IEEE

Optimal Control Theoretic Neural Optimizer: From Backpropagation to Dynamic Programming

Abstract: Optimization of deep neural networks (DNNs) has been driving modern advancements in artificial intelligence. With DNNs characterized by a prolonged sequence of nonlinear propagation, ...
GitHub

The issue of dynamic point segmentation.

This code segment (inference.py, lines 217-222) for dynamic point segmentation appears to use only the sky region mask (bg_mask_i).
C&EN

Hierarchical Reinforcement Learning with Dynamic Meta Agent for Adaptive Cut Selection in Integer Programming with Applications to Sensor Network Design

Department of Chemical Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India Indian Institute of Technology Delhi-Abu Dhabi, Khalifa City B 20010, Abu Dhabi, UAE ...
Total Retail

Beyond Traditional Segmentation: How AI is Changing the Dynamic Content Game

Wondering what your customers really want? Right now? In 2025? Here it is: Customers want brands to meet them where they are, in real time, with made-for-them messaging that’s genuinely helpful given ...
Frontiers

Optimal portfolio selection in jump-uncertain stochastic markets via maximum principle and dynamic programming

This study develops a unified framework for optimal portfolio selection in jump–uncertain stochastic markets, contributing both theoretical foundations and computational insights. We establish the ...
GitHub

Used Unsupervised Machine Learning using KMeans for user segmentation of mall customers dataset.

There was an error while loading. Please reload this page. This project demonstrates how to build a K-Means clustering algorithm from scratch to segment mall ...
IEEE

Video scene segmentation using a novel boundary evaluation criterion and dynamic programming

Abstract: Video scene segmentation is a fundamental step for video summarization and browsing, which is a very promising application of multimedia analysis. There are two key elements, namely, ...