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Found 7 papers, 1 papers with code
An Efficient Data Analysis Method for Big Data using Multiple-Model Linear Regression
This paper introduces a new data analysis method for big data using a newly defined regression model named multiple model linear regression(MMLR), which separates input datasets into subsets and construct local linear regression models of them.
Rank-Regret Minimization
Thus it considered the problem of finding the minimal set $S$ with a rank-regret (the rank of top-1 tuple of $S$ in the sorted list of $D$) at most $k$, called the rank-regret representative (RRR) problem.
PCP Theorems, SETH and More: Towards Proving Sub-linear Time Inapproximability
In this paper we propose the PCP-like theorem for sub-linear time inapproximability.
Auto-Model: Utilizing Research Papers and HPO Techniques to Deal with the CASH problem
In many fields, a mass of algorithms with completely different hyperparameters have been developed to address the same type of problems.
Autoregressive-Model-Based Methods for Online Time Series Prediction with Missing Values: an Experimental Evaluation
In this paper, we focus on online methods for AR-model-based time series prediction with missing values.
Impacts of Dirty Data: and Experimental Evaluation
Data quality issues have attracted widespread attention due to the negative impacts of dirty data on data mining and machine learning results.
Quantum Image Processing and Its Application to Edge Detection: Theory and Experiment
Processing of digital images is continuously gaining in volume and relevance, with concomitant demands on data storage, transmission and processing power.
Quantum Physics
