We propose an Gaussian Mixture Model (GMM) learning algorithm, based on ...
The Traveling Salesman Problem (TSP) is a well-known problem in combinat...
To promote the development of Vision-Language Pre-training (VLP) and
mul...
We consider the problem of constructing small coresets for k-Median in
E...
We study coresets for clustering with capacity and fairness constraints....
Designing small-sized coresets, which approximately preserve the costs
o...
Fine-grained classification and counting of bone marrow erythroid cells ...
Neural-symbolic computing aims at integrating robust neural learning and...
Constructing small-sized coresets for various clustering problems in
Euc...
We consider robust clustering problems in ℝ^d, specifically
k-clustering...
Motivated by practical generalizations of the classic k-median and
k-mea...
(j,k)-projective clustering is the natural generalization of the family ...
In recent years, extreme weather events frequently cause large-scale pow...
The surprisingly popular algorithm (SPA) is a powerful crowd decision mo...
We provide the first coreset for clustering points in ℝ^d that
have mult...
The Fisher information matrix provides a way to measure the amount of
in...
Neural architecture search (NAS) is a hot topic in the field of automate...
With the advances of artificial intelligence (AI) technology, many studi...
Coresets are modern data-reduction tools that are widely used in data
an...
Semi-supervised learning (SSL) is effectively used for numerous
classifi...
We initiate the study of coresets for clustering in graph metrics, i.e.,...
An ε-coreset for a given set D of n points, is usually a
small weighted ...
In this paper we prove an analogue of the Komlós-Major-Tusnády (KMT)
emb...
We design coresets for Ordered k-Median, a generalization of classical
c...
We study the problem of constructing ε-coresets for the (k,
z)-clusterin...
Uniformity testing and the more general identity testing are well studie...