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Found 7 papers, 1 papers with code
A multi-layer refined network model for the identification of essential proteins
In order to improve the accuracy of the identification of essential proteins, researchers attempted to obtain a refined PIN by combining multiple biological information to filter out some unreliable interactions in the PIN.
Exploring Depth Information for Face Manipulation Detection
As one of the important face features, the face depth map, which has shown to be effective in other areas such as the face recognition or face detection, is unfortunately paid little attention to in literature for detecting the manipulated face images.
OSS Mentor A framework for improving developers contributions via deep reinforcement learning
In open source project governance, there has been a lot of concern about how to measure developers' contributions.
Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous Features
Recently there has been significant interest in learning optimal decision trees using various approaches (e. g., based on integer programming, dynamic programming) -- to achieve computational scalability, most of these approaches focus on classification tasks with binary features.
Linear regression with partially mismatched data: local search with theoretical guarantees
We prove that under a suitable scaling of the number of mismatched pairs compared to the number of samples and features, and certain assumptions on problem data; our local search algorithm converges to a nearly-optimal solution at a linear rate.
Interior-Point Methods Strike Back: Solving the Wasserstein Barycenter Problem
Computing the Wasserstein barycenter of a set of probability measures under the optimal transport metric can quickly become prohibitive for traditional second-order algorithms, such as interior-point methods, as the support size of the measures increases.
Solving L1-regularized SVMs and related linear programs: Revisiting the effectiveness of Column and Constraint Generation
The linear Support Vector Machine (SVM) is a classic classification technique in machine learning.
