Summary of How Can Deep Neural Networks Fail Even with Global Optima?, by Qingguang Guan
How Can Deep Neural Networks Fail Even With Global Optima?by Qingguang GuanFirst submitted to arxiv…
Summary of Instance Selection For Dynamic Algorithm Configuration with Reinforcement Learning: Improving Generalization, by Carolin Benjamins et al.
Instance Selection for Dynamic Algorithm Configuration with Reinforcement Learning: Improving Generalizationby Carolin Benjamins, Gjorgjina Cenikj,…
Summary of Deep Learning Activation Functions: Fixed-shape, Parametric, Adaptive, Stochastic, Miscellaneous, Non-standard, Ensemble, by M. M. Hammad
Deep Learning Activation Functions: Fixed-Shape, Parametric, Adaptive, Stochastic, Miscellaneous, Non-Standard, Ensembleby M. M. HammadFirst submitted…
Summary of Adaptive Parametric Activation, by Konstantinos Panagiotis Alexandridis et al.
Adaptive Parametric Activationby Konstantinos Panagiotis Alexandridis, Jiankang Deng, Anh Nguyen, Shan LuoFirst submitted to arxiv…
Summary of Motion Meets Attention: Video Motion Prompts, by Qixiang Chen et al.
Motion meets Attention: Video Motion Promptsby Qixiang Chen, Lei Wang, Piotr Koniusz, Tom GedeonFirst submitted…
Summary of Lumina-next: Making Lumina-t2x Stronger and Faster with Next-dit, by Le Zhuo et al.
Lumina-Next: Making Lumina-T2X Stronger and Faster with Next-DiTby Le Zhuo, Ruoyi Du, Han Xiao, Yangguang…
Summary of An Autotuning-based Optimization Framework For Mixed-kernel Svm Classifications in Smart Pixel Datasets and Heterojunction Transistors, by Xingfu Wu and Tupendra Oli and Justin H. Qian and Valerie Taylor and Mark C. Hersam and Vinod K. Sangwan
An Autotuning-based Optimization Framework for Mixed-kernel SVM Classifications in Smart Pixel Datasets and Heterojunction Transistorsby…
Summary of Optimized Speculative Sampling For Gpu Hardware Accelerators, by Dominik Wagner et al.
Optimized Speculative Sampling for GPU Hardware Acceleratorsby Dominik Wagner, Seanie Lee, Ilja Baumann, Philipp Seeberger,…
Summary of Separation Power Of Equivariant Neural Networks, by Marco Pacini et al.
Separation Power of Equivariant Neural Networksby Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele SantinFirst submitted…
Summary of Sigmoid Gating Is More Sample Efficient Than Softmax Gating in Mixture Of Experts, by Huy Nguyen et al.
Sigmoid Gating is More Sample Efficient than Softmax Gating in Mixture of Expertsby Huy Nguyen,…