Node classification is the task of predicting the labels of unlabeled no...
This study proposed a YOLOv5-based custom object detection model to dete...
The US apple industry relies heavily on semi-skilled manual labor force ...
Graph neural architecture search (NAS) has gained popularity in automati...
Offline safe RL is of great practical relevance for deploying agents in
...
In this paper, we study the collaborative learning model, which concerns...
Monocular depth estimation can play an important role in addressing the ...
Safety comes first in many real-world applications involving autonomous
...
Open domain question answering (ODQA) is a longstanding task aimed at
an...
In this letter, we study the simultaneously transmitting and reflecting
...
Image clustering is an important, and open challenge task in computer vi...
We investigate top-m arm identification, a basic problem in bandit theor...
In this paper, we study the tradeoffs between time-speedup and the numbe...
Safe reinforcement learning (RL) has achieved significant success on
ris...
In this paper, we propose a novel prosody disentangle method for prosodi...
Deep unsupervised hashing has been appreciated in the regime of image
re...
Cycle-consistent generative adversarial networks (CycleGAN) have shown t...
We study the problem of learning to cluster data points using an oracle ...
Hashing technology has been widely used in image retrieval due to its
co...
We study Thompson Sampling algorithms for stochastic multi-armed bandits...
Non-parallel training is a difficult but essential task for DNN-based sp...
Motivated by real-world applications such as fast fashion retailing and
...
Dynamic Uncertain Causality Graph(DUCG) is a recently proposed model for...
We study multinomial logit bandit with limited adaptivity, where the
alg...
We consider the following problem in this paper: given a set of n
distri...
Book chapter that summarizes recent research on agricultural robotics in...
Best arm identification (or, pure exploration) in multi-armed bandits is...
We study linear programming and general LP-type problems in several big ...
In this paper we study how to perform distinct sampling in the streaming...
In this paper we study edit similarity joins, in which we are given a se...
We consider statistical estimations of a matrix product over the integer...
We study the classic k-means/median clustering, which are fundamental
pr...
We study the collaborative PAC learning problem recently proposed in Blu...
We propose smooth q-gram, the first variant of q-gram that captures
q-gr...
This letter adopts long short-term memory(LSTM) to predict sea surface
t...