5 papers
A Quantum Approach to Stochastic Optimization in Insurance Underwriting
Mitchell Bordelon, Maurice Garfinkel, Vivek Dixit +7
The presence of stochastic elements in combinatorial optimization problems makes them particularly challenging, as such problems quickly become intractable for classical computers…
Tricks and Plug-ins for Gradient Boosting in Image Classification
Biyi Fang, Truong Vo, Jean Utke +1
Convolutional Neural Networks (CNNs) have achieved remarkable success across a wide range of machine learning tasks by leveraging hierarchical feature learning through deep archite…
Tricks and Plug-ins for Gradient Boosting with Transformers
Biyi Fang, Truong Vo, Jean Utke +1
Transformer architectures dominate modern NLP but often demand heavy computational resources and intricate hyperparameter tuning. To mitigate these challenges, we propose a novel f…
Unsupervised Video Summarization via Iterative Training and Simplified GAN
Hanqing Li, Diego Klabjan, Jean Utke
This paper introduces a new, unsupervised method for automatic video summarization using ideas from generative adversarial networks but eliminating the discriminator, having a simp…
Video to Video Generative Adversarial Network for Few-shot Learning Based on Policy Gradient
Yintai Ma, Diego Klabjan, Jean Utke
The development of sophisticated models for video-to-video synthesis has been facilitated by recent advances in deep reinforcement learning and generative adversarial networks (GAN…