Sparse K-Means with the l_q (0leq q< 1) Constraint for High-Dimensional Data Clustering
… sparse k-means clustering with the lq (0 < q < 1) constraint (lq-k-means). Although the …
Then we evaluate the performance of lo-k-means, lq-k-means and l1-k-means based on the …
Then we evaluate the performance of lo-k-means, lq-k-means and l1-k-means based on the …
Index-based, high-dimensional, cosine threshold querying with optimality guarantees
… We used the variables LQ_parent, Q2_parent, and L2_parent to accumulate the values
when the right turns are made. The number of traversal steps is no more than the depth of the …
when the right turns are made. The number of traversal steps is no more than the depth of the …
Identifying affective levels on music video via completing the missing modality
M Chen, G Cheng, L Guo - Multimedia Tools and Applications, 2018 - Springer
… where Q i j = K(x i ,x j ) = ϕ(x i T)ϕ(x j ). … In the original paper [22], the result V is used as input
of k-means … AG (2017) Feature interaction augmented sparse learning for fast kinect motion …
of k-means … AG (2017) Feature interaction augmented sparse learning for fast kinect motion …
ICDM 2013
The following topics are dealt with: social networks; information networks; human behavior
prediction; active learning; generative maximum entropy learning; spatiotemporal pattern …
prediction; active learning; generative maximum entropy learning; spatiotemporal pattern …