5 days ago ¡¤ We implement both solvers on GPUs and demonstrate their computational efficiency and scalability on a set of numerical examples. The remainder of the paper is ...

4 days ago ¡¤ In this paper, we derived strong iterative convex relaxations for quadratic optimization problems with M-matrices and indicators, of which signal estimation ...

5 days ago ¡¤ This paper presents a modular framework for constructing randomized algorithms that compute partial matrix decompositions.

6 days ago ¡¤ With improved computational capabilities and optimized algorithms, large AI models will facilitate faster adaptation to decision-making tasks in underwater ...

3 days ago ¡¤ We answer this question by discussing how optimizers have evolved from traditional methods like gradient descent to more advanced techniques to address ...

3 days ago ¡¤ ... convex optimization problems and developing efficient numerical algorithms to solve them. Despite their efficiency and computational tractability, convex models ...

7 hours ago ¡¤ ... convex optimization and deep reinforcement learning algorithm to attain the near-optimal solution. Specifically, the inner layer solves the discrete ...

3 days ago ¡¤ XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning ...

4 days ago ¡¤ This paper introduces a simple yet effective method for long-tailed classification, called mixed mutual transfer (MMT), which facilitates the mutual transfer of ...

6 days ago ¡¤ To improve computational efficiency of pore-scale modeling a GPU-based LB simulation will be ... model predictive control (MPC) strategy is employed to predict ...