This paper studies Byzantine-robust stochastic optimization over a
decen...
We present GenMM, a generative model that "mines" as many diverse motion...
We target a 3D generative model for general natural scenes that are typi...
The homogeneity, or more generally, the similarity between source domain...
Sparse reduced rank regression is an essential statistical learning meth...
A basic condition for efficient transfer learning is the similarity betw...
Dimension reduction and data quantization are two important methods for
...
Recently, the method that learns networks layer by layer has attracted
i...
Recently, it has been observed that 0,1,-1-ternary codes which are simpl...
This paper aims to solve a distributed learning problem under Byzantine
...
Synthesizing novel views of dynamic humans from stationary monocular cam...
This paper establishes unified frameworks of renewable weighted sums (RW...
Reduced rank regression is popularly used for modeling the relationship ...
In this paper, we propose a communication- and computation-efficient
alg...
This paper develops a communication-efficient algorithm to solve the
sto...
As a typical dimensionality reduction technique, random projection can b...