L1-ball-type priors are a recent generalization of the spike-and-slab pr...
Accurate acquisition of crowd flow at Points of Interest (POIs) is pivot...
Longest Increasing Subsequence (LIS) is a fundamental problem in
combina...
This report describes the UNISOUND submission for Track1 and Track2 of
V...
Lossless floating-point time series compression is crucial for a wide ra...
Multivariate time-series anomaly detection is critically important in ma...
There are a prohibitively large number of floating-point time series dat...
Robot localization using a previously built map is essential for a varie...
Real-world graphs generally have only one kind of tendency in their
conn...
We study the task of spatio-temporal extrapolation that generates data a...
Millions of slum dwellers suffer from poor accessibility to urban servic...
Tactile sensors are believed to be essential in robotic manipulation, an...
Continuous in-hand manipulation is an important physical interaction ski...
This work continues the study of linear error correcting codes against
a...
With the development of sophisticated sensors and large database
technol...
Considering the ill-posed nature, contrastive regularization has been
de...
In this paper, we aim to learn a semantic radiance field from multiple s...
Robotic grasping is a fundamental ability for a robot to interact with t...
Robust prediction of citywide traffic flows at different time periods pl...
Air pollution is a crucial issue affecting human health and livelihoods,...
The performance of a camera network monitoring a set of targets depends
...
Designing safety-critical control for robotic manipulators is challengin...
Network traffic classification is the basis of many network security
app...
With the continuous development of deep learning in the field of image
g...
Weed management plays an important role in many modern agricultural
appl...
Graph contrastive learning (GCL) has recently emerged as an effective
le...
This paper presents the system description of the THUEE team for the NIS...
This paper describes speaker verification (SV) systems submitted by the
...
This report describes our speaker verification systems for the tasks of ...
Locally Decodable Codes (LDCs) are error-correcting codes
C:Σ^n→Σ^m with...
With the outbreak of today's streaming data, sequential recommendation i...
Anomaly detection with only prior knowledge from normal samples attracts...
Existing recommender systems extract the user preference based on learni...
Recommender systems are prone to be misled by biases in the data. Models...
In this paper, we introduce DA^2, the first large-scale dual-arm
dexteri...
Despite the rapid advance of unsupervised anomaly detection, existing me...
Graph contrastive learning (GCL) alleviates the heavy reliance on label
...
Data insufficiency problem (i.e., data missing and label scarcity issues...
Collision avoidance is a widely investigated topic in robotic applicatio...
A bathtub in a library, a sink in an office, a bed in a laundry room – t...
Multivariate time series forecasting has long received significant atten...
Anomaly detection from graph data is an important data mining task in ma...
In recent years, graph neural networks (GNNs) have emerged as a successf...
Locally Decodable Codes (LDCs) are error-correcting codes for which
indi...
Illegal vehicle parking is a common urban problem faced by major cities ...
Multi-branch convolutional neural network architecture has raised lots o...
This paper describes the multi-query multi-head attention (MQMHA) poolin...
Most recent speaker verification systems are based on extracting speaker...
Accurate forecasting of citywide traffic flow has been playing critical ...
Recommender system is one of the most important information services on
...