Search Results for author:
Found 3 papers, 2 papers with code
Approximate Nearest Neighbor Search with Window Filters
We define and investigate the problem of $\textit{c-approximate window search}$: approximate nearest neighbor search where each point in the dataset has a numeric label, and the goal is to find nearest neighbors to queries within arbitrary label ranges.
PECANN: Parallel Efficient Clustering with Graph-Based Approximate Nearest Neighbor Search
In particular, we study variants of density peaks clustering, a popular type of algorithm that has been shown to work well in practice.
BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU Hardware
Efficient large-scale neural network training and inference on commodity CPU hardware is of immense practical significance in democratizing deep learning (DL) capabilities.
Ranked #2 on
Node Classification
on Yelp-Fraud
