The approximate nearest neighbor (ANN) search problem is fundamental to
...
This paper studies the curious phenomenon for machine learning models wi...
Language models can be augmented with a context retriever to incorporate...
This paper presents a novel nearest neighbor search algorithm achieving ...
Quantization based methods are popular for solving large scale maximum i...
Inverted file and asymmetric distance computation (IVFADC) have been
suc...
Many emerging use cases of data mining and machine learning operate on l...
We derive a class of noise probability distributions to preserve (ϵ,
δ)-...
We derive the optimal (0, δ)-differentially private query-output
indepen...
Existing music recognition applications require a connection to a server...
This paper presents a computationally efficient machine-learned method f...
Learning-based binary hashing has become a powerful paradigm for fast se...
We propose a quantization based approach for fast approximate Maximum In...
One major goal of vision is to infer physical models of objects, surface...