions of categorical…
Density Sketches for Sampling and Estimation
Aditya Desai, Benjamin Coleman, Anshumali Shrivastava
We introduce Density sketches (DS): a succinct online summary of the data distribution. DS can accurately estimate point wise probability density. Interestingly, DS also provides a…