108 citations · 353 across the 17 of their papers we have counts for
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BlinkML: Efficient Maximum Likelihood Estimation with Probabilistic Guarantees
Yongjoo Park, Jingyi Qing, Xiaoyang Shen +1
The rising volume of datasets has made training machine learning (ML) models a major computational cost in the enterprise. Given the iterative nature of model and parameter tuning,…
A Bandit Approach to Maximum Inner Product Search
Rui Liu, Tianyi Wu, Barzan Mozafari
There has been substantial research on sub-linear time approximate algorithms for Maximum Inner Product Search (MIPS). To achieve fast query time, state-of-the-art techniques requi…
QuickSel: Quick Selectivity Learning with Mixture Models
Yongjoo Park, Shucheng Zhong, Barzan Mozafari
Estimating the selectivity of a query is a key step in almost any cost-based query optimizer. Most of today's databases rely on histograms or samples that are periodically refreshe…
Revisiting Projection-Free Optimization for Strongly Convex Constraint Sets
Jarrid Rector-Brooks, Jun-Kun Wang, Barzan Mozafari
We revisit the Frank-Wolfe (FW) optimization under strongly convex constraint sets. We provide a faster convergence rate for FW without line search, showing that a previously overl…
VerdictDB: Universalizing Approximate Query Processing
Yongjoo Park, Barzan Mozafari, Joseph Sorenson +1
Despite 25 years of research in academia, approximate query processing (AQP) has had little industrial adoption. One of the major causes of this slow adoption is the reluctance of…