Unlike cloud-based deep learning models that are often large and uniform...
Analysts and scientists are interested in querying streams of video, aud...
Recently, learning-based algorithms have achieved promising performance ...
In this paper, we introduce AdaSelection, an adaptive sub-sampling metho...
Multi-output deep neural networks(MONs) contain multiple task branches, ...
In this paper, the authors propose a new approach to solving the groundw...
Today, recommender systems have played an increasingly important role in...
The security of artificial intelligence (AI) is an important research ar...
Over the past few years, AI methods of generating images have been incre...
As ML models have increased in capabilities and accuracy, so has the
com...
Grasp pose estimation is an important issue for robots to interact with ...
This paper presents a class of one-dimensional cellular automata (CA) mo...
Evaluation of biases in language models is often limited to syntheticall...
Using prompts to utilize language models to perform various downstream t...
Motivated by applications to single-particle cryo-electron microscopy
(c...
A novel intercarrier interference (ICI)-aware orthogonal frequency divis...
Prior works on formalizing explanations of a graph neural network (GNN) ...
We present a theoretical framework recasting data augmentation as stocha...
In commercial buildings, about 40
is attributed to Heating, Ventilation,...
We study the non-convex optimization landscape for maximum likelihood
es...
In this paper, we introduce an Augmented Lagrangian based method to
inco...
In this work, we propose a learning-based approach to the task of detect...
Considerable work on adversarial defense has studied robustness to a fix...
In many real life situations, including job and loan applications,
gatek...
Current blockchains are restricted by the low throughput. Aimed at this
...
We study the transfer of adversarial robustness of deep neural networks
...
We study the outlier eigenvalues and eigenvectors in variance components...
High-speed rail (HSR) systems potentially provide a more efficient way o...
A vine copula model is a flexible high-dimensional dependence model whic...
Label noise may handicap the generalization of classifiers, and it is an...
We study principal components analyses in multivariate random and mixed
...
In the orthognathic surgery, dental splints are important and necessary ...
This paper proposes to learn high-performance deep ConvNets with sparse
...
Large unweighted directed graphs are commonly used to capture relations
...
The state-of-the-art of face recognition has been significantly advanced...
This paper designs a high-performance deep convolutional network (DeepID...
We analyze directed, unweighted graphs obtained from x_i∈R^d by
connecti...
The key challenge of face recognition is to develop effective feature
re...
Efficient Natural Evolution Strategies (eNES) is a novel alternative to
...
We analyze the size of the dictionary constructed from online kernel
spa...
This paper presents Natural Evolution Strategies (NES), a recent family ...
We present a novel Natural Evolution Strategy (NES) variant, the Rank-On...
To maximize its success, an AGI typically needs to explore its initially...