期刊： JOURNAL OF MACHINE LEARNING RESEARCH, 2021; 22 ()
How neural network behaves during the training over different choices of hyperparameters is an important question in the study of neural networks. In ......
期刊： JOURNAL OF MACHINE LEARNING RESEARCH, 2021; 22 ()
Large-scale matrix linear regression models with high-dimensional responses and high dimensional variables have been widely employed in various large-......
期刊： JOURNAL OF MACHINE LEARNING RESEARCH, 2021; 22 ()
Spectral clustering has become one of the most popular algorithms in data clustering and community detection. We study the performance of classical tw......
期刊： JOURNAL OF MACHINE LEARNING RESEARCH, 2021; 22 ()
Recommender systems have been extensively used by the entertainment industry, business marketing and the biomedical industry. In addition to its capac......
期刊： JOURNAL OF MACHINE LEARNING RESEARCH, 2021; 22 ()
Identifying informative predictors in a high dimensional regression model is a critical step for association analysis and predictive modeling. Signal ......
期刊： JOURNAL OF MACHINE LEARNING RESEARCH, 2021; 22 ()
Tensors are becoming prevalent in modern applications such as medical imaging and digital marketing. In this paper, we propose a sparse tensor additiv......
期刊： JOURNAL OF MACHINE LEARNING RESEARCH, 2021; 22 ()
This paper presents a new methodology for modeling the local semantic distribution of responses to a given query in the human-conversation corpus, and......
期刊： JOURNAL OF MACHINE LEARNING RESEARCH, 2021; 22 ()
A sketch of a large data set captures vital properties of the original data while typically occupying much less space. In this paper, we consider the ......
期刊： JOURNAL OF MACHINE LEARNING RESEARCH, 2021; 22 ()
We propose the class-specified topic model (CSTM) to deal with the tasks of text classification and class-specific text summarization. The model assum......
期刊： JOURNAL OF MACHINE LEARNING RESEARCH, 2021; 22 ()
We provide general adaptive upper bounds for estimating nonparametric functionals based on second-order U-statistics arising from finite-dimensional a......
期刊： JOURNAL OF MACHINE LEARNING RESEARCH, 2021; 22 ()
Modern machine learning methods are often overparametrized, allowing adaptation to the data at a fine level. This can seem puzzling; in the worst case......
期刊： JOURNAL OF MACHINE LEARNING RESEARCH, 2021; 22 ()
This paper considers a decentralized online submodular maximization problem over time-varying networks, where each agent only utilizes its own informa......
期刊： JOURNAL OF MACHINE LEARNING RESEARCH, 2021; 22 ()
Bandit Convex Optimization (BCO) is a fundamental framework for modeling sequential decision-making with partial information, where the only feedback ......
期刊： JOURNAL OF MACHINE LEARNING RESEARCH, 2021; 22 ()
Many machine learning models involve solving optimization problems. Thus, it is important to address a large-scale optimization problem in big data ap......
期刊： JOURNAL OF MACHINE LEARNING RESEARCH, 2021; 22 ()
In this paper, we propose a novel algorithm for large-scale regression problems named Histogram Transform Ensembles (HTE), composed of random rotation......
