163 citations · 212 across the 10 of their papers we have counts for
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cs.DB2022
Tuning the Tail Latency of Distributed Queries Using Replication
Nathan Ng, Hung Le, Marco Serafini
Querying graph data with low latency is an important requirement in application domains such as social networks and knowledge graphs. Graph queries perform multiple hops between ve…
cs.LG2022★ 12 cited
If Influence Functions are the Answer, Then What is the Question?
Juhan Bae, Nathan Ng, Alston Lo +2
Influence functions efficiently estimate the effect of removing a single training data point on a model's learned parameters. While influence estimates align well with leave-one-ou…
cs.LG2022★ 1 cited
Predicting Out-of-Domain Generalization with Neighborhood Invariance
Nathan Ng, Neha Hulkund, Kyunghyun Cho +1
Developing and deploying machine learning models safely depends on the ability to characterize and compare their abilities to generalize to new environments. Although recent work h…