For the problems of low recognition rate and slow recognition speed of
t...
Constructing asymptotically valid confidence intervals through a valid
c...
Natural reading orders of words are crucial for information extraction f...
Affinity graphs are widely used in deep architectures, including graph
c...
View based strategies for 3D object recognition have proven to be very
s...
Attention networks show promise for both vision and language tasks, by
e...
ProductNet is a collection of high-quality product datasets for better
p...
For a product of interest, we propose a search method to surface a set o...
Anomaly detection aims to detect abnormal events by a model of normality...
Feature learning on point clouds has shown great promise, with the
intro...
We consider the problem of sequentially making decisions that are reward...
We propose a family of near-metrics based on local graph diffusion to ca...
An important result from psycholinguistics (Griffiths & Kalish, 2005) st...
Boosting is a generic learning method for classification and regression....
We consider sequential decision making problems for binary classificatio...